Springboard is an online school for 21st century skills like Data Science and UX Design

Springboard

springboard

A few years ago at an agile demo a stakeholder made a special appearance. The team was closing in on a minimum viable product. The demonstration focused on sound effects and animations. The team revealed a configurable animation board to demo the effects quickly. The experiences were easy to launch consecutively; isolated and variably configured. The animation board did not depend on the larger system but the intention was to tie each animation in later. While the team demoed, the stakeholder asked if the animation board could be evaluated for further experimentation. With this feedback the team noted the value and quickly wrote down what to explore next. Of course, this wasn’t the first time the team used the technique. Other similar discoveries were made during previous demos. The team was aware the feature isolation and containment was incredibly powerful both for their demos and for product value. unrealized For us as engineers, naming things is really hard. Harder still is how to communicate things. To the above story, there exists no vocabulary to describe the effort of execution. There is no description for the iterative containment orchestration in . software engineering So this is what I am to propose, a definition to describe the unique execution with its benefits and drawbacks. Developing and demoing in containment is an example of what I call the . springboard pattern Let’s describe what the pattern is. What Is The Springboard Pattern? The springboard pattern is known as a pattern. Mobile operating systems that have constrained viewing areas have used the pattern widely. The app launcher is an example. visual design The springboard visual design pattern used on app launchers. Our introductory story and its animation board also fits this model. We can think of the animation board as the contained screen launcher and each animation as an contained app with its configurations. When applied to software development, the springboard pattern acts as a guardrail to develop features in isolated pieces that are easily on the platform. There are many benefits to engineering and product. The pattern is a way to operationally execute both and . demonstrable iteratively incrementally The springboard pattern is a way to keep dependencies in check and develop features on a cycle centered around . Here are the rules an engineer must follow while iterating. product demonstrations The feature… Is launched from a board that includes other features. Can launch quickly with minimum setup. Can launch on its own and in any order. Can be configured to launch in any state. Resists larger system coupling and dependencies. If we follow these rules as a feature is developed, magic happens. This includes promotion of modularity, testability and build time, unrealized product ideation, engineer efficiency and advantages of the framework. Let’s discuss these next. Promotes Modularity The springboard pattern insists features to be developed in isolation from one another. As each feature is developed, the team must do their best to develop the solution in . containment Dependencies will certainly be used but the layers must be made to cleanly separate the feature for demonstration. The feature should be modularized and independent. As the iterations continue and demos succeed, the springboard item should then be integrated into the larger system. As this occurs, the team should continue to resist coupling and ensure the feature code cohesion is high. From start to finish, each item should have a weak measure of . connascence The springboard design pattern. At any time during the cycle the pattern can be easily violated, diminishing the return of the modularization and to the springboard pattern. Therefore, the team must make decisions by leaning on tools of layering, wrapping, and flow of control using dependency inversion. prudent and deliberate Supports Testability And Build Time The development of a demonstrable item from the springboard must be tested well. The unit tests that are developed will also serve as documentation of the module. The concept of the springboard pattern is one that promotes testability. Its dependencies should be highly configurable. The feature should have available configurations available for its . Thus this promotes ease of testing and mocking of all situations of the feature. dependency injections Build time also is maintained and the complexity of the codebase is normalized with each feature. Incoming features can be not to be built and those features that are rejected from the demos are continuously removed. flagged Finally, a natural phenomenon of the springboard pattern can reveal and produce of that individual feature. The feature had started a life without the larger system to prove only itself. The springboard can produce tools that test part of the feature in contra to the larger system as they are their own subsystems. diagnostic test tooling Product Ideation And Engineer Efficiency Opportunities happen when products are deconstructed into independent pieces. In the case of the introduction example, there appeared to be an unrealized product value in the use of an animation board. Stakeholders refer to the features of their products as cohesive constructs and use vocabulary to describe them. Wouldn’t it be powerful to immedaitely find the feature without friction? The springboard gives us a and allows for between engineers and gives us a tool to quickly how each feature was built. learning library cross pollination locate A simple springboard example with domain language. As an additional benefit, the engineers work is to be demonstrated at a moments notice. The usual cost of the time to prepare for the demo (you giving time for the engineers to prep, yes?) is offset by a more isolated solution. always available are Mileage may vary depending on domain and the reception from stakeholders. In the most pragmatic terms, products must predict less and experiment more. Having the features deconstructed and isolated may predict a different outcome or a reconfiguration of that product value. Framework Support With the springboard pattern, there could be undiscovered benefits that coincide with features of the framework. The framework the team works with may vary. For this post, I’ll discuss Android in relation to the use of a springboard. efficiency Recently in the Android ecosystem, Google has launched and discussed at length the incorporation and break out of new concepts in the area called . As we can see from above, everything that is demonstrable to stakeholders should be modular and isolated. As the work is developed, insulate each feature from major dependencies and optimize dependencies for every feature. Product may want to launch these features separate or together. Instant Apps feature modules Another example on Android is the concept of isolated . Each activity should be able to launched in isolation taking only what it needs to survive an experience. If features are built in isolated activities, the software acquire pieces of an application that can be easily reconfigured to taste. activities Finally with the latest versions of the Android, its tooling have significantly improved. Independent modules allow for building abilities which significantly decrease build time. Setups that use code organization may cause building delays especially if the product dimensions are extensive. flavored Before we conclude, there are drawbacks to consider. Drawbacks There are possible drawbacks to this mode of execution. The team will have to make decisions that make the most sense to steer clear of over engineering. The springboard approach may… — “ ”. The team should build only what they need, and not a single line more. Violate YAGNI You ain’t gonna need it — the best architectural decisions are ones that are deferred. Operating this way may force harder code decisions sooner. Accelerate decisions — additional logic to support layering and modularization may increase time to contribute and slightly longer development time. Increase complexity However, keep in mind that the cost paid will most certainly provide a cost benefit for code that is consistent and adaptable. needs room to breathe and the code and products deserve that breathing room. Adaptability Now let’s wrap this up. Spring Into Action Developing for isolation and modularity is a practice all engineers should strive for. However there had not been a pragmatic approach to these concepts and a way to describe how to execute on them. It is assumed engineers simply build this way but the reality is that they simply do not. The in software development finally gives us a word to use to communicate our intention both in software execution. When adhering to this pattern, we manage and increase . As described above, the benefits are plenty, but be aware of the cost of drawbacks. springboard pattern complexity optionality The springboard pattern takes effort and drive but the benefits could be incredible to the team and to their products. Center the pattern around the team demos and adhere to it.

The Springboard Pattern

Fund Your Web3 Development With These Grant Programs

এই অনুদান প্রোগ্রামগুলির সাথে আপনার ওয়েব3 বিকাশের জন্য অর্থায়ন করুন

Finanzieren Sie Ihre Web3-Entwicklung mit diesen Förderprogrammen

Financia tu desarrollo Web3 con estos programas de subvenciones

Financez votre développement Web3 avec ces programmes de subventions

इन अनुदान कार्यक्रमों के साथ अपने वेब3 विकास को वित्तपोषित करें

これらの助成金プログラムを利用して Web3 開発に資金を提供しましょう

이 보조금 프로그램으로 Web3 개발 자금을 조달하세요

Financie seu desenvolvimento Web3 com estes programas de subsídios

Финансируйте свою разработку Web3 с помощью этих грантовых программ

Web3 Geliştirmenizi Bu Hibe Programlarıyla Finanse Edin

Tài trợ cho việc phát triển Web3 của bạn bằng các chương trình tài trợ này

利用这些资助计划资助你的 Web3 开发

PayPal Abandoned Me; Crypto Saved Me

পেপ্যাল আমাকে পরিত্যাগ করেছে; ক্রিপ্টো আমাকে বাঁচিয়েছে

PayPal hat mich im Stich gelassen; Krypto hat mich gerettet

PayPal me abandonó; Cripto me salvó

PayPal m'a abandonné ; La crypto m'a sauvé

पेपाल ने मुझे छोड़ दिया; क्रिप्टो ने मुझे बचाया

PayPal は私を見捨てたが、暗号通貨は私を救った

PayPal이 나를 버렸습니다. 암호화폐가 나를 구해줬어요

PayPal me abandonou; A criptografia me salvou

PayPal оставил меня; Крипто спасло меня

PayPal Beni Terk Etti; Kripto Beni Kurtardı

PayPal đã bỏ rơi tôi; Tiền điện tử đã cứu tôi

PayPal 抛弃了我；加密货币拯救了我

The Power of Universal Semantic Layers: Insights from Cube Co-founder Artyom Keydunov

The change in sentiment surrounding Wall Street has been palpable as stubborn inflation continues in its refusal to subside. Following December’s buoyant outlook and the expectation among some that rate cuts could come as soon as March, markets are now having to react to the very real possibility that there may be no cuts at all this year. But how could a higher-for-longer scenario impact the S&P 500? March had been pinpointed as an optimistic stage for the beginning of the Fed’s switch to a dovish monetary policy as the battle against inflation continued to be won. Instead, it was March’s Consumer Price Index (CPI) figures that sparked concern throughout Wall Street. CPI inflation surpassed expectations to post a 3.5% increase in consumer prices for the year to March. Although it weighed in only a little higher than its 3.4% forecast, the headlines were clear: high inflation isn’t going anywhere fast. The S&P 500 reacted to the news by retracing sharply from a period of consistent growth that began in late October 2023, posting a decline of more than 5% from its March 28th peak of 5,254.35. Following the decline, the contrast between the optimistic start to Q1 2024 and Q2 is jarring. While the S&P 500 posted growth of more than 10% in the first quarter, much of its progress has been undone by the shifting economic outlook. More pessimism could be on the way. Although the market-implied odds for no cuts to take place at all in 2024 remains low at 11%, confounding inflation figures could see the prospect of a higher-for-longer period of high inflation manifest throughout the year. According to Bank of America economists, the prospect of no rate cuts until March 2025 at the earliest is a “real risk.” The economists still believe that one single cut taking place throughout the year is the most likely scenario, but it’s clear that investors need to consider the possibility of inflation staying for a good while longer on Wall Street. At the beginning of the year, forecasts had been suggesting that at least six quarter-percentage point reductions would be likely, and markets had largely priced in lower rates moving into the new year. This makes April’s inflation figures especially worrying. But what’s next for the S&P 500 and Wall Street as a whole? Keeping Up With Expectations Wall Street has largely managed to perform well amid historically high interest rates in 2023, so why is the news that rates may stay higher for longer so concerning? The cause for concern stems from the market’s ability to anticipate events and prices in its expectations many months in advance. The S&P 500’s market rally of more than 25% between late October and late March has been down in no small part to the anticipation that the Fed’s switch to a dovish monetary policy means rate cuts are imminent. We can see in the index’s rapid 5% drop that these shifting expectations are a key cause for concern among investors, who may be exploring more safe haven strategies while uncertainty creeps back into Wall Street. Here, the problem stems from the S&P 500’s exceptional form in the wake of Federal Reserve rate cuts. Investors likely saw parallels between the 2023 economic climate and 1995, in which the Fed doubled interest rates to 6% in 12 months before undergoing a series of cuts once inflation calmed to 2%. With the final rate hike arriving on February 1st and the first cut taking place on July 6th of the same year, 1995 became a springboard for growth on the S&P 500, with the index posting 34% growth–its highest annual gain since the 1950s. As the parallels broke down and CPI data arrived hotter than expected, the timely reality check for the S&P 500 has been particularly tumultuous. What Will Higher for Longer Look Like? With interest rate hikes in 2023 coinciding with the generative AI boom, the S&P 500 actually posted a strong annual growth rate of 24%. Should the rate of innovation in this industry continue to facilitate both hype and adoption at an enterprise level, it’s entirely possible that big tech stocks can continue to bring positivity to US markets even during times of high-interest rates. However, the wider impact of higher-for-longer rates can be varied depending on the impacted stocks and their fundamentals. While the first interest rate hikes in 2022 saw stocks with high valuations struggle, the 2023 macroeconomic climate forced more investors to look instead at how the bottom line of companies was being impacted by higher rates. Rob Haworth, senior investment strategy director at U.S. Bank Wealth Management, suggests that this puts smaller companies under the microscope due to issues in funding at higher rates, as opposed to more resilient larger companies with higher liquidity to navigate uncertainty. Data supports this thesis. While the large-cap stocks populating the S&P 500 Growth Index suffered a 29.41% decline in 2022, the small-cap stocks among the Russell 2000 Index performed better, experiencing smaller losses of 20.44%. These fortunes were reversed in 2023, with the S&P 500 Growth and Russell 2000 posting growth of 30.03% and 16.93% respectively. This trend is continuing into 2024, and recent disappointment surrounding the expectation of rate cuts is likely to push more investors to look for stocks that offer economic stability, rather than riskier opportunities based on innovation. With this in mind, the S&P 500 stocks that boast stronger balance sheets and higher cash reserves could become a leading choice on the index, but backtracking rate expectations will likely pave the way for more long-term volatility throughout US markets. “Given these dynamics, investors may choose to take a balanced approach by diversifying their portfolios to include both safe assets such as gold and riskier assets such as both growth and value stocks,” explained Maxim Manturov, head of investment research at Freedom Finance Europe. “While cautious optimism may prevail in the stock market, the appeal of gold as a hedge against economic uncertainty remains attractive, from a tactical perspective.” “Gold's expected upside is emphasized by the speculative potential offered by the NUGT ETF (Direxion Daily Gold Miners Index Bull 2x Shares), presenting an attractive proposition for investors in terms of risk/reward ratio from current levels.” Diversification Remains Key for Investors Although we’re experiencing a generative AI boom, the uncertainty of the current economic climate suggests that more diversification should be a priority for investors. Building exposure to more commodities can be an excellent way of hedging against more disappointment and confounding inflation figures in 2024, but investor optimism can help to drive markets off the back of good news. The record-breaking S&P 500 rally of 1995 will shape sentiment today, and the arrival of any lower-than-expected CPI data could see more optimism flood back into US markets. While it’s difficult to anticipate Fed rate cuts in 2024, sentiment will continue to shape Wall Street performance throughout the year, and with this in mind, maintaining some levels of exposure can go a long way toward building a sustainable portfolio amid wider market uncertainty. The change in sentiment surrounding Wall Street has been palpable as stubborn inflation continues in its refusal to subside. Following December’s buoyant outlook and the expectation among some that rate cuts could come as soon as March, markets are now having to react to the very real possibility that there may be no cuts at all this year. But how could a higher-for-longer scenario impact the S&P 500? March had been pinpointed as an optimistic stage for the beginning of the Fed’s switch to a dovish monetary policy as the battle against inflation continued to be won. Instead, it was March’s Consumer Price Index (CPI) figures that sparked concern throughout Wall Street. CPI inflation surpassed expectations to post a 3.5% increase in consumer prices for the year to March. Although it weighed in only a little higher than its 3.4% forecast, the headlines were clear: high inflation isn’t going anywhere fast. 3.5% increase 3.5% increase The S&P 500 reacted to the news by retracing sharply from a period of consistent growth that began in late October 2023, posting a decline of more than 5% from its March 28th peak of 5,254.35. Following the decline, the contrast between the optimistic start to Q1 2024 and Q2 is jarring. While the S&P 500 posted growth of more than 10% in the first quarter , much of its progress has been undone by the shifting economic outlook. more than 10% in the first quarter more than 10% in the first quarter More pessimism could be on the way. Although the market-implied odds for no cuts to take place at all in 2024 remains low at 11%, confounding inflation figures could see the prospect of a higher-for-longer period of high inflation manifest throughout the year. According to Bank of America economists , the prospect of no rate cuts until March 2025 at the earliest is a “real risk.” The economists still believe that one single cut taking place throughout the year is the most likely scenario, but it’s clear that investors need to consider the possibility of inflation staying for a good while longer on Wall Street. Bank of America economists Bank of America economists At the beginning of the year, forecasts had been suggesting that at least six quarter-percentage point reductions would be likely, and markets had largely priced in lower rates moving into the new year. This makes April’s inflation figures especially worrying. But what’s next for the S&P 500 and Wall Street as a whole? Keeping Up With Expectations Wall Street has largely managed to perform well amid historically high interest rates in 2023, so why is the news that rates may stay higher for longer so concerning? The cause for concern stems from the market’s ability to anticipate events and prices in its expectations many months in advance. The S&P 500’s market rally of more than 25% between late October and late March has been down in no small part to the anticipation that the Fed’s switch to a dovish monetary policy means rate cuts are imminent. We can see in the index’s rapid 5% drop that these shifting expectations are a key cause for concern among investors, who may be exploring more safe haven strategies while uncertainty creeps back into Wall Street. Here, the problem stems from the S&P 500’s exceptional form in the wake of Federal Reserve rate cuts. Investors likely saw parallels between the 2023 economic climate and 1995, in which the Fed doubled interest rates to 6% in 12 months before undergoing a series of cuts once inflation calmed to 2%. likely saw parallels likely saw parallels With the final rate hike arriving on February 1st and the first cut taking place on July 6th of the same year, 1995 became a springboard for growth on the S&P 500, with the index posting 34% growth–its highest annual gain since the 1950s. As the parallels broke down and CPI data arrived hotter than expected, the timely reality check for the S&P 500 has been particularly tumultuous. What Will Higher for Longer Look Like? With interest rate hikes in 2023 coinciding with the generative AI boom, the S&P 500 actually posted a strong annual growth rate of 24%. Should the rate of innovation in this industry continue to facilitate both hype and adoption at an enterprise level, it’s entirely possible that big tech stocks can continue to bring positivity to US markets even during times of high-interest rates. However, the wider impact of higher-for-longer rates can be varied depending on the impacted stocks and their fundamentals. While the first interest rate hikes in 2022 saw stocks with high valuations struggle, the 2023 macroeconomic climate forced more investors to look instead at how the bottom line of companies was being impacted by higher rates. Rob Haworth, senior investment strategy director at U.S. Bank Wealth Management, suggests that this puts smaller companies under the microscope due to issues in funding at higher rates, as opposed to more resilient larger companies with higher liquidity to navigate uncertainty. Data supports this thesis. While the large-cap stocks populating the S&P 500 Growth Index suffered a 29.41% decline in 2022, the small-cap stocks among the Russell 2000 Index performed better, experiencing smaller losses of 20.44%. These fortunes were reversed in 2023, with the S&P 500 Growth and Russell 2000 posting growth of 30.03% and 16.93% respectively. growth of 30.03% and 16.93% growth of 30.03% and 16.93% This trend is continuing into 2024, and recent disappointment surrounding the expectation of rate cuts is likely to push more investors to look for stocks that offer economic stability, rather than riskier opportunities based on innovation. With this in mind, the S&P 500 stocks that boast stronger balance sheets and higher cash reserves could become a leading choice on the index, but backtracking rate expectations will likely pave the way for more long-term volatility throughout US markets. “Given these dynamics, investors may choose to take a balanced approach by diversifying their portfolios to include both safe assets such as gold and riskier assets such as both growth and value stocks,” explained Maxim Manturov, head of investment research at Freedom Finance Europe . Freedom Finance Europe “While cautious optimism may prevail in the stock market, the appeal of gold as a hedge against economic uncertainty remains attractive, from a tactical perspective.” “Gold's expected upside is emphasized by the speculative potential offered by the NUGT ETF (Direxion Daily Gold Miners Index Bull 2x Shares), presenting an attractive proposition for investors in terms of risk/reward ratio from current levels.” Diversification Remains Key for Investors Although we’re experiencing a generative AI boom, the uncertainty of the current economic climate suggests that more diversification should be a priority for investors. Building exposure to more commodities can be an excellent way of hedging against more disappointment and confounding inflation figures in 2024, but investor optimism can help to drive markets off the back of good news. The record-breaking S&P 500 rally of 1995 will shape sentiment today, and the arrival of any lower-than-expected CPI data could see more optimism flood back into US markets. While it’s difficult to anticipate Fed rate cuts in 2024, sentiment will continue to shape Wall Street performance throughout the year, and with this in mind, maintaining some levels of exposure can go a long way toward building a sustainable portfolio amid wider market uncertainty.

What’s the Fate of the S&P 500 if Rate Cuts Don’t Happen in 2024?

যদি 2024 সালে রেট কম না হয় তাহলে S&P 500-এর ভাগ্য কী?

Was droht dem S&P 500, wenn es 2024 nicht zu Zinssenkungen kommt?

¿Cuál es el destino del S&P 500 si no se producen recortes de tipos en 2024?

Quel sera le sort du S&P 500 si les baisses de taux ne se produisent pas en 2024 ?

यदि 2024 में ब्याज दरों में कटौती नहीं होती है तो S&P 500 का क्या होगा?

2024年に利下げが行われない場合、S&P 500の運命はどうなるでしょうか?

2024년에 금리 인하가 일어나지 않는다면 S&P 500의 운명은 어떻게 될까요?

Qual será o destino do S&P 500 se os cortes nas taxas não acontecerem em 2024?

Какова судьба S&P 500, если снижение ставок не произойдет в 2024 году?

2024'te Faiz İndirimi Olmazsa S&P 500'ün Kaderi Ne Olur?

Số phận của S&P 500 sẽ ra sao nếu việc cắt giảm lãi suất không xảy ra vào năm 2024?

如果 2024 年不降息，标准普尔 500 指数的命运将会如何？

The following are the top of my RWA projects. I put the list together based on interesting facts surrounding them, whether they talk about partnerships, connections, or proof of time acquired by cooperating with corporations and governments. Also, I am focusing on new projects that still need to prove their true potential. This article will describe several RWA projects, but the main focus is on the first three. Also, I will provide detailed reasoning between the first two projects, and it’s only my own opinion. Also, all listed projects are solid and create strong and needed competitors to create a desired competition, without the essence of which the mentioned project would not grow. Thanks to this article, you can better understand the technology and interesting projects in this space as a springboard for your own research. [1] Maple Finance The first place goes to Maple (MPL). Beyond its appealing logo (a nod to my Toronto Maple Leafs fandom) and food-inspired name), what sets this project apart are two key advantages it holds over traditional banks. First, Maple enables global capital aggregation, leveraging the Ethereum blockchain's infrastructure. Secondly, it facilitates loans worldwide. By operating on this digital platform, Maple can efficiently pool capital, create loans, and manage repayments, offering a superior alternative to traditional banking. Notably, even large-scale withdrawals from Maple are processed within hours, a testament to its efficiency and scalability. Maple's strategic alliances further enhance its appeal. It collaborates with Circle, the entity behind the USDC stablecoin, and is in active discussions with Vaneck, a potential game-changer for the project. The only hurdle in Vaneck's direct interest is the green light from DeFi user regulators, a challenge that Maple needs to be well-positioned to overcome. All in all, Maple seems more tailored for bigger investors, and one should follow the money flow. To sum it up, Maple Finance is revolutionizing DeFi and institutional lending, and I'm here for it! Their innovative use of Ethereum for global capital aggregation and worldwide loans is something impressive. With strategic partnerships enhancing its allure and a keen eye on navigating regulatory waters, Maple is positioned to bridge traditional finance and blockchain. It's an exciting time to watch Maple cater to the needs of big investors and institutions, promising a seamless blend of RWA and DeFi. Chico Crypt also covered this project in his podcasts. Yup, they have written in their cards but don't worry, the competition is very strong :) [2] LTO Network The second place goes to the LTO Network, a new player in the RWA field. However, we must remember that it is the leading blockchain in Europe for business and corporate use. Their achievements and contributions to blockchains paved the way for successfully delivering the DeFi RWA bridge that connects real-world assets with DeFi liquidity. Their main advantage is their background in law; thus, they have a better chance to score big with DeFi regulators and find a way to do business with each country's legislation. The Dapps on LTO Network now offer a range of tools that solve broader issues such as identity, digital ownership, and privacy. Their latest solution for bridging real-world assets (RWA) on a chain is extremely cool. You can now tokenize everything in a so-called “ Ownable” and hold/trade and consume these in your wallet. Everything on LTO is also GDPR compliant, and they have another company founded by LTO Network CEO, , which solves the taxes and legislation for their business. Besides, their key partnerships, especially with Unizen, are crucial for improving RWA and DeFi integration, ensuring secure, transparent DeFi access for institutions. Also, the upcoming EQTY platform launch is highly anticipated and set to centralize RWA operations and enhance DeFi liquidity ties, marking a major leap in the RWA ecosystem's development. Other great things about this project are its unique tokenomics and history records, which put it on the map as a serious and verified-by-time project (since 2018). Also, it is good to remember its connections with Polygon, Chainlink, and Curve, which provide massive advantages in gathering needed liquidity and proper operability with other blockchains. To bring this home, here is the last thing I want to say: Centralization often hampers the integration of Real World Assets (RWA) into the blockchain, posing a risk to asset security. LTO Network fixes this with a decentralized system and Layer-1 infrastructure that includes a privacy layer, ensuring that asset value is recognized and protected. Based on information shared by LTO, their users will have access to investments such as: Firm24 bar of gold stake of Private Equity (PE) that invests in cryptocurrency stake of Venture Capital (VC) funds that invest in cryptocurrency LTO Network's strengths in the RWA space lie in its familiarity with the importance of regulations for blockchain and DeFi and its founders' past working experience with legal structures and taxes. The potential combination of DeFi and RWAs provides the best possible use case for crypto, where blockchain delivers a platform for crypto in traditional money and finance. Now that third place on my list is clear. I am pretty sure Florence Finance is a solid choice that just needs to prove itself after achieving Tier 1 and 2 CEX listings and a better position in the MC leaderboard; the description is just a little bit lower in this article. It is time to explain what led me to decide first and second place. Maple Finance may outperform LTO Network by offering more specialized financial instruments and lending solutions due to its focus on decentralized corporate debt markets. Its emphasis on institutional borrowers and undercollateralized loans could provide businesses with more tailored capital-raising and liquidity management options. Additionally, Maple Finance's expertise in DeFi lending and navigating financial regulations may offer advantages to users seeking specialized financial services on the blockchain. On the other hand, LTO Network's broad utility in enhancing business processes, coupled with its innovations in asset management and data privacy, positions it as a versatile and secure platform for organizations looking to leverage blockchain technology for a wide range of applications beyond the scope of DeFi lending and liquidity solutions offered by Maple Finance. Besides, LTO Network excels in bridging digital and traditional financial systems by facilitating tokenizing and managing real-world assets. This capability allows for the seamless integration of physical assets into the blockchain, providing users with innovative ways to manage and verify ownership - a significant advancement in asset liquidity and accessibility. If we add Rick Schmitz's background as a tax lawyer and well-established connection, we will have strong competition for Maple Finance if the cards are played right. Besides, both can have similar yet distinct areas of interest, thus attracting different sets of clientele. Now, I will go to project number three, the last-ranked project on my list. [3] Florence Finance Florence Finance (FF). Another new player in the field, and third place on my list, still needs to be added to tier 1 or 2 CEXes; thus, it provides a decent narrative for a run. Florence's founder is Chiel Ruiter, a former Managing Director at Goldman Sachs and UBS, who leads the project. Alongside him is Leo Greve, who brings extensive experience at ING Bank and Citigroup. While having team members with established careers and connections is beneficial, FF seeks to transcend the need for corporate affiliations. The project aims to democratize access to the RWA ecosystem for both large and small crypto investors, eliminating the reliance on institutional intermediaries. The platform's integration with the USDC, EURS & EURA stablecoins, issued by Circle, STASIS, and Angle Protocol, marks a significant step in its evolution. This integration enhances transparency and adds stability, leveraging Stasis & Angle's status as the widely used and successful Euro stablecoins in the DeFi space. The team's knowledge is good, and based on my research, Rick Schmitz, the LTO Network founder and industry leader in blockchain, was an advisor in the early days. FF is not just another project. It's an Arbitrum blockchain innovation that bridges Real-World Assets (RWA) and Decentralized Finance (DeFi). The platform opens doors to financial tools and markets, traditionally accessible only to those with substantial portfolios and connections. This unique approach piques curiosity and sets Florence apart. Florence's mission is clear: efficiently and transparently converting users' excess stablecoin balances into Euro-denominated, yield-generating loans for European SMEs. This vision fosters a collaborative platform between users and SME lenders, inspiring a new era of financial inclusivity. The protocol's design ensures that it never loans out more than the raised funds, operating without leverage or fractional reserves. While users may temporarily face liquidity constraints in converting FLR to stablecoins, the solidity of FF and the underlying loan portfolio remains unaffected and has over three years of onchain provenance without credit events. Clearpool First place out of my top three, yet I need to say the one with the most active marketing, measured based on the cardinality of created blog posts  and a Twitter presence. Clearpool has a special place in this article, mainly because it provides good competition for Maple, even though it focuses on different market aspects. Clearpool is known for its unique approach to uncollateralized lending pools, enabling individual and institutional liquidity providers to offer capital to borrowers directly. It emphasizes dynamic interest rates based on pool liquidity and borrower demand, whereas, on the other hand, Maple opts for structured corporate debt, allowing crypto-native companies and institutional borrowers to obtain undercollateralized loans. While their name, Clearpool, makes us think of the fun-filled movie Deadpool, Clearpool is "dead" serious about its approach, which is to connect various RWA stakeholders using permissionless marketplaces. Besides, it is pioneering the bridge between traditional finance and DeFi while maintaining compliance with regulations. Clearpool is a decentralized finance ecosystem incorporating the first-ever permissionless marketplace for unsecured institutional liquidity. Driven by market forces of supply and demand, Clearpool’s permissionless single-borrower pools enable institutions to raise short-term capital while providing DeFi lenders access to risk-adjusted returns based on interest rates derived by market consensus. A second, fully permissioned institutional-grade platform meets the compliance needs for wholesale borrowing and lending of digital assets by institutional market participants. This is a non-custodial, institutional-grade marketplace where you can connect to the largest global KYC and AML-compliant network for wholesale borrowing and lending of digital assets. Since Clearpool is permissionless, you can lend directly to whitelisted institutions and earn risk-adjusted returns without a lock-up period. The Clearpool Oracle network, composed of various institutions, votes on parameters determining permissionless pools' interest rates. The rest of the RWA I will list here lies on a similar level for me, yet they differ in a special gambit here and there. They all have proof of record, achievements under their belt, and already working products. Besides, mentioning some competitors and providing a complete picture is always good, so here it is: Aave Aave is the largest DeFi project currently on the market. It operates and governs the network through a decentralized autonomous organization (DAO), so its significance must be considered. Being a DAO means Aave has a governance token that allows people to vote and participate in network ecosystems. While their product is good, the Aave token as an investment provides another reason to give it a go when the RWA bulls are back in town. Aave is a decentralized finance application that allows people to lend and borrow cryptocurrencies to earn fees. It is also a Source Protocol to create Non-Custodial Liquidity Markets to earn interest on supplying and borrowing assets with variable or stablecoins. Aave offers peer-to-peer lending using crypto as a traded asset. It uses an algorithm to determine lending rates and match lenders to borrowers. Aave has an associated Aave token, an Ethereum-based token that powers the governance of its platform. Ondo Finance Ondo Finance has grabbed my attention due to the institutional grade RWA structure they have implemented. I can see their platform appealing to investors looking for something closer to the world of traditional finance. Ondo Finance (OF) provides access to RWA-backed pools for yield generated from real-world assets such as treasury bonds and other institutional-grade assets. OF is also a DeFi platform that offers structured investment products, combining fixed-income and variable-yield strategies within the cryptocurrency market. It aims to bridge traditional and decentralized finance by providing users with diversified investment options. Ondo allows investors to choose between stable, lower-risk returns and higher-risk, variable returns, catering to different risk appetites. This approach makes DeFi more accessible to a broader range of investors, particularly those seeking structured and diversified investment strategies in crypto. Goldfinch Finance Borrowing capacity and access to liquidity are major drawcards for RWAs, and Goldfinch is firmly exploring this area. Thus, I am including it on my list. Goldfinch is a decentralized finance protocol that extends credit to borrowers without requiring traditional crypto collateral (it eliminates the need for borrowers to over-collateralize their loans with on-chain assets). It allows investors to supply capital to borrower pools, which is then lent out. The project aims to expand access to capital, especially in emerging markets, by leveraging off-chain credit assessments to make loans. Goldfinch focuses on creating a more inclusive finance model by bridging DeFi and traditional credit markets. Borrowers (currently off-chain lending businesses) propose deal terms for credit lines (Borrower Pools) to the protocol. Goldfinch's community of Investors can then supply capital to these credit lines (Pools), either directly to individual Pools (as Backers) or indirectly by automatically allocating capital across the protocol (Liquidity Providers via the Senior Pool). These Borrower businesses use their credit lines to draw down stablecoins, specifically USDC, from their Pool. Borrowers then exchange the USDC for fiat currency and deploy it on the ground to end-borrowers in their local markets. Thus, the protocol provides the utility of crypto—specifically, its global access to capital—while leaving the actual end-borrower loan origination and servicing to the businesses best equipped to handle that in their communities. The end

Unlocking 2024/25: The Ultimate Guide to Top RWA Crypto Projects

2024/25 আনলক করা: শীর্ষ RWA ক্রিপ্টো প্রকল্পের চূড়ান্ত নির্দেশিকা

2024/25 freischalten: Der ultimative Leitfaden für die besten RWA-Kryptoprojekte

Desbloqueo 2024/25: la guía definitiva para los principales proyectos criptográficos de RWA

Déverrouillage 2024/25 : le guide ultime des meilleurs projets de cryptographie RWA

अनलॉकिंग 2024/25: शीर्ष आरडब्ल्यूए क्रिप्टो परियोजनाओं के लिए अंतिम गाइड

2024/25 年のロック解除: トップ RWA 暗号プロジェクトへの究極ガイド

2024/25 잠금 해제: 최고의 RWA 암호화폐 프로젝트에 대한 궁극적인 가이드

Desbloqueando 2024/25: o guia definitivo para os principais projetos de criptografia RWA

Разблокировка 2024/25: полное руководство по лучшим криптопроектам RWA

2024/25'in Kilidini Açma: En İyi RWA Kripto Projelerine İlişkin Temel Kılavuz

Mở khóa 25/2024: Hướng dẫn cơ bản về các dự án tiền điện tử RWA hàng đầu

解锁 2024/25：顶级 RWA 加密项目终极指南

Uniting Titans of AI: SingularityNet Investors Eye Option2Trade's $888K Bonanza In the dynamic intersection of and , two titans stand poised for a historic convergence. , a beacon of A.I.-powered trading innovation, has unfurled an enticing $888,000 giveaway, capturing the imagination of investors from SingularityNet (AGIX), a community deeply rooted in the advancement of A.I. technologies. This magnetic pull towards Option2Trade’s (O2T) giveaway underscores a shared vision between Option2Trade (O2T) and SingularityNet’s (AGIX) aficionados—leveraging artificial intelligence to redefine the boundaries of financial growth and technological progress. artificial intelligence cryptocurrency Option2Trade (O2T) A Meeting of Minds and Machines The allure of Option2Trade's (O2T) $888k giveaway has not only spotlighted the platform's prowess in integrating A.I. into trading but has also resonated with the SingularityNet (AGIX) community, known for championing the cause of decentralized A.I. networks. This alignment of interests heralds a new era of collaboration and innovation in the crypto space. The A.I. Revolution Beckons Both Option2Trade (O2T) and SingularityNet (AGIX) stand at the forefront of the A.I. revolution, driving forward with the mission to harness A.I. for groundbreaking applications—in trading for Option2Trade (O2T), and a decentralized marketplace of A.I. services for SingularityNet (AGIX). The $888k giveaway by Option2Trade (O2T) not only serves as a magnet for investors but also as a beacon for A.I. enthusiasts within the SingularityNet (AGIX) community, highlighting the vast potential of A.I. in transforming the financial landscape. The O2T Giveaway: A Springboard for A.I. Integration Option2Trade's (O2T) bold move to offer an $888,000 giveaway is more than a marketing strategy; it's a testament to the platform's confidence in its AI-driven trading solutions and a commitment to fostering a community of forward-thinking investors. SingularityNet Investors: Diving into the A.I. Trading Arena For investors in , the Option2Trade (O2T) giveaway represents an unparalleled opportunity to diversify their portfolios with a platform that aligns with their technological ethos and investment philosophy. SingularityNet (AGIX) From A.I. Services to A.I. Trading SingularityNet (AGIX) investors, already attuned to the nuances of A.I. and its transformative potential, find in Option2Trade’s (O2T) giveaway an opportunity to expand their investment horizons into A.I.-powered trading. By engaging with Option2Trade (O2T), SingularityNet (AGIX) investors not only stand a chance to win a substantial sum but also to become part of a pioneering community at the intersection of A.I. and finance. Envisioning a Future Fueled by A.I. As the Option2Trade (O2T) giveaway draws widespread attention, including from the keen minds behind SingularityNet (AGIX), the future seems poised for an explosion of A.I.-driven innovations in the financial domain. This partnership in spirit between Option2Trade (O2T) and SingularityNet (AGIX) investors underscores a collective march towards a future where A.I. shapes not just the tools of trade but the very fabric of financial success. In conclusion, as Option2Trade (O2T) unfurls its $888k giveaway, it not only sets the stage for a monumental shift in A.I.-powered trading but also invites a partnership with the visionary investors of SingularityNet (AGIX). Together, they embody the pioneering spirit of the crypto and A.I. community, charting a course towards a future where technology and finance merge to unlock new realms of possibility and prosperity. For more information on the Option2Trade (O2T) Presale: Use promo code O2TLaunch to get a 15% bonus Visit Option2Trade Join and become a community member: | Twitter Telegram This story was distributed as a release by B TCwire under HackerNoon’s Business Blogging  Program. Learn more about the program here: https://business.hackernoon.com/

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SingularityNet (AGIX) 投资者青睐人工智能巨头 Option2Trade (O2T) 的 88.8 万美元赠品

87 Stories To Learn About Machinelearning

Let's learn about via these 64 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Machine Learning Tutorials /Learn Repo 1. Top 9 Free Beginner Tutorials for Machine Learning (ML) This post includes a round-up of some of the best free beginner tutorials for Machine Learning. 2. Golang in Machine Learning Can Golang be used in Machine Learning? In the article you will learn advantages and disadvantages of using Go lang in Machine learning 3. How to Build an Image Search Engine to Find Similar Images After reading this article, you will be able to create a search engine for similar images for your objective from scratch 4. Beat The Heat with Machine Learning Cheat Sheet If you are a beginner and just started machine learning or even an intermediate level programmer, you might have been stuck on how do you solve this problem. Where do you start? and where do you go from here? 5. How to Leverage Machine Learning to Improve AdWords Efficiency Recent issues surrounding racial inequality in the United States have led to direct action in the digital marketing world as well. More and more companies are pausing their Facebook ad campaigns because of the social network’s inaction on discrimination and hate speech. 6. Automatic Feature Selection in Python: An Essential Guide Feature Selection in python is the process where you automatically or manually select the features in the dataset that contribute most to your prediction. 7. How To Compare Documents Similarity using Python and NLP Techniques In this post we are going to build a web application which will compare the similarity between two documents. We will learn the very basics of natural language processing (NLP) which is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. 8. An Essential Python Text-to-Speech Tutorial Using the pyttsx3 Library Basically, what we want to do is to give some piece of text to our program and it will convert that text into the speech and will read that to us. 9. The Four Types of Machine Learning | Part 2 In the previous post, we saw the first two types of machine learning. In this post, we will discuss the other two types of machine learning. These are — Semi-su 10. Pycaret: A Faster Way to Build Machine Learning Models Pycaret is an open-source, low code library in python that aims to automate the development of machine learning models. 11. Evaluating Regression Models in Machine Learning Model evaluation is very important since we need to understand how well our model is performing. 12. Image Style Transfer And Video Transformation In EbSynth Using EbSynth and Image Style Transfer machine learning models to create a custom AI painted video/GIF. 13. Build a GUI for Your Machine Learning Models How to build a cool GUI for your Machine Learning models with Gradio so that you can visualise your models easily and effectively for people to understand. 14. Kinetics Dataset - Training and Evaluating Models for Video Classification A guide to using the open-source tool FiftyOne to download the Kinetics dataset and evaluate video understanding models 15. How I Approached Machine Learning Interviews at FAANGs as an ML Engineer Cracking a Machine learning interview at companies like Facebook, Google, Netflix, Snap etc. really comes down to nailing few patterns that FAANGs look for. 16. How to Train Computer Vision Models Efficiently The starting point of building a successful computer vision application is the model. Computer vision model training can be time-consuming and challenging if one doesn’t have a background in data science. Nonetheless, it is a requirement for customized applications. 17. The Hunt for Data: Creating a Computer Vision Dataset for Road Safety In this article, I would like to share my own experience of developing a smart camera for cyclists with an advanced computer vision algorithm 18. Why and How do We Split the Dataset Dataset is one important part of the machine learning project. Without data, machine learning is just the machine, and learning is stripped from the title. Whic 19. The Four Types Of Machine Learning There are three types of machine learning. Initially, there were three, but later type added one more type to the ranks of machine learning types. Thus in total 20. What are Decision Trees in Machine Learning? Learn to measure the performance of your Regression Models - Tutorial by Berk Hakbilen 21. Artificial Intelligence (AI) VS Machine Learning (ML) - A Beginner's Guide If you are new to the AI and ML world, this guide is for you to clear the doubts between both domains. 22. Deploy Computer Vision Models with Triton Inference Server There are a lot of Machine Learning courses, and we are pretty good at modeling and improving our accuracy or other metrics. 23. 70-Page Report on the COCO Dataset and Object Detection [Part 1] Quickly find common resources and/or assets for a given dataset and a specific task, in this case dataset=COCO, task=object detection 24. How I Transfer an Artistic Style to Any Image Machine learning and artificial intelligence have been on my radar for years now, but more as a concept and “thing I should know about.” I didn’t feel that I had the free time or skills to dig into it. However, my attitude about machine learning has changed in the past few months. I have seen new and easier tools become accessible to the public. In this post I will walk you through how to transfer an art style to any image using some of these tools. 25. Top 8 Machine Learning Content Creators on YouTube Here are the top Machine Learning content creators on YouTube to follow for tutorials, deep learning, and more. 26. NLP Tutorial: Creating Question Answering System using BERT + SQuAD on Colab TPU Open sourced by Google Research team, pre-trained models of BERT achieved wide popularity amongst NLP enthusiasts for all the right reasons! It is one of the best Natural Language Processing pre-trained models with superior NLP capabilities. It can be used for language classification, question & answering, next word prediction, tokenization, etc. 27. Machine Learning Model with FLASK REST API In this tutorial we will see how you can make your first REST API for Machine Learning Model using FLASK. We will start by creating machine learning model. Then we will see step-by-step procedure to create API using Flask and test it using Postman. 28. 6 Essential Tips to Solve Data Science Projects Data science projects are focusing on solving social or business problems by using data. Solving data science projects can be a very challenging task for beginners in this field. You will need to have a different skills set depending on the type of data problem you want to solve. 29. Building a Monte Carlo Markov Chain Pipeline Using Luigi A few months ago I was accepted into a data science bootcamp - Springboard, for their data science career track. As part of this bootcamp I had to work on Capstone projects that would help build my portfolio, show my ability to extract, clean up data, build models and extract insights from said models. For my first project I opted to build a Monte Carlo Markov Chain pipeline initially with the objective of building a multi-touch attribution model that would help me understand conversion rates from different states in the signup process and use that to understand which channels appeared to deliver the greatest conversion rates for users coming through a given landing page and transitioning through the different signup states defined in my dataset. 30. From TF to TFLite: Deploying ML Models on Mobile [Part 1] tl;dr - Link to code: TensorFlow GAN model. So the other day I was talking to my rubber ducky about how G-Board predicts my next word, even when those words are entirely made up by me, in that how it actually learns on-device. How amazingly Netflix, Amazon, Google Maps make use of machine learning in their apps. How does machine learning on apps even work? Does the model learn even after being deployed? Can I deploy a GAN model on mobile? 31. NLP Tutorial: Topic Modeling in Python with BerTopic Topic modeling is an unsupervised machine learning technique that can automatically identify different topics present in a document (textual data). Data has become a key asset/tool to run many businesses around the world. With topic modeling, you can collect unstructured datasets, analyzing the documents, and obtain the relevant and desired information that can assist you in making a better decision. 32. 9 Reasons Why You Should Keep Learning Machine Learning Machine Learning is an application of Artificial Intelligence. It allows software applications to become accurate in predicting outcomes. Machine Learning focuses on the development of computer programs, and the primary aim is to allow computers to learn automatically without human intervention. 33. Top 5 Machine Learning Platforms to Watch in 2022 Machine Learning Operations (MLOps) is a form of DevOps in a growing area. In this article, we'll discuss the top 5 Machine Learning Platforms to watch in 2022. 34. Logistic Regression: Train Model In Python And Use It on Angular Front End Demo for this article can be found here. 35. Machine Learning Explained in 5 Minutes Google uses it to provide millions of search results every hour. It helps Facebook guess your next love interest. Even Elon Musk’s Tesla uses it to make self-dr 36. Adversarial Examples In Machine Learning Explained There are easy ways to build adversarial examples that can fool any deep learning model and create security issues no matter how complex the model is. 37. Why Data Science Competitions are Important & How to Get Started To become a Data Scientist, you have to learn, gain the required skills and practice a lot to get more experience. Participating in data science competitions has been one of the best approaches to help beginners in data science get more experience and finally apply for job opportunities. 38. Scikit Learn 1.0: New Features in Python Machine Learning Library Scikit-learn is the most popular open-source and free python machine learning library for Data scientists and Machine learning practitioners. The scikit-learn library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction. 39. How to Build a Sentiment Analysis App Using Gradio and Hugging Face In this article, we are going to create an end-to-end AI Sentiment Analysis web application using Gradio and hugging face transformers. 40. Software Engineering Best Practices Collection for Machine Learning An ever-increasing number of organizations are developing applications that involve machine learning components. The complexity and diversity of these applications calls for software engineering techniques to ensure that they are built in a robust and future-proof manner. 41. Fine-Tuning Machine Learning Models with DVC Experiments for Transfer Learning You can work with pretrained models and fine-tune them with DVC experiments. 42. 70-Page Report on the COCO Dataset and Object Detection [Part 2] This blog is part 1 of (and contains a link to) a 70+ page report was created to quickly find data resources and/or assets for a given dataset and a specific ta 43. How Machines Learn Emotions: Sentiment Analysis of Amazon Product Reviews How do you train machines to identify emotions? This is a tutorial for sentiment analysis of Amazon product reviews using machine learning algorithms. 44. A Data Scientist's Guide to Semi-Supervised Learning Semi-supervised learning is the type of machine learning that is not commonly talked about by data science and machine learning practitioners but still has a very important role to play. 45. Improve Machine Learning Model Performance by Combining Categorical Features Learn how to combine categorical features in your dataset to improve your machine learning model performance. 46. 10 Best + Free Machine Learning Courses Collection Here's a compilation of some of the best + free machine learning courses available online. 47. How To Use Microsoft Excel To Classify Your Data An accessible introduction to ML - no programming or math required. By the end of this tutorial, you’ll have implemented your first algorithm without touching a single line of code. You’ll use Machine Learning techniques to classify real data using basic functions in Excel. You don’t have to be a genius or a programmer to understand machine learning. Despite the popularized applications of self-driving cars, killer robots, and facial recognition, the foundations of machine learning (ML) are quite simple. This is a chance to get your feet wet and understand the power of these new techniques. 48. Top 12 Javascript Libraries for Machine Learning Rapidly evolving technologies like Machine Learning, Artificial Intelligence, and Data Science were undoubtedly among the most booming technologies of this decade.  The s specifically focusses on Machine Learning which, in general, helped improve productivity across several sectors of the industry by more than 40%. It is a no-brainer that Machine Learning jobs are among the most sought-after jobs in the industry. 49. Encoding Categorical Data for ML Algorithms Encoding is a technique used to convert categorical data to numerical representations to be able to use the data in machine learning algorithms. 50. Scikit-Learn 0.24: Top 5 New Features For any data scientists & machine-learning engineers use scikit-learn for different machine learning projects here are  5 best new features in scikit-learn 0.24 51. The Hundred-Page Machine Learning Book [Review] I first ordered The Hundred-Page Machine Learning book back in May and am only just now finishing it up. In COVID-time, that was about 10 years ago. As you might have inferred, this book is NOT a quick read. What it lacks in easy reading, it makes up for in efficiency. This book swallows up the heavyweight mathematics textbooks and spits out a slim product no thicker than the width of my smartphone. From page one all the way to page 136, Andriy Burkov, the author, does not waste a single word in distilling the most practical concepts in machine learning. You read that right. It is MORE than 100 pages! Sounds like the book has some bias. Get it? Now get ready for my hundred-page book review. Just kidding. 52. Build A Commission-Free Algo Trading Bot By Machine Learning Quarterly Earnings Reports [Full Guide] Introduction 53. Top 20 ML Stories For Data Science Data Science is undoubtedly one of the main fields that every AI, ML, or data science enthusiast crosses paths with. Now with the advancement of data science, it is not just restricted to refine the data and then put it on the board. It is combined with Machine Learning that makes your machines smart by using the data that you just optimized to feed the machine. 54. How to Deploy Machine Learning Models to the Cloud Quickly and Easily Machine learning models are usually developed in a training environment (online or offline). And you can then deploy them and use them with live data. 55. Credit Card Fraud Detection via Machine Learning: A Case Study A machine learning guide on how to identify fraudulent credit card transactions by using the PyOD toolkit. 56. [Hacking Tinder] Train an AI to Auto-Swipe for You 🖖 Auto-tinder was created to train an AI using Tensorflow and Python3 that learns your interests in the other sex and automatically plays the tinder swiping-game for you. 57. Building Machine Learning Models With TensorFlow In this article, I will share with you some useful tips and guidelines that you can use to better build better deep learning models. 58. 70-Page Report on the COCO Dataset and Object Detection [Part 3] 59. [Explained] Machine Learning Fundamentals: Optimization Problems and How to Solve Them If you start to look into machine learning and the math behind it, you will quickly notice that everything comes down to an optimization problem. Even the training of neural networks is basically just finding the optimal parameter configuration for a really high dimensional function. 60. The Full Story behind Convolutional Neural Networks and the Math Behind it Convolutional Neural Networks became really popular after 2010 because they outperformed any other network architecture on visual data, but the concept behind CNN is not new. In fact, it is very much inspired by the human visual system. In this article, I aim to explain in very details how researchers came up with the idea of CNN, how they are structured, how the math behind them works and what techniques are applied to improve their performance. 61. How I built this: Machine learning with Amazon Personalize and a Customer Data Platform Learn how an infrastructural Customer Data Platform can help you overcome common machine learning challenges with this use case tutorial. 62. [Tutorial] Build a Gender Classifier for Live Webcam Stream using Tensorflow and OpenCV Training a Neural Network from scratch suffers two main problems. First, a very large, classified input dataset is needed so that the Neural Network can learn the different features it needs for the classification. 63. Intro to Audio Analysis: Recognizing Sounds Using Machine Learning 64. Loan Risk Prediction Using Neural Networks A Step-by-Step Guide (With a Healthy Dose of Data Cleaning) Thank you for checking out the 64 most read stories about Machine Learning Tutorials on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

64 Stories To Learn About Machine Learning Tutorials

The New York Times Company v. Microsoft Corporation Court Filing December 27, 2023 is part of . You can jump to any part in this filing . This is part 10 of 27. HackerNoon’s Legal PDF Series here IV. FACTUAL ALLEGATIONS C. Defendants’ Unauthorized Use and Copying of Times Content 82. Microsoft and OpenAI created and distributed reproductions of The Times’s content in several, independent ways in the course of training their LLMs and operating the products that incorporate them. 1. Unauthorized Reproduction of Times Works During GPT Model Training 83. Defendants’ GPT models are a family of LLMs, the first of which was introduced in 2018, followed by GPT-2 in 2019, GPT-3 in 2020, GPT-3.5 in 2022, and GPT-4 in 2023. The “chat” style LLMs, GPT-3.5 and GPT-4, were developed in two stages. First, a transformer model was pre-trained on a very large amount of data. Second, the model was “fine-tuned” on a much smaller supervised dataset in order to help the model solve specific tasks. 84. The pre-training step involved collecting and storing text content to create training datasets and processing that content through the GPT models. While OpenAI did not release the trained versions of GPT-2 onward, “[d]ue to [OpenAI’s] concerns about malicious applications of the technology,” OpenAI has published general information about its pre-training process for the GPT models.[12] 85. GPT-2 includes 1.5 billion parameters, which was a 10X scale up of GPT.[13] The training dataset for GPT-2 includes an internal corpus OpenAI built called “WebText,” which includes “the text contents of 45 million links posted by users of the ‘Reddit’ social network.”[14] The contents of the WebText dataset were created as a “new web scrape which emphasizes document quality.”[15] The WebText dataset contains a staggering amount of scraped content from The Times. For example, the NYTimes.com domain is one of the “top 15 domains by volume” in the WebText dataset,[16] and is listed as the 5th “top domain” in the WebText dataset with 333,160 entries.[17] 86. GPT-3 includes 175 billion parameters and was trained on the datasets listed in the table below.[18] 87. One of these datasets, WebText2, was created to prioritize high value content. Like the original WebText, it is composed of popular outbound links from Reddit. As shown in the table above, the WebText2 corpus was weighted 22% in the training mix for GPT-3 despite constituting less than 4% of the total tokens in the training mix. Times content—a total of 209,707 unique URLs—accounts for 1.23% of all sources listed in OpenWebText2, an open-source re-creation of the WebText2 dataset used in training GPT-3. Like the original WebText, OpenAI describes WebText2 as a “high-quality” dataset that is “an expanded version of the WebText dataset … collected by scraping links over a longer period of time.”[19] 88. The most highly weighted dataset in GPT-3, Common Crawl, is a “copy of the Internet” made available by an eponymous 501(c)(3) organization run by wealthy venture capital investors.[20] The domain www.nytimes.com is the most highly represented proprietary source (and the third overall behind only Wikipedia and a database of U.S. patent documents) represented in a filtered English-language subset of a 2019 snapshot of Common Crawl, accounting for 100 million tokens (basic units of text): [21] 89. The Common Crawl dataset includes at least 16 million unique records of content from The Times across News, Cooking, Wirecutter, and The Athletic, and more than 66 million total records of content from the Times. 90. Critically, OpenAI admits that “datasets we view as higher-quality are sampled more frequently” during training.[22] Accordingly, by OpenAI’s own admission, high-quality content, including content from The The Times, was more important and valuable for training the GPT models as compared to content taken from other, lower-quality sources. 91. While OpenAI has not released much information about GPT-4, experts suspect that GPT-4 includes 1.8 trillion parameters, which is over 10X larger than GPT-3, and was trained on approximately 13 trillion tokens.[23] The training set for GPT-3, GPT-3.5, and GPT-4 was comprised of 45 terabytes of data—the equivalent of a Microsoft Word document that is over 3.7 billion pages long. [24] Between the Common Crawl, WebText, and WebText2 datasets, the Defendants likely used millions of Times-owned works in full in order to train the GPT models. 92. Defendants repeatedly copied this mass of Times copyrighted content, without any license or other compensation to The Times. As part of training the GPT models, Microsoft and OpenAI collaborated to develop a complex, bespoke supercomputing system to house and reproduce copies of the training dataset, including copies of The Times-owned content. Millions of Times Works were copied and ingested—multiple times—for the purpose of “training” Defendants’ GPT models. 93. Upon information and belief, Microsoft and OpenAI acted jointly in the large-scale copying of The Times’s material involved in generating the GPT models programmed to accurately mimic The Times’s content and writers. Microsoft and OpenAI collaborated in designing the GPT models, selecting the training datasets, and supervising the training process. As Mr. Nadella stated: So, there are a lot of, I call it, product design choices one gets tomake when you think about AI and AI safety. Then, let’s come at itthe other way. You have to take real care of the pretrained data because models are trained on pretrained data. What’s the quality,the provenance of that pretrained data? That’s a place where we’vedone a lot of work.[25] 94. To the extent that Microsoft did not select the works used to train the GPT models, it acted in self-described “partnership” with OpenAI respecting that selection, knew or was willfully blind to the identity of the selected works by virtue of its knowledge of the nature and identity of the training corpuses and selection criteria employed by OpenAI, and/or had the right and ability to prevent OpenAI from using any particular work for training by virtue of its physical control of the supercomputer it developed for that purpose and its legal and financial influence over the OpenAI Defendants. 95. Upon information and belief, Microsoft and OpenAI continue to create unauthorized copies of Times Works in the form of synthetic search results returned by their Bing Chat and Browse with Bing products. Microsoft actively gathers copies of the Times Works used to generate such results in the process of crawling the web to create the index for its Bing search engine. 96. On information and belief, Microsoft and OpenAI are currently or will imminently commence making additional copies of Times Works to train and/or fine-tune the next-generation GPT-5 LLM. 97. Defendants’ large-scale commercial exploitation of Times content is not licensed, nor have Defendants received permission from The Times to copy and use its works to build their GenAI tools. Continue Reading . Here [12] OpenAI, Better Language Models and Their Implications, OPENAI (Feb. 14, 2019), https://openai.com/research/better-language-models. [13] Id. [14] GPT-2 Model Card, GITHUB (Nov. 2019), https://github.com/openai/gpt-2/blob/master/model_card.md. [15] RADFORD ET AL., LANGUAGE MODELS ARE UNSUPERVISED MULTITASK LEARNERS 3 (2018), https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf. [16] GPT-2 Model Card, supra note 14. [17] GPT-2 / domains.txt, GITHUB, https://github.com/openai/gpt-2/blob/master/domains.txt (last visited Dec. 21, 2023). [18] BROWN ET AL., LANGUAGE MODELS ARE FEW-SHOT LEARNERS 9 (2020), https://arxiv.org/pdf/2005.14165.pdf. [19] Id. at 8. [20] COMMON CRAWL, https://commoncrawl.org/ (last visited Dec. 21, 2023). [21] DODGE ET AL., DOCUMENTING LARGE WEBTEXT CORPORA: A CASE STUDY ON THE COLOSSAL CLEAN CRAWLED CORPUS (2021), https://arxiv.org/abs/2104.08758. [22] BROWN ET AL., supra note 18. [23] Maximilian Schreiner, GPT-4 Architecture, Datasets, Costs and More Leaked, THE DECODER (July 11, 2023), https://the-decoder.com/gpt-4-architecture-datasets-costs-and-more-leaked/. [24] Kindra Cooper, OpenAI GPT-3: Everything You Need to Know [Updated], SPRINGBOARD (Sept. 27, 2023), https://www.springboard.com/blog/data-science/machine-learning-gpt-3-open-ai/. [25] Nilay Patel, Microsoft Thinks AI Can Beat Google at Search — CEO Satya Nadella Explains Why, THE VERGE (Feb. 7, 2023), https://www.theverge.com/23589994/microsoft-ceo-satya-nadella-bing-chatgpt-googlesearch-ai. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 1:23-cv-11195 retrieved on December 29, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. nycto-assets.nytimes.com

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টাইমস বনাম মাইক্রোসফ্ট/ওপেনএআই: জিপিটি মডেল প্রশিক্ষণে টাইমসের অননুমোদিত পুনরুত্পাদন (10)

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द टाइम्स बनाम माइक्रोसॉफ्ट/ओपनएआई: जीपीटी मॉडल प्रशिक्षण में टाइम्स वर्क्स का अनधिकृत पुनरुत्पादन (10)

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The world of web development has been in a constant state of evolution, with new tools and approaches. It makes it easier for developers to create interactive and user-friendly applications. Among these tools, , a JavaScript library developed by , has emerged as a key player in the field. An intrinsic part of React’s growing popularity is the introduction of . Before Hooks, managing state and lifecycle events in functional components was a challenge. React Facebook Hooks Hooks revolutionized this by making it possible to use state and other React features without writing a class. This essay delves into the nuances of React Hooks, providing insights on different types of hooks including useState and useEffect, the concept of Custom Hooks and how they aid in reusing stateful logic between various components, and how testing paradigms change with the inclusion of Hooks. Understanding React Hooks Unpacking React Hooks: A Transition in State Management for Developers Introduced with the release of React 16.8, React Hooks has swiftly transformed the landscape of React development. Seemingly abstract and complex at first, React Hooks is truly an ingenious addition to a developer’s toolbox, pushing the envelope of functional components and elevating the state management game immeasurably. React Hooks, in essence, are functions that allow developers to ‘hook into’ React state and other lifecycle features straight from functional components. They abrogate the mandate of writing in classes, to access features like state or lifecycle methods. This gateway to clean and readable code is exceptional, hence the buzz that surrounds React Hooks. Before React Hooks, transitioning between functional and class components was a daunting task, eclipsing the read flow of the code and making the process cumbersome. The mounting complexity was a typical outcome during rewrites on the incorporation of lifecycle methods or states. React Hooks turns this around, making the journey from functional to class-based components smooth and efficient. Furthermore, React Hooks take a stride forward in demystifying the React component lifecycle. React Hook ‘useState’ transforms the way of defining a state variable. Gone are the days of ‘setState’ bound with the limitations of class components. It cleans up and simplifies the codebase by bundling up multiple state updates into one, facilitating better management. However, the praise doesn’t stop with ‘useState’. The ‘useEffect’ Hook is another prized possession of this library. It essentially amalgamates componentDidMount, componentDidUpdate, and componentWillUnmount, allowing side effects in the functional component. It navigates each peril in the lifecycle of a React component with rolled-up sleeves. The application of React Hooks goes beyond just state management. It encourages code reusability without prop drilling and complexity of render props or higher-order components (HOC). The ability to divide the component logic into smaller reusable functions is freeing for a developer. So, why should developers care? The answer lies in the sheer ability of React Hooks to simplify and streamline. They usher in cleaner code, smoother navigation, and an enhanced developer experience. Dealing with ‘this’ keyword or binding event handlers, typical of class components, are tasks of the past. Improved testing via breaking down of complex components into smaller, single-purpose functions is an undeniable advantage. To put it bluntly, React Hooks are not just another feature; they represent a paradigm shift in the React development journey. By embracing React Hooks, developers can allocate more focus on building the application logic rather than grappling with React’s complexities. The shift orchestrates efficient code organization, eases testing, and improves the overall application’s performance. While getting accustomed to React Hooks may entail a learning curve, the payoff in terms of cleaner, more efficient code is worth the time investment. For developers committed to staying on the cutting edge of technology, adopting React Hooks is not just a trend but a significant step in enhancing their coding prowess. This plunge into the world of React Hooks is the embodiment of technological advancement in programming – a resolution for better, not just an evolution. For developers eyeballing a sleek and efficient coding experience and top-of-the-line React applications, React Hooks are more than a game-changer – they’re a whole new ballgame. State Hook (useState) Diving deeper into the utilization of the Hook, developers across the globe continue to find innovative ways to manage their application’s state in an uncomplicated manner. While functional components initially lacked the state management abilities of their class component counterparts, the inception of with the introduction of Hooks has successfully leveled the playing field. useState useState The Hook allows developers to add state to functional components, granting them the power to react to user actions, network responses, and other events in a resource-efficient manner. The Hook returns a pair: the current state and a function capable of updating it. The initial state can be set similar to any providing ample flexibility for dynamic applications. This enhances the developer’s capability to manipulate application responses based on varied user inputs. useState JavaScript variable, If we dig deeper, a deeper understanding of why plays an integral part in React applications is necessary. To put it simply, without , any changes made to a component’s state wouldn’t render a re-update to the user interface. Thus, is integral to maintaining an interactive, application that accurately reflects state changes. useState useState useState responsive One particularly notable advantage of using is its heightened code readability compared to class components. Let’s face it; writing was never fun or straightforward. By employing , different states are defined with individual names, eliminating the need for complex objects and allowing for direct, unambiguous reference to each state variable. This simplification is not only easier on the beginner’s eyes but also aids seasoned developers in maintaining neat and organized code – a win-win for all. useState setState useState setState Another selling point of lies in its ability to set the state directly instead of merging new and old states like in class components, reducing the chances of bugs slipping through the cracks when your application gets complicated. This feature also parallels JavaScript’s standard behavior, providing a smoother learning curve for developers new to React. useState A useful trick employed by developers using is passing a function into the setter, bootstrapping lengthy computations. This avoids executing the initial state computation on every render but instead only when mounting, providing an edge in optimization and speed. useState A noteworthy detail while employing is understanding different state variables can trigger multiple re-renders. In complex applications, this can impact performance. Therefore, a judicious and precise use of is strongly recommended to retain the application’s performance efficiency. useState useState In conclusion, the Hook, part of the game-changing React Hooks, ups the ante for state management in functional components. It simplifies writing, understanding, testing, and debugging code, while also providing efficient optimization possibilities. With a clear approach and robust understanding of the hook, developers can enhance their React applications and step up their programming game. useState useState Despite React Hooks requiring a paradigm shift, the payoff is rewarding. This shift is not only changing the way developers approach their code but also shaping the future of programming at large. As an alluring technology, mastering React Hooks is a worthwhile venture for every earnest developer. Effect Hook (useEffect) Without a doubt, the rise of the Hook in React has been a significant boon in managing side effects within functional components. Unlike other methods, offers a more seamless way to control side effects, often perceived as one of the most challenging tasks in programming. This makes your components much cleaner and more efficient, leading to an overall improvement in your React applications. useEffect useEffect Cementing its position as a revolutionary tool, eliminates the need to separate same logic based on different lifecycle methods such as , , and . It allows for a comprehensive management of similar tasks in one place. Imagine the simplicity — no more jumping around the code to find related logic. All side-effects managed within a single . useEffect componentDidMount componentDidUpdate componentWillUnmount useEffect Interestingly, the Hook also offers conditional execution. This feature allows a developer to dictate when the effect should run, providing a higher degree of control. It may sound minor, but this flexibility saves computational power when deriving or manipulating data, ultimately enhancing app performance. useEffect The clean up function, an under-recognized feature of the Hook, is designed to clean up after an effect. It’s inbuilt, anticipating the necessity for unsubscriptions, clearing intervals or timeouts, removing event listeners, and other such actions that are paramount to preventing memory leaks. This forward-thinking functionality is another testament to how has revolutionized side-effect management. useEffect useEffect Supercharging functionality, the custom Hooks offer full leverage of and . Derived from these primitive Hooks, custom Hooks allow encapsulation of complex logic or side effects that can later be easily used or reused in different components. Styling your programming approach with the unique features of creates a springboard for efficient code execution and codebase organization. useState useEffect useEffect In a nutshell, the adoption of and React Hooks in general, marks a defining moment in a programmer’s journey. They offer an organized, efficient, and performant method of managing side effects in functional components. The clean, concise, and intuitive interface of these tools can dramatically accelerate the development efficiency of applications. The shift towards these Hooks symbolizes not only the ongoing advances in programming techniques, but the relentless pursuit of simplicity in complexity– truly a revolution in the making. useEffect Remember, technology evolves at a breathtaking pace, and keeping abreast of new trends like React Hooks is crucial for software developers. The Hook is more than just a new tool to add to your developer toolkit – it’s an innovation that is helping to redefine effective coding. The future of software development is here, and it hinges, in part, on mastery of tools like the Hook. This isn’t just another tech hype, but a significant stride in the world of programming that demands attention. useEffect useEffect Custom Hooks In the whirlwind of innovation that is React, Hooks have without a doubt made a splash. Now, let’s dive into the deep end – the world of Custom Hooks. There’s more to this wonder than meets the eye, so fasten your seatbelts, tech enthusiasts, because we’ll creatively demonstrate how to write reusable stateful logic with Custom Hooks. Exploring Custom Hooks After studying the useState and useEffect hooks, it’s only logical to introduce Custom Hooks. They are, contrary to popular belief, not a feature of React. Instead, they are born from the core React minds by combining useState, useEffect, and other built-in hooks. Think of them as JavaScript functions with a twist—they can utilize React Hooks. Custom Hooks tying together several different hooks allows developers to abstract component logic. This makes for highly reusable pieces of stateful logic, transforming how React apps are crafted. Writing Custom Hooks Writing a Custom Hook is zero complexity. Name-wise, Custom Hooks must start with ‘use’ so they’re not confused with regular JavaScript functions. Our journey unravels as we create a Custom Hook that fetches data from an API—something that could be reused across applications. The ‘useApiData’ hook handles the fetching and returns the response, error, and a ‘isLoading’ flag. Custom Hooks Iterate the Game React’s introduction of Hooks is a leap forward that has reset the immersion bar. Custom Hooks take this to a further dimension, allowing developers to craft their toolset—tools that best fit the problem at hand. This idea of reusability in programming may not be new, but Custom Hooks’ way of handling it gives it a fresh spin. Widely performing functions can now be abstracted into a Single Custom Hook, thereby decreasing duplication. Furthermore, they bring better abstraction, easier testing, and increased readability and maintainability. They are truly a profound step forward in not only the React world but also the broader realm of technology. In Conclusion Custom Hooks, without an iota of doubt, are a game changer in writing reusable stateful logic. Their tangible benefits have reverberated through the developer community—clean code, improved reusability, better abstraction, and above all, the ability to create a personal toolbox that aids in handling repetitive tasks more efficiently. In this ever-evolving tech era, staying updated and grasping new trends are vital. Mastering Custom Hooks provides developers a stint to be ahead of the curve. Moreover, they stand as the testament of advancement, simplification, and efficiency in programming. Recipe for the future? It seems like it’s ‘Hooked’ on someone! Testing with Hooks Harnessing the Power of Testing Components Using Hooks in React For React developers keen on elevating their programming skills to higher levels, diving into a thorough testing process using Hooks is indispensable. But it necessitates understanding more than just the basic use of useState, useEffect, and even custom Hooks — we’re looking into a meticulously planned out process to guarantee valid, reliable results. Implementing Testing Strategy with Hooks React Hook’s implementation in a testing strategy revolutionizes the testing process. This powerful feature offers a fresh perspective to lessen the burden of testing React components. Given the inherent complexity of testing, using Hooks often results in a streamlined and effective testing process. No process is complete without proper planning. A planned testing strategy involves breaking down the components into individual units. Once accomplished, developers can focus on testing each Hook on an individual component level, ensuring all functionalities perform as expected without unforeseen side effects. The use of comprehensive tools like Jest and React Testing Library can expedite the testing of components with Hooks. Jest, a JavaScript testing framework, is widely preferred because of its powerful mocking capabilities, whereas the React Testing Library is specifically designed to test React components. Testing of useState Hooks Testing useState Hooks can be tricky, especially when there are asynchronous state updates. React’s act() function ensures that all updates related to these events have been processed and applied to the DOM before making any assertions about the result. This effectively enables developers to test components with useState Hooks with high reliability. Testing of useEffect Hooks For testing components with useEffect Hooks, developers should keep in mind that it may run after every render, which could potentially damage test isolation. To mitigate these potential issues, asynchronous behavior is recommended when testing this Hook. Mocking is also an effective method to isolate and test certain behaviors of useEffect Hooks, ensuring that side effects do not interfere with the overall testing process. Testing of Custom Hooks Testing custom Hooks, on the one hand, may require a different approach. Due to the complexity they can introduce, they need to be tested meticulously. The React Testing Library again plays a significant role here, providing the custom renderHook function. It allows developers to isolate and test custom Hook functionality separately from the component. Benefits of Testing with Hooks Testing with Hooks not only improves code coverage, but it also streamlines the overall testing process by simplifying the handling of state and lifecycle methods within functional components. It aids developers in creating more maintainable and readable code, greatly improving their control over component behavior. Beyond testing, the idiomatic patterns embodied within Hooks elevate code quality to maximize performance and user experience while fostering code reusability. Ultimately, developers can enjoy enhanced testability of their applications with confidence about their application’s reliability and maintainability. Embrace the Future, Master Hooks In the rapidly changing world of technology, mastering Hooks have become crucial for every developer keen on riding the wave. Joining the Hooks bandwagon might have seemed just a trend at first, but given its widespread use and constant evolution, it’s now more of a necessity. In conclusion, using Hooks for testing provides compelling advantages that positively impact the development and testing processes, taking them to the next level. By mastering the art of testing with Hooks, developers can confidently create high-quality, reliable React applications. Photo by on thomastastet Unsplash The functionality and power offered by React Hooks truly mark a significant advancement in web development. They provide a much sought-after flexibility that React developers had been seeking in managing state and side-effects in functional components. Furthermore, the concept of Custom Hooks opens the door for improved code organization, promoting logic reuse, and ultimately enhancing code maintainability. To cap it all, although testing components using Hooks introduces some unique challenges, adept knowledge of these Hooks and effective strategies can empower developers to accurately test their applications. React Hooks, with their profound impacts, have undoubtedly made the functional programming in React more efficient and nuanced. Also published here.

How React Hooks Revolutionize Functional Components

First published in 1991, by , outlines the harrowing journey of taking a technology product from early adoption to mainstream success. Crossing the Chasm Marketing and Selling High-Tech Products to Mainstream Customers Dr Geoffrey A. Moore It remains exceedingly relevant for B2B startups, even in our current hyper-accelerated technological landscape. Below are five lessons from this iconic treatise that I believe every B2B startup should scrutinize anew. The Chasm is Not a Metaphor; It’s a Graveyard If you think the chasm is an overblown metaphor, you’re deluding yourself. This is where startups go to die, and it’s astonishing how many promising B2B startups fall into oblivion here. The chasm occurs post-innovators and early adopters, right before the early majority stage in the technology adoption lifecycle. It’s a trap because product/market fit among early adopters is not automatically replicable for the broader market. Early adopters are forgiving. They can see the future and are willing to deal with incomplete or buggy products because they see the potential. The early majority does not share this magnanimity. They want solutions, not potential. They require robustness, full-feature sets, and most importantly, minimal adoption risk. This is why you should never mistake initial success with early adopters as a sign that you’ve made it. You need a separate, dedicated strategy to cross the chasm, focusing on a singular compelling reason for mainstream customers to adopt your product. Establishing this will give you the focal point around which you can evolve and refine your offering, thus enabling you to satisfy the stringent demands of the early majority. Whole Product Concept: No Product is an Island Every B2B entrepreneur needs to understand that no product exists in isolation. Early adopters might be willing to piece together the ‘whole product’ by integrating your solution with other services, but the mainstream market won’t. They want a complete, end-to-end solution that solves their problem out-of-the-box. The Whole Product Concept is not just the generic product you've made; it’s the complete package required to achieve the desired result. It includes customer support, complementary products, system integration, and even the know-how to use it effectively. By fulfilling the whole product, you don't just sell a product; you sell a promise of a solved problem. The best way to tackle this is through strategic partnerships, API integrations, and robust customer support systems, thereby creating an ecosystem around your product. You have to make the customer feel that everything has been thought of, leaving no rough edges or unanswered questions. Niche Marketing is Not a Luxury; It’s a Necessity The chasm-crossing strategy that most resonates with B2B startups is the "bowling pin" strategy. The principle here is to first dominate a niche market and then use that as a springboard to enter adjacent markets. This is antithetical to the 'big bang' approach that tries to capture as much market share as possible, as quickly as possible. Instead, focus on a narrow target where you can become the indisputable leader. This is crucial for two reasons: First, becoming a leader in a niche market allows you to make mistakes and learn without fatal consequences. Second, it creates referenceable clients that serve as social proof when you enter adjacent markets. Your reputation precedes you, and the next market is more likely to trust you because you've already proven yourself elsewhere. The Sales Process: High Touch Over High Tech Many B2B startups invest in highly scalable, low-touch sales processes. While this works for early adopters, crossing the chasm demands a high-touch approach. The mainstream market doesn’t want to self-serve; they want to be guided. Here, a charismatic sales team that can hand-hold potential clients becomes invaluable. These are not just salespeople; they are consultants who understand the client’s domain, needs, and apprehensions. The consultative sales approach works because you're no longer selling a product; you're selling a vision of how their business will look after implementing your solution. You must train your sales team to articulate this vision convincingly, providing prospects with a tangible roadmap of how you'll solve their issues and bring value. Crossing the Chasm is an Ongoing Process Crossing the chasm is not a one-time event; it’s a constant process. The moment you think you’ve crossed it, there's another one staring you in the face as market dynamics change, competitors emerge, or technologies evolve. The chasm keeps reappearing, and your strategies must evolve with it. The success factors that helped you cross the first chasm may not work for the second or third. Thus, you need to maintain a culture of constant learning and adaptation. Conclusion This book represents an adaptation of the innovation adoption model known as the " " theory, originally formulated by the eminent scholar, . Geoffrey Moore’s Crossing the Chasm should not be a book that you read once and put back on the shelf. It should be a manual that you consult regularly, making necessary adjustments to your strategy as you move forward. Diffusion of Innovations Everett Rogers While the tech landscape has evolved dramatically since the book was first published, the core principles remain as valid as ever for B2B startups looking to make a lasting impact.

5 Lessons From Crossing The Chasm That Every B2B Startup Needs to Revisit

প্রতিটি B2B স্টার্টআপকে পুনরায় দেখার প্রয়োজন যে খাদ অতিক্রম করা থেকে 5টি পাঠ

5 Lehren aus der Überwindung der Kluft, die jedes B2B-Startup noch einmal überdenken muss

5 lecciones aprendidas de cruzar el abismo que toda startup B2B debe revisar

5 leçons tirées du franchissement du gouffre que chaque startup B2B doit revisiter

खाई को पार करने के 5 सबक जिन पर हर बी2बी स्टार्टअप को दोबारा विचार करने की जरूरत है

すべての B2B スタートアップが再検討する必要があるキャズムを越えることから得た 5 つの教訓

모든 B2B 스타트업이 재검토해야 하는 캐즘 건너기에서 얻을 수 있는 5가지 교훈

5 lições de como cruzar o abismo que toda startup B2B precisa revisitar

5 уроков преодоления пропасти, к которым должен вернуться каждый B2B-стартап

Her B2B Startup'ın Yeniden Ziyaret Etmesi Gereken Uçurumu Aşmaya İlişkin 5 Ders

5 bài học từ việc vượt qua vực thẳm mà mọi công ty khởi nghiệp B2B cần xem lại

每个 B2B 初创公司都需要重新审视跨越鸿沟的 5 个教训

Let's learn about via these 38 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Food /Learn Repo 1. Why We Should All Pay Attention To Recent Food Tech Innovations There is a lot of food tech innovations out there that have been popping up over the past few years. And food tech has become a fairly popular industry to be in 2. 7 Companies with Recipe APIs in 2022 An overview of 7 Companies with recipe APIs in 2022 3. Startup Interview: "Not as many people genuinely care about food security as they should" Grow fast and fix things: if you aren’t fixing things, you are not growing fast enough. Look where "move fast and break things" has gotten us. 4. What's Inside Junk Food? Remember how your mom told you to finish your food before getting dessert? It turns out your mom was right! 5. On Food Waste and Relevance of Privacy: Noonies Nominee Paran Sonthalia Noonies 2021 nominee, Paran Sonthalia, is still a Berkley student. But that didn't stop him on the mission of reducing food waste. Hear more from him here. 6. The Ultimate Hamburger Grilling Guide What if I ask you what you want to have right now? If I were you, I would surely say hamburger. Nothing is better than a juicy, cheesy, perfectly grilled hamburger. However, not everyone can make a perfectly grilled hamburger. You need to nail every step and cook the meat at the right temperature to make a perfect hamburger. This article is the ultimate hamburger grilling guide with step by step process to make the perfect hamburger. 7. Food Tech Stories: How These Guys Built A Multi-Billion Dollar Family Business Who doesn’t know Panda Express? It is a fast-food restaurant chain that offers American Chinese cuisine. With over 2,200 locations, it is a forward-runner in the Asian restaurant chain niche. The idea of Panda Express was born in the United States. First restaurants used to be located in shopping mall food courts, but the chain has been expanded since then. You can see Panda Express in universities, airports, military bases, amusement parks, and other places. 8. What’s the Healthiest Way to Lose Weight We would all like to lose body fat rapidly. However, not only is that nearly impossible (get real), but it’s also incredibly unhealthy. According to the people who lose weight gradually (one-to-two pounds per week) are more successful in keeping the weight off. 9. Reconstructing Our Food Supply Chains with Blockchain Technology Blockchain technology can streamline and restructure the way that we interpret global supply lines, a change that may be vital for addressing climate change. 10. How Blockchain can Disrupt the Restaurant Industry This article talks about blockchain and restaurant tech to disrupt and uplift the restaurant industry after COVID-19. 11. How AI is Transforming the Grab&Go Food Market 12. Brainpower And Brainberries: 7 Food Ideas to Hack your Brain Are you a programmer who wants to know what are the best food that would best fit your lifestyle? Developers and programmers can have very demanding jobs. They stay up for long hours and require a lot of brainpower in order to get their work done and meet their deadlines. 13. Diving into the Legal Issues of NFTs in FoodTech The implementation of NFT leads not only to the improvement of operations and brand image but also causes some legal issues which are worth knowing about. 14. How Social Media Can Help You Eat Healthily Just about everyone who has tried to make radically healthier changes to their daily food consumption have realized that this is easier to accomplish with some kind of support system aside from your own will to succeed. It is a great help for people to cheer you on, support you, give you advice, or even criticize you on your way to better eating and overall health. 15. 5 Important Things We've Learned from Nonprofits Working in Food Security Here are 5 useful takeaways we've learned from nonprofits working in food security. 16. Food Tech Stories: Food On Wheels Can Solve Last Mile Problem Urbanization is a common process in many regions of the world, including a huge proportion of people in less developed countries. Rapid urbanization can cause many problems, including poverty and food insecurity, which can make it harder for citizens to eat a healthy diet. No matter how hard policymakers are trying to promote healthy and sustainable diets, it’s still an acute problem in modern cities. 17. Emerging Food Technology Trends & Insights for 2022 The food industry is one industry that benefits from the use of technology, from data gathering, food quality, blockchain tech and supply chain tracking. 18. What These 4 Charities Are Doing to Fight Hunger Doing the Pandemic We spoke to four food security organizations in Colombia, Portugal, South Africa, and the United States to better understand the challenges facing organizations 19. Here's Why 70% of Americans Are Overweight or Obese Sollozzo goes over why 70% of Americans are overweight. 20. Food Tech Stories: How Sugarmate Helps People With Diabetes Today, most people with diabetes opt to deal with their condition with the help of a continuous glucose monitor or CGMs. Since finger prick testing is not really convenient, CGMs are a great option. And they give a surge of information nonstop as well. However, most data is useless unless the right tools are used to analyze it. 21. Bolstering Food Integrity With Blockchain How Blockchain Could Enhance Our Food Integrity? 22. Traditional Ukrainian Food: Beginners Guide Ukrainian's love to eat. As a result, there is a variety of dishes to choose from. Light flavours and heavenly taste is what describes Ukrainian food the best. However they're not easy to prepare. You cannot prepare Ukrainian food as taco in seven minutes. It takes time, and it's totally worth it. Traditional Ukrainian food consists of a lot of ingredients like meat, vegetables, seasonings, some herbs, etc. There is a diversity of ingredients and that is what brings out the unique taste it has. 23. Healthy Eating Under Coronavirus Quarantine Eating out has become a big part of our lives and with everyone now at home, a lot needs to change to make up for it. Before this lockdown, Americans would eat out on average nearly 6 times per week. Eating at home is still popular - Americans spend around $4,400 annually on food for their fridge; around 7% of their total annual spending. In these past few weeks, however, going to grocery stores has been discouraged and most restaurants have been closed. This has caused many to stock up on a variety of items. Shoppers are stocking up on goods like canned foods, hand sanitizer, toilet paper, and bottled water. Sales for some of these items such as oat milk and medical masks are up by hundreds of percent and other products like frozen and fresh fruit, dried beans, bath and shower wipes, and water all have higher sales that are higher by a noticeable amount. 24. Food Tech Stories: The Secret Of The Sustainable Food System The EAT-Lancet report is the primary full logical report of what comprises a sound eating regimen from a sustainable food system, and which activities can support and accelerate food framework change. 25. Top 10 App Ideas for Restaurant and Food Business Startups in 2022 This post will provide you with the best app ideas for restaurant and food business startups to use as a springboard 26. The Future of Protein Have you ever tasted a veggie burger? Are you a vegan? You have a vegan friend, should you turn vegan? Did you ever thought about stop eating meat? Are you aware of animal slaughtering? 27. 7 Shopify Alternatives to Create an Online Food Delivery Platform Top Shopify alternatives restaurateurs must consider to develop their online food delivery platform. 28. The Dark Side of Food Delivery: Inside Uber Eats, Zomato, and Deliveroo In this thread, the slogging community discusses their thoughts on food delivery services, their impact on the food industry, and the main perks and drawbacks. 29. What is the Best Pizza Topping? (Slogging Insights) In this slogging thread, the team at Hackernoon discusses the best pizza topping. The debate gets heated with the Hackernoon team heavily divided on the best. 30. What is the Best Brunch? In this Slogging thread, the team at Hackernoon, discusses, what the best brunch is. We also talk about why Gordon Ramsay is heavily overrated. 31. Mental Health Awareness Month: How to Maintain Good Mental Health During the COVID-19 Pandemic Stress, anxiety, and fear are normal responses to actual or perceived threats, especially when confronted with uncertain situations. As a result of the COVID-19 pandemic, people are experiencing heightened levels of stress and anxiety. 32. Oxidative Priority: Understanding the Science Behind Fat Loss This time I want to introduce one rule. The one that is underneath most diets. It is the Oxidative Priority, and how this is related to fat loss. 33. Should We Gene-Edit Our Fruits and Vegetables? In this slogging thread, our community discussed the benefits of gene editing, and how it is different from GMOs. 34. The Whole Shebang of McDonald’s Business Model and Branding Strategies Let’s unravel McDonald’s Business Model and Branding Strategies. Read what makes the world's largest restaurant chain by revenue profitable & recession proof. 35. The Food Truck: An Old Business Idea Worth Exploring? Food trucks have been around for quite some time now, an idea sprung forth from an older necessity-driven idea, the chuckwagon. It is a simple proposition, really: instead of the public going to a restaurant or diner to eat, the food comes to them. One could consider it the older cousin of straight-to-your-door food delivery. 36. How Come Junk Food is Still An Epidemic? First part of this article: https://hackernoon.com/junk-food-whats-inside-it-107ar30zv 37. Are Insects The Future of Food? In this slogging thread, our random channel community discusses Japan's vending machines' new snack: insects! 38. 20 Mouthwatering WordPress Restaurant Themes to Make You and Your Business Salivate If you want to make your online restaurant modern and functional, you should choose a professionally advanced WordPress theme that comes with all essentials. Thank you for checking out the 38 most read stories about Food on HackerNoon. to find the most read stories about any technology. 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Hi All! Here is my weekly email discussing mental models, performance, business, and entrepreneurship. We’re often told to embrace togetherness, to seek connection in our daily interactions, but what if I told you that keeping our distance is sometimes the real key to a harmonious society? In this unconventional journey, we are going to delve deep into a philosophy that might just change the way you perceive human interactions forever. It All Started With Schopenhauer & Freud The roots of the Hedgehog's Dilemma are buried deep in the soils of intellectual thought, sprouting first from the mind of and later cultivated by . Arthur Schopenhauer Sigmund Freud Before we jump in, imagine a cold winter's day - a group of hedgehogs huddling together for warmth, but forced to remain apart to avoid hurting each other with their sharp spines. This imagery, both vivid and somewhat contrary to our everyday narratives about relationships and intimacy, forms the crux of the Hedgehog's Dilemma. Like hedgehogs seeking warmth but using their spines to maintain distance, individuals strive to foster close relationships while still preserving their autonomy. Schopenhauer, a powerhouse of philosophical thought, first introduced this analogy to illustrate the balance between intimacy and self-preservation, a dance of coming close for warmth and retreating to avoid the pricks of too close an encounter. , later adopted this paradoxical thinking, utilizing it as a springboard to explore the intricate nuances of human relationships and individual psychology. Freud, the father of psychoanalysis The Hedgehog's Dilemma Now, I’m sure dropping Schopenhauer and Freud is taking some of you back to college, but hear me out for a second. Surprisingly enough (not surprising), these two powerhouses of thought were onto something… that seems to have been forgotten. So let’s do this, I want to break it down a little bit more. Show you how this plays out in real life and then we’ll discuss how to leverage this mental model to help better optimize and understand your own relationships. Remember, the Hedgehog's Dilemma is a mental model. A framework to help you better understand why you do what you do. It will not change anything overnight, but it will give you clarity on why certain relationships feel the way they do, and why you may feel compelled to pull away when trying to get close to someone. Use it as a lens to examine your behaviors and tendencies, not as an excuse. With understanding comes the power to make different choices. I want you to do this. Picture yourself as one of those hedgehogs. You have an intrinsic need for warmth, for connection, but at the same time, you harbor a natural, self-protective instinct. This is the essence of the Hedgehog's Dilemma: a narrative that teaches us the importance of finding our in relationships, a distance that respects individual boundaries while fostering connections. comfortable distance By internalizing this concept, we can start to view human relationships through a lens that honors both individuality and community, that recognizes the need for self-preservation alongside the pursuit of connection. This isn't just about hedgehogs (obviously); it's about us, navigating the complex terrains of modern relationships, armed with insights that encourage balanced, harmonious connections. Let’s dive into this little bit of very useful (but IMO, mostly forgotten) wisdom. Why Do We Love/Hate Other People? When you really boil it down, the push and pull of the Hedgehog's Dilemma comes from two core human needs that are always in tension - our drive to connect vs. our need to stand apart. Our deep desire for close relationships evolved because bonding and teamwork helped humans survive back in the day. But we also needed to act independently at times, so self-preservation got wired in too. . This tension got baked into our brains Too much intimacy can feel rewarding but also anxiety-provoking when we feel like we're losing our identity. Isolation leaves us feeling free but also lonely and rudderless without social bonds to anchor us. Our brains light up when we bond, releasing feel-good chemicals like oxytocin that bring comfort and safety. But rejection activates pain centers since we're wired to need social connections. At the same time, autonomy fires up our dopamine and ego, which provide a sense of personal power and coherence. So the Hedgehog's Dilemma perfectly captures this tug-of-war written into our social wiring - the need to come together versus remain apart, stay connected versus assert independence. We're always trying to strike that balance as we move through different types of relationships and phases of life. The Hedgehog Dilemma in Modern Life Now let’s fast forward and look at how to apply the Hedgehog’s Dilemma to balance intimacy and autonomy in key relationships today. Friendships Friendships require nurturing bonding experiences together, yet research shows too much closeness can breed resentment. Friends who spent every free minute together experienced greater conflict. Scheduling regular one-on-one time is important, but so is respecting each other’s need for space. Studies show time apart makes friends appreciate each other more. Actionable Tips: Plan shared activities 2-3 times per month. Researchers propose this optimal balance. Take turns picking activities you each enjoy. This ensures equity in your friendship. Discuss ideal communication cadence. Overtexting can feel intrusive, so align on expectations. Romantic Partnerships Romantic relationships involve intricate dances between affection and autonomy. John Gottman’s research reveals satisfied couples build intimacy yet retain a sense of separateness. Taking a couples’ attachment style quiz can provide insight into innate needs for closeness vs. independence. Actionable Tips: Agree on regular “me time” for independent activities. Couples who spend adequate alone time report higher relationship satisfaction. Schedule weekly date nights to nurture your bond. Studies show consistent date nights correlate to greater happiness. Initiate regular check-ins on changing needs for space vs. connection. This proactive communication prevents conflicts. Family Relationships Families require balancing unconditional love with respect for personal boundaries as children grow. Research by child psychologist Dr. Gordon Neufeld highlights the importance of honoring the separateness of family members. Actionable Tips: Maintain family traditions, but allow flexibility. Adapting traditions to members’ changing needs shows respect, but are very important for relationships and health. Discuss needs openly. Families thrive when members articulate shifting needs for closeness/space. Offer unconditional support for independent pursuits like hobbies or travels. This conveys your bond persists despite physical distance. Professional Relationships Even workplace relationships demand an equilibrium between collegiality and productivity. Leaders seen as too personal are considered less professional. But leaders that are not personal at all, are less trusted. Actionable Tips: Set boundaries but find common ground. Leaders who share some personal details are considered more trustworthy. Limit social time that impedes work. Workers who socialize a few times per month are most productive. Show empathy, but don’t become a therapist. Listen to struggles, but re-direct to HR if severe. What The Dilemma Means For You : In the pursuit of authentic relationships, encourage deep self-inquiry to understand your core values and expectations. This foundational work aids in building connections that are truly harmonious, avoiding the mirage of superficial compatibility. Distill Personal Truths : Cultivate the ability to maintain a dual focus - preserving your individuality while nurturing the relationship. This involves a continuous process of balancing personal growth with the nurturing of relationships, creating a space of mutual respect and development. Adopt a Dual Focus Strategy : Develop a communication blueprint that clearly outlines the modes and frequencies of communication that foster healthy relationships. This strategy prevents misunderstandings and fosters a space of open dialogue and understanding. Craft a Communication Blueprint : Incorporate regular emotional audits within your relationships, where you take time to assess the emotional health of the relationship, identify areas of improvement, and work together to foster greater harmony and understanding. Engage in Regular Emotional Audits : Build a trust framework within your relationships that clearly outlines the actions and behaviors that foster trust. This guideline serves as a roadmap for building and maintaining trust, and preventing betrayals and misunderstandings. Develop a Trust Framework : Embrace collaborative problem-solving strategies that encourage diverse perspectives and innovative solutions. This approach not only fosters a sense of collaboration but also nurtures a culture of respect and mutual growth. Implement Collaborative Problem-Solving : In professional settings, advocate for the creation of environments that foster psychological safety, encouraging individuals to share their insights and ideas without fear of retribution, and fostering innovation and collaboration. Foster a Culture of Psychological Safety : Develop strategies for establishing and maintaining personal and professional boundaries. This involves crafting clear guidelines on the limits of your availability and engagement and fostering relationships that respect individual space and autonomy. Strategic Boundary Management It's about using the wisdom in the Hedgehog's Dilemma to build connections that are not just strong and fulfilling, but also resilient to the fast-paced changes around us. It's about making smart moves in relationships, being more in tune with yourself and others, and ultimately creating bonds that stand the test of time. If you enjoyed this article, I’d love to hear from you. Also published . here Write me at or at me and I’ll do my best to get back to everyone! scott@scottdclary.com tweet @ScottDClary

Lessons on Human Connection from the Hedgehog's Dilemma 

হেজহগের দ্বিধা থেকে মানব সংযোগের পাঠ

Lehren zur menschlichen Verbindung aus dem Igel-Dilemma

고슴도치의 딜레마에서 배우는 인간관계에 대한 교훈

Уроки человеческих связей из «Дилеммы ежа»

Kirpi İkileminden İnsan Bağlantısı Üzerine Dersler

We’re starting a new fascinating series about the history of large language models (LLMs). Why should I know about it? “To fundamentally push the deep learning research frontier forward, one needs to thoroughly understand what has been attempted in the history and why current models exist in present forms” Haohan Wang and Bhiksha Raj from On the Origin of Deep Learning Large Language Models (LLMs) have a fascinating history that dates back to the early 1930s when the first ideas of computational linguistics were born. You may argue that this tracing is excessive and that LLMs have nothing in common with the old-fashioned prehistoric computer systems. You may also argue that LLMs are based on real, hard-core deep learning. However, deep learning itself originated in 1943, when the first ancestor of the artificial neural model was proposed by McCulloch and Pitts. Exactly 60 years ago! What took us so long to get to modern LLMs? This series isn't about drowning you in technical details. While we provide an extensive list of references for those who want to delve deeper, our main goal is to captivate your attention and share the influential developments that have shaped LLMs. Consider it a springboard for further exploration, a chance to find something in history that can inspire you for a new ML discovery. It's an invitation to immerse yourself in the story of LLMs, which made such a splash last year. In this episode, we'll take you on a time-travel adventure from 1933 to 1966. Ready? Let’s dive into The Era of Mechanical Translation and How It Crashed! The first steps in the US, USSR, and UK The concept of , but it wasn't that engineers and mathematicians began to develop the first concrete ideas about how to make it a reality. mechanical translation (MT) has always been a distant dream that tickled the imagination of many inventors until the early 20th century In 1933, significant progress was made when two individuals, , a French-Armenian, and , a Russian, independently patented their ideas for mechanical translation systems. George Artsrouni Petr Smirnov-Troyanskii 1933 – George Artsrouni and Petr Smirnov-Troyanskii independently secure patents detailing the first proposals of systems for mechanical translations. George Artsrouni designed a storage device on paper tape which could be used to find the equivalent of any word in another language. Troyanskii proposed a three-stage approach, where humans would handle the initial and final stages of translation, with the machine serving as an intermediary. Troyanskii firmly believed that in the future, the entire translation process could be fully mechanized. 1937 – Artsrouni demonstrates his first prototype Troyanskii's ideas hold greater significance compared to those of Artsrouni, yet their impact remained largely confined within the borders of the USSR. The lack of international awareness about Troyanskii's work limited the broader recognition and influence his ideas could have had on a global scale. . By that time, the progress made in the field of mechanical translation was limited to the development of a program capable of performing dictionary-based lookup operations, emulating the tasks performed by human translators. It wasn't until 1947 that some occasional conversations started to happen about mechanical translation in the United States 1947 – First discussions of MT in the US Challenged by limited resources and a lack of formal support, . and could devote only their spare time from their normal university duties to this unexplored domain. At odd moments, they collaborated on creating a detailed description of a dictionary that could potentially be used in conjunction with computing machines. the United Kingdom faced difficulties in establishing itself in the field of mechanical translation Andrew Booth Richard Hook Richens 1947 – The start of Booth and Richens's collaboration on the dictionary The same year, in 1947, , having been exposed to computer design problems during the war and understanding the capabilities of modern electronic computers, envisioned the possibility of using computers for translation. He wrote to famous professor Norbert Wiener of MIT, expressing the idea of ( . He even speculated that the problem of translation could be approached as a cryptographic problem. Warren Weaver designing a computer for translation to address the significant communication challenges between people “for the constructive and peaceful future of the planet”) However, , in his response, . Despite Weaver’s attempt to persuade Wiener by suggesting that a computer could handle the vocabulary and combinations of words, the discussion did not lead to any concrete progress in the field of translation at that time. Professor Wiener expressed skepticism about the feasibility of mechanical translation due to the vague boundaries of words in different languages and the extensive emotional and international connotations attached to them . This event inspired a wave of research at the University of Washington, the University of California at Los Angeles, and the Massachusetts Institute of Technology. But in 1949, Warren Weaver went ahead and published “Translation,” a that brought the concept of mechanical translation to global attention memorandum 1949 – Warren Weaver presents his memorandum about Translation In terms of machinery, the first notable advancement took place in 1950. , in collaboration with International Business Machines (IBM), initiated the , giving birth to the Georgetown Machine – the world's first mechanical translation marvel. It symbolized a promising glimpse into a future where words could effortlessly cross language barriers. The events start to unfold much faster for MT from this moment. Leon Dostert Georgetown-IBM Experiment 1950 – The invention of the Georgetown Machine, the first machine for mechanical translation Around the same time, was appointed as the first full-time machine translation (MT) researcher at MIT. He became the one to organize focused entirely on machine translation, for which he published a of the present state of research on mechanical translation. This and the next year This placed the basis and defined the main directions of MT research for the following years. Yehoshua Bar-Hillel the 1st International conference 10-page overview IBM - MIT Memory Conference emphasized two essential needs: long-term basic research and the demonstration of MT in action. 1951 – Yehoshua Bar-Hillel is appointed as the first full-time researcher in the MT 1952 – The 1st International Conference on MT at MIT 1953 - IBM - MIT Memory Conference MT in action! Full action on MT was happening in the Soviet Union. By the spring of 1951, nearly fifty engineers had been working on the machine, and by the autumn of 1952, the : the First Computer of the S.A. Lebedev Institute of Precise Mechanics and Computer Engineering was in operation. At this moment, it was one of Europe's fastest electronic computers. It also was used as a prototype of the first Chinese computer built with the help of Soviet engineers. BESM-1 https://www.youtube.com/watch?v=U4i6al2TBIY&embedable=true BESM-1 had 1024 words of read–write memory and 1024 words of read-only memory. It also had external storage: four magnetic tape units of 30,000 words each and fast magnetic drum storage with a capacity of 5120 words and an access rate of 800 words/second. An incredible capability for that time! 1952 – USSR completes the creation of BESM-1 Four years after its invention, in 1954, the Georgetown Machine took center stage with a , showcasing its capabilities. A thoughtfully curated set of 49 Russian sentences was translated into English. Notably, this translation was accomplished using a highly limited vocabulary of only 250 words and a mere six grammar rules. public demonstration This demonstration generated widespread publicity and became one of the most influential instances in the history of machine translation. The experiment was a collaborative effort between two IBM staff members, , and , along with Leon Dostert and Paul Garvin from the Institute of Languages and Linguistics at Georgetown University. Cuthbert Hurd Peter Sheridan The captivating showcase of the Georgetown Machine's capabilities ignited a surge of optimism and excitement. What’s more important, providing a solid foundation for further advancements in the field of machine translation. the demonstration's success attracted significant funding and support, 1954 – The first public demonstration of an MT system using the Georgetown Machine Meanwhile, across the Atlantic, the Nuffield Foundation made a to Birkbeck College, University of London, that allowed it to take the project of MT translation on a full-time basis in Great Britain. generous grant 1955 – The  Nuffield  Foundation  grant  to  Birkbeck  College,  University  of  London In 1956, several impressive demonstrations of machine translation took place at Birkbeck College, utilizing the computing machine. APEXC (All Purpose Electronic (X) Computer) The same year, a modest, roughly 8-week workshop was organized by , , , and . Its name was . It was for this group that Artificial Intelligence was first named as a science. McCarthy Marvin Minsky Nathaniel Rochester Claude Shannon The Dartmouth Summer Research Project on Artificial Intelligence 1956 – Demonstration of MT experiments on APEXC in Great Britain 1956 – The Dartmouth Summer Research Project on Artificial Intelligence These years the enthusiasm around MT was high; the topic was so hot that research and development groups appeared everywhere. In 1957, (one of the original ten invitees to the Dartmouth workshop) published the first paper on machine learning, " ." Ray Solomonoff An Inductive Inference Machine 1957 – Ray Solomonoff publishes the first paper on machine learning, "An Inductive Inference Machine" In 1959, IBM showed some muscle and unveiled their masterpiece, the first member of the system family, named "Mark I." Automatic Language Translator It consisted of a 65,000-word dictionary and a custom tube-based computer to do the lookups. Texts were hand-copied onto punched cards using custom Cyrillic terminals and then input into the machine for translation. A system was installed for the US Air Force, which produced translations for many years. It was a custom computer that used a high-speed optical disk with 170,000 words and phrases to translate Russian documents into English. 1959 – IBM demonstrates the Automatic Language Translator “Mark 1” It was not the only MT system in use in the US. A group under Michael Zarechnak at Georgetown University proposed the method adopted and named . It was successfully demonstrated in 1961 and 1962. As a result, Russian-English systems were installed at Euratom in 1963 and at the Oak Ridge National Laboratory of the US Atomic Energy Commission in 1964. Georgetown Automatic Translation (GAT) 1962 – A group under Michael Zarechnak in Georgetown University proposes the method adopted and named Georgetown Automatic Translation (GAT) The disillusion and the fall of MT In the mid-1960s, t . In the many research groups that were established around the world, there came an understanding that MT is much more difficult than they had anticipated. The following years were a time of disillusionment. he US government started to question whether MT was financially reasonable and as effective as humans In addition, in 1964, the United States government formed the to evaluate the progress and potential of machine translation. Automatic Language Processing Advisory Committee (ALPAC) 1964 – The Automatic Language Processing Advisory Committee (ALPAC) is formed to assess the state of MT research The publication of the ALPAC in November . It led to significant reductions in funding and a shift toward more theoretical research in computational linguistics. The report's impact was substantial, even giving rise to discussions among researchers about the possibility of similar assessments. While the notoriety of ALPAC is well-known, the report's actual content is often forgotten or misunderstood. Titled "Languages and machines: computers in translation and linguistics," it addressed not only machine translation but also the broader field of computational linguistics, although in practice, NLP research was mostly focused on MT at that time. report 1966 crushed machine translation 1966 – The publication of the ALPAC report Some condemned the ALPAC report as narrow, biased, and shortsighted. However, its influence was profound. It brought a virtual end to MT research in the United States for many years, and MT was perceived as a complete failure. What happened in the next decade that allowed researchers to get into the “languages and machines” concept again? This pivotal period would witness a shift in focus towards practical applications of natural language processing, and the advent of statistical models would breathe new life into the dream of breaking down language barriers. But more on this with all the details – in the next episode! To be continued… If you liked this issue, to receive Oh, and please, share this article with your friends and colleagues. Because... subscribe the second episode of the LLMs history straight to your inbox. To fundamentally push the research frontier forward, one needs to thoroughly understand what has been attempted in history and why current models exist in present forms. Also published . here

The History of LLMs - Part 1: The Era of Mechanical Translation and How It Crashed 

Let's learn about via these 88 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Mvp /Learn Repo No, we're not talking about the most valuable player. MVP stands for "minimum viable product". 1. The Future of Product Management is No-Code Development Three months ago I decided to immerse myself in the rapidly growing world of no-code development. This is what I’ve learned. 2. How to Use Story Mapping to Define MVP Requirements and Align Teams Over the course of my career, I have had the pleasure of building multiple products from scratch, and have collected some strategies that help the process of building a new product and lead to a highly productive and streamlined experience for all stakeholders involved. Story mapping is one of those. 3. The Five Step Approach for Tackling Complex Problems “The definition of genius is taking the complex and making it simple.” - Albert Einstein 4. Minimum Viable Tool (MVT) There is a lot of talk about the Minimum Viable Product — a prototype with just enough features to satisfy early customers, and provide feedback for future development. But feature creep often starts much earlier, in the design & development, if not the ideation stage of a project. 5. Build an Effective MVP in 5 Steps — An Algorithm for Startups Imagine you have a business idea and it seems very good and feasible. No rush to order full cycle development with tremendous investments and the same uncertainty. Test your business hypothesis with an MVP. 6. Why It's a Minimum Viable Process (And Not a Minimum Viable Product) Why do so many startups fail? Why do we hear the concept of the MVP so often? What is it, and is it beneficial? You might think you know the answers to all of these questions. But do you really? Here we talk about all this and even more. I’m happy to welcome product creators and curious developers into this learning journey. So, let’s start with defining the MVP (minimum viable product), one of the most overused and misunderstood concepts in the modern web. In this article, you can learn how an MVP can kickstart your startup. 7. How to Launch Without a Product Or, the No-Product Framework 8. Making a Side Project Yesterday I tweeted that I’d be making one more “big” app before the end of the year. I asked if people preferred if I document the process as I go, or do a recap post at the end of the project. 9. How Developers Win With Low-Code Platforms Photo Credit, @reallynattu 10. How I Built and Shipped My Revenue-Ready MVP in 4 Hours By Using Low-Code Approach All you need is an idea, the right tools and an audience. 11. How To Hire A Developer For Your MVP In 2020 You have an exciting new app idea, so let's make it happen! Hiring a developer can be a difficult task for someone with a non-technical background, especially if they have no plan with which to form their ideas into reality. 12. Software Architecture Basics: What, How & Why Software architecture, design and process of architecting explained using a case study. 13. One Small Step for You, One Big Step for Your IT Career We all sometimes try taking on more significant tasks than we can deliver on—it stems directly from our human inability to evaluate complex tasks correctly. 14. 7 Benefits of MVP for Startups In this article, we are considering key peculiarities and benefits of a minimum viable product that will help you enter the market more successfully. 15. Mozilla Spring MVP Lab TLDR: Apply to be a part of the Mozilla Spring MVP Lab at mozilla.org/builders 16. Start with a Prototype, Follow with an MVP and Then Get to the Final Product Your Guide to the Main Stages of Tech Startup Development 17. Why You Should Always Build a MVP First Let’s take a look at a classic example of a situation that I have observed numerous times. An enthusiastic maker has an idea for a great product and starts building right away without checking for competitors, creating a landing page first or getting some feedback from potential users. The maker sits down in front of his computer and starts building his product blindly. 18. Mozilla Summer Startup Studio and MVP Lab TLDR: See mozilla.org/builders for more details regarding our summer programs! 19. How I Used Blitz JS To Take My Pet Project Into Production Our colleague Lazar decided to built an Absence Tracker, so we can ditch the Telegram group where we reported our absences. 20. Java Vs. PHP: What To Choose In 2021 The choice of a programming language for your startup directly depends on the needs of your project, your budget and other parameters. 21. How to go From Idea to MVP Simple steps to get an idea off the ground and start building momentum. 22. My Experience of Using Notion to Build this All-in-One Job Application Tracker I have attempted to build a Notion template which serves as a job application tracker and different aspects of a job search making the process more conducive. 23. 3 Successful Examples of Using an MVP (Minimum Viable Product) A concept first introduced on the Lean Startup book, MVP means minimum viable product and it is a way to get the most knowledge about the target of your project 24. How to Build and Validate a Startup Idea with a Landing Page MVP [In Less Than Two Hours] The toolkit to help you build MVP with $0 capital and 0 code 25. Startup Costs: Can the MVP Route Save You a Lot of Money? Entrepreneurship is getting popular with every passing day, leading to an increase in rising startups. But how many have tasted success? 26. 5 Low/No-Code Tools For Freelance Mobile App Development in 2020 In the growing world of low-code and no-code, dozens of app building platforms claim to offer the best solution for building native mobile apps. 27. How to Launch Your Own Blockchain: Mainnet Launch [Part VI] I   II   III   IV   V 28. How to Build, Launch & Grow a Profitable Classified Website Like OLX - From Start to Profit The online marketplace platform offers a great opportunity for buyers and sellers to get in contact and sell and buy products through the platform. Classified marketplace platforms are much more comfortable as the user can be both a seller and a buyer. 29. Six Crucial Startup Lessons I Would Share With My Younger Self In hindsight, the first business I started had all the ingredients to succeed. I just didn’t realize it at the time. 30. 10 Great Ways to Evaluate your Minimum Viable Product (MVP) Do you know the main purpose of building Minimum Viable Product or MVP? The answer is to validate the product that you will be launching in the market. 31. How I Designed, Built and Launched a product over the Weekend - A Breakdown of Events Earlier this year, I launched a side project of mine called Lancerlist which is a platform that allows companies to find freelancers in their city. 32. How to Build a MVP REST API Using Low-Code Approach Build and host and API in 15 minutes? Crazy? No, really! 33. About the new simple declarative language we invented for developing web apps with no boilerplate Wasp is a simple language that makes developing full-stack web apps (React, Node) easy and removes boilerplate. 34. How to Find Product-Market Fit by Starting With an MVP MVP is a basic version of a product that consists of minimum features and core functionality, solving an important problem for the end-users. 35. How to Buy Awesome 20 Dollar Prescription Glasses from China 😎 I have bought my first glasses on AliExpress for just 5 dollars. That included prescription lenses and shipping — of course. 36. Microservices and CQRS: Why Business Should Care We have created this blog post for business stakeholders managing the development of a software system or product, those looking to find ways to reduce cost and time to market. This post will be useful for those whose technical background is a bit outdated or isn’t sufficient to make that judgment call. We will look at how to approach architecture planning so that the product is scalable and the money is spent wisely. Also, we will show the example of how CQRS can help in the implementation of client applications and whether microservices is indeed the panacea. 37. Top 10 App Ideas for Restaurant and Food Business Startups in 2022 This post will provide you with the best app ideas for restaurant and food business startups to use as a springboard 38. MVC vs. MVP vs. MVVM: Which Pattern to Choose for Android App Development? In today’s world, the number of mobile device users is continuously growing. This entails the rapid increase in the mobile application development market. Companies around the globe launch hundreds of apps daily. They upgrade their functionality and design with the latest trends. Industry leaders regularly modernize platforms for their creation, filling them with new construction principles. 39. A Guide to Minimum Viable Products for Fractional CTOs 40. MVP(Minimum Viable Product): What It Is and How It Is Built Ever wondered what is an MVP and why do you need it? Here's a detailed overview of what you need to know about MVP in 2023. 41. Can No-code Help Platform Cooperative Developers? Is no-code a potential solution to break past the bottleneck inhibiting the development of platform cooperatives? 42. 10 NoCode Tools to Help You Build Your MVP 🚀 A list of 10 free Nocode tools for creating and launching a successful startup ✅🚀 43. What is an MVP for Software Development? Why is a Minimum Viable Product Important for Software Development Projects? Discover in this article! 44. How I Copied My Favorite SaaS Landing Page 👀 I've got some bad news... 45. How to build an effective MVP in 3 steps Building a startup! You have an epiphany and say to yourself: 46. How to Precisely Validate and Test Startup Ideas through MVP Techtic lists down 6 ways to validate & test business startup ideas through MVP.  Also, know the advantages of MVP and how MVP assists businesses. 47. KYC, Neobanks and More: An Interview with Vitaliy Dyachenko, CEO and Founder of UppLabs 48. Do You Know How to Fail Fast With Your Next Idea? I am sharing all the knowledge I gathered during my research in four months of testing different business ideas. Before starting investing lots of time and building an MVP (minimum viable product) you can test ideas with adtotyping and get some metrics without writing a single line of code. This process shows a powerful way to validate ideas with the help of Facebook. 49. How to Build a Successful MVP in 3 Months 🚀 The year was 2007. There were two guys who just moved to San Francisco. Both were unemployed, so they faced the trouble of paying rent. Suddenly, they realized that all the hotel rooms in San Francisco were reserved because the local industrial design conference at the time attracted a large number of visitors. 50. How to Choose the Right Type of MVP for Your Startup Idea MVPs can come in a thousand shapes and forms. So, in this article, we will focus on the most popular ones. 51. How to Build a Food Delivery Marketplace MVP in Three Hours Here’s the toolkit to build a food delivery marketplace startup. I love to do fast prototyping in 24 hours. Here’s my toolkit to build a food delivery marketplace idea under 3 hours. 52. 5 Tips For Launching a Successful Product Many new products get launched in the market every day. But not every product is a hit. 53. Benefits of Using React Native for MVP Development This article explores why startups choose to develop MVP and the numerous benefits awarded to mobile projects because of React Native. 54. Descriptive Analysis: Why Did These 500 Trending Startups Shut Down? Discovering meaningful patterns in business failures. 55. Choosing Between Prototyping vs MVPs in Software Development In this blog, we shed some light on both MVPs and prototyping to help you understand their requirements and usage in the software development industry. 56. What Is An MVP and Why Is It Necessary? A Deep Dive A minimum viable product (MVP) is a product with a limited number of features that solves at least one issue of your targeted customer. Here's why you need one. 57. Build Startup Success By Launching MVPs In this article, learn more about MVP, their benefits, and 10 steps to building ideal MVPs 58. Creating a Poor Man's API Using PostgREST Creating a full-fledged API requires resources, both time and money. [59. Lean Innovation: How to Tackle Product Development in a Lean and Efficient Way](https://hackernoon.com/lean-innovation-how-to-tackle-product-development-in-a-lean-and-efficient-way-tx2b3wqu) Nowadays, it is especially important to keep the process of product development lean and efficient. Therefore it is helpful to determine the concrete goal of each phase. This makes it easier to keep the entire process goal-oriented, structured and efficient. 60. Why Monolithic Architecture has a Bad Reputation Pros and Cons of Monolithic Architecture in its traditional incarnation or as a Distributed Monolith. 61. Why Start With The First Usable Version of Your Product, Instead of the Best Version There are many possible approaches to launch a new product, and just as many obstacles along the way. However, there's a way of assessing the chances of success before diving in full commitment, and that's where the Minimum Viable Product (MVP) comes in. 62. Building A Tezos's Smart Contract Dashboard Using ReactJS, TezBridge and Netlify [A How-To Guide] I always find it troublesome for me to deploy and interact with Tezos’s Smart Contract at my job as a Software Engineer in my company. So, I decided to build a tool (web app) to solve my problem. 63. How to Build a Cross-Platform App: A Guide that Covers the Main Aspects Software applications market has got a thriving and competitive nature – and it’s no wonder. Mobile, desktop, web, embedded applications help businesses make their services more accessible for the users. Surely, every service provider strives for winning a larger audience of users and keeping the quality at a high-level at the same time. What can make it possible? This is cross-platform development. 64. How To Validate Your Startup Idea With Less Time and Money Validation: The Most Overlooked Aspect Of A Startup 65. Should You Build Your Startup in Public? You have had a great idea, spent some time validating your business idea and are now facing the next questions: How should I approach my building? One of the most used buzzwords in the indie hacker space is “building in public“. It comes in different styles and with different methods. Of course, success in building a side-project publicly also varies. I aim to provide a starting point in this article with a look at methods, platforms, and tools. This blog-post links into the series on introduction in the indie hacker space. 66. Why and How We Used Singer to Bootstrap Our MVP One of the (many) hard things about doing a startup is figuring out what that MVP should be. You are trading off between presenting something that is “good” enough that it gets people excited to use (or invest in) you and getting something done fast. In this article, we explore how we wrestled with this trade-off. Specifically, we explore our decisions around how to use Singer to bootstrap our MVP. It is something we get tons of questions about, and it was hard for us to figure out ourselves! 67. Maximizing Product Success: The Role of Hypothesis Testing, Prototyping, and MVPs Learn how to test hypotheses and create prototypes and MVPs to ensure the success of your product. Find out how methods like RAT and MVP can help product manage 68. What I Learned Building My Side Project: Codetalks.TV 🤓 What is Codetalks? 69. What is a Minimum Viable Product? - Essential Features and Guidelines A Minimum Viable Product is the initial version of your mobile application that contains the main features needed to satisfy the user’s problems. 70. How Minimum Viable Secure Product [MVSP] Works The Minimum Viable Secure Product or MVSP is a way of ensuring that your product is secure from a cybersecurity perspective and will help your reputation. 71. The MVP Lite Approach: A Software Development Approach for 2021 And Beyond What helps people overcome obstacles? Crushing obstacles is hard work. It requires a lot of planning, time management, inner fire, and a thorough understanding of your goals. 72. How the MVP Concept Makes Companies Rethink Their Business Models Essentially, MVP is a tool that allows companies to test the ideas before proceeding to stages of full development and launch. 73. Minimum Viable Product: a Crucial Stage of Development Process In software development, testing ideas, doing trials and continuously learning is the approach that leads to success. That’s why creating a minimum viable product (MVP) can be so beneficial for every business that wants to have their IT product done the right way. 74. The 3 Tools You Need to Need to Get Your MVP From Idea to Launch Over the last 20 years, our Project Manager, Pedro, has helped build many startups. 75. Estimating How Long Will It Take to Build Your MVP If you’re reading this, chances are that you’re about to take the first step in turning your business vision into a reality by building an MVP. 76. 7 Reasons Why Django Framework is a Perfect Framework for Startups The programming language and the main framework are often crucial for startups. Here is why we think Django is a wise choice. 77. Low-code vs No-code: Selecting the Best Stack For Your Startup Choosing the right tech stack for a startup: no-code VS low-code VS code 78. From Idea to MVP to Hacker News in 44 Hours A day by day account of how I went from initial idea to coding and releasing my new app in 11 days, culminating in a Hacker News post. 79. How to Find Minimum Viable Product-Market Fit (PMF) Focus on the problem, not the solution 80. 7 Reasons Why Your MVP may Never Launch 81. A Failed Trip in the MVP World: 'I Thought I Knew Relativity, but Reality is Different' Entering your first towards an MVP (minimum viable product) can cause confusion if you focus on outcomes as planned. Plan to learn with the trip instead. 82. Utility First CSS Leads to Rapid Prototyping I am the co-founder of Flexiple and Remote Tools. In this post, I describe why I chose to use a utility-first CSS framework to build my website’s UI in a fast, robust and low-maintenance way. 83. All the Firebase Functions you Need to Build Your Next Serverless Application Build your own CRUD application by leveraging Firebase's Firestore JavaScript SDK. 84. Building Around A Niche: The Story Behing Carrd's MVP and Success Learning how to build a better MVP by studying Carrd's growth to $1m ARR and 1.6m users. 85. What's The One Thing You Can’t Miss When Building an MVP? At Altar.io we’ve built dozens of products over the years, working with entrepreneurs from all over the world. 86. Evaluating Your App Idea and Supercharging your Chances of Success [Part 2] This is a continuation of a series on bring an app to life, from nothing to something. Read Part 1 here. 87. How to Take Your MVP From Idea to Launch As a business person without the tech skills to build an MVP, it can be tempting to look for a software development partner as soon as possible. 88. Building a Tech Startup  Without a Technical Co-Founder Finding a technical co-founder is one of the biggest challenges faced by startup founders. Here’s how Audapio’s Founder Dudley Gould overcame this common startup hurdle. Thank you for checking out the 88 most read stories about Mvp on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

88 Stories To Learn About Mvp

In my role as Spike’s CEO and co-founder, I've had the opportunity to experience the immense benefits of open protocols. Our team chat and collaboration platform is a testament to this, functioning as a layer 2 solution built atop the foundational layer 1 email protocol (SMTP). This open protocol has allowed us to offer unique solutions for our customers while reducing the need for yet another app. Open protocols are the lifeblood of the internet. They are the invisible threads that weave together the vast digital world we interact with daily. Protocols like TCP, HTTP, SMTP, FTP, and many others have not only stood the test of time but have also been the springboards for significant innovation over the past few decades. They provide a common language, a set of rules that different clients and solutions can use to communicate easily across different device types and platforms. This uniformity is what makes the internet a global network instead of a collection of isolated systems that cannot communicate. When we look at the adoption of new technology, this common understanding is critical. It reduces friction and simplifies compatibility. Customers are more likely to embrace new technology when it fits seamlessly into their existing digital ecosystem, and open protocols are key to achieving this. Imagine a world where Apple’s iCloud email couldn't communicate with Gmail users. The tech industry moved away from protocols Over the past 15 years, we've seen a noticeable shift in the tech industry. Companies have increasingly moved away from building on open protocols, opting instead to create platforms they own and control. From a business perspective, it might seem like a better path to own and control the entire stack, but it’s a bad idea to try to lock your customers in. Any web browser can access just about any website. Imagine a world where our web browsers could only access a subset of the internet. That’s the world we’ve seen developed with social media and messaging apps. Facebook owns and controls its customer’s data. and non-Apple users can’t easily use it with Android customers. This wasn’t how the internet was designed to be, but big tech companies have taken over and built up walled gardens. Customers are lock-in and innovation is stifled iMessage isn’t available on the PC The state of affairs at Twitter I've been closely following the over the past few months. Following Elon Musk's buyout of the company, a significant restructuring occurred, leading to the departure of numerous executives and nearly half of the workforce - especially on the engineering side. This move, while drastic, has had unintended consequences, including a surge in legal fees and the potential aiding of Meta in creating . Twitter now finds itself , not only with Meta over accusations of intellectual property theft but also with a legal firm over a hefty bill and with former employees over severance pay issues. Threads has emerged as a formidable competitor gaining rapid popularity with nearly 100 million users in a matter of days. These developments underscore the complex challenges Twitter is grappling with, as it navigates a path forward as a private company. Every decision Musk makes is analyzed and written about in depth by the tech media and mainstream media alike. recent chaos at Twitter Threads in legal disputes The Reddit effect While the world was watching the drama on Twitter, another social media giant, Reddit, was grappling with its own controversy. Reddit CEO Steve Huffman in May that the platform would begin charging third-party apps, bots, and companies for using the site's API that many of the popular third-party apps used. This decision sparked a from the Reddit community, leading to a 48-hour protest where numerous popular subreddits went dark in opposition which dramatically affected Reddit’s SEO and advertising impact. This powerful demonstration of community powers underscores the balance social media platforms must strike between operational needs and user expectations - further defining the question: who is the customer among free services? announced significant backlash Enter Nostr Towards the end of 2022, Nostr emerged as a promising open protocol designed to create a new way to build social networking solutions that are free of big tech control. Its unique approach allows users to own and control their data, fostering the creation of decentralized social networks that are very similar to the early days of email when anyone could run their own server. Unlike traditional platforms like Facebook or Reddit, Nostr doesn't rely on a central server. Users run a Nostr client, publish content, sign it with their private key, and send it to other servers that relay the content. While this might sound complicated, it’s all happening in a matter of seconds. If users have issues with certain relays, they have the freedom to run their own relay or even start their own network of relays to redistribute their content. There is no Nostr “database” or “main server”. Nostr servers are powered by the people for the people. Any company can run one on a massive AWS server or any single person can run it on something as simple as a Raspberry Pi4. Despite being an open-source project, Nostr has garnered significant support from major technology influencers, including a . While Nostr operates independently of Bitcoin, it can be integrated with Bitcoin's Lightning Network, opening up possibilities for worldwide without the need for banks - especially in areas around the world that are . notable donation from former Twitter CEO and founder Jack Dorsey micropayments unbanked Should Twitter build on top of Nostr? In the world of social media, the idea of a major platform like Twitter becoming a Nostr client and supporter represents a major shift. This move would fundamentally alter the dynamics of user interaction and data ownership, marking a departure from the traditional model of social networks. Instead of operating as “owner of data”, Twitter would become a Nostr client and relay. At its core, Nostr is about empowering users without the need for trusted third parties.. It allows users to own and control their data, a stark contrast to the current norm where platforms hold the reins. By adopting Nostr, Twitter would be placing the power back into the hands of its users, a move that aligns with the original ethos of the internet - a decentralized space where users have control. This shift would not only change the way Twitter operates but also redefine its goals. Instead of focusing on controlling user data and interactions, Twitter's objective would become creating the best Nostr client. This means providing a user experience that is seamless, intuitive, and enriching, while also ensuring that users have the freedom and tools to manage their data. Twitter could still have advertising, and still offer Twitter Blue for verification and increased reach, but it would all be done on top of Nostr as the client backend. Twitter would switch from running it’ own core technology to simply acting as a client on top of an open protocol - very similar to how email apps work today. By embracing Nostr as a backend protocol, Twitter could enhance user trust, foster a more democratic and inclusive platform, and stimulate innovation worldwide without the need to be the gatekeeper for everything. This move could set a precedent for other social networks, encouraging them to follow suit and embrace open protocols like Nostr and (a competing protocol). In an era where concerns about data privacy and platform control are increasingly prominent, this could be a significant step towards a more user-centric model of social media where the users are ultimately in control of their data ActivityPub Wrap up In my experience leading Spike, I've seen firsthand the benefits of prioritizing user empowerment and data ownership. Our platforms are built on top of email technology so Spike users can easily chat with someone using iCloud or Gmail. Simply put, protocols > platforms. As we look towards the future, the potential adoption of Nostr by Twitter could signal the dawn of a new era for social media. This would be an era characterized by genuine user control, where the power dynamics are shifted back to the individuals who form the backbone of these platforms. It's a bold vision, indeed, but one that I firmly believe is worth pursuing by Twitter, Threads, and other social media platforms. A social media landscape where users are truly in control, where data ownership is the default and expectations, and where platforms compete on providing the best user experience rather than controlling the most data, is a landscape that promises greater freedom, inclusivity, and innovation. The journey towards a more user-centric model of social media is just beginning. But with open protocols like Nostr leading the way, I believe we are heading in the right direction. And I, for one, am excited to see where this journey takes us.

Twitter's Redemption: How Nostr Could Reshape Its Future

Off on a Comet! a Journey through Planetary Space by Jules Verne, is part of the HackerNoon Books Series. You can jump to any chapter in this book . A MYSTERIOUS SEA here CHAPTER V. A MYSTERIOUS SEA Violent as the commotion had been, that portion of the Algerian coast which is bounded on the north by the Mediterranean, and on the west by the right bank of the Shelif, appeared to have suffered little change. It is true that indentations were perceptible in the fertile plain, and the surface of the sea was ruffled with an agitation that was quite unusual; but the rugged outline of the cliff was the same as heretofore, and the aspect of the entire scene appeared unaltered. The stone hostelry, with the exception of some deep clefts in its walls, had sustained little injury; but the gourbi, like a house of cards destroyed by an infant’s breath, had completely subsided, and its two inmates lay motionless, buried under the sunken thatch. It was two hours after the catastrophe that Captain Servadac regained consciousness; he had some trouble to collect his thoughts, and the first sounds that escaped his lips were the concluding words of the rondo which had been so ruthlessly interrupted; “Constant ever I will be,
           Constant....” His next thought was to wonder what had happened; and in order to find an answer, he pushed aside the broken thatch, so that his head appeared above the . “The gourbi leveled to the ground!” he exclaimed, “surely a waterspout has passed along the coast.” debris He felt all over his body to perceive what injuries he had sustained, but not a sprain nor a scratch could he discover. “Where are you, Ben Zoof?” he shouted. “Here, sir!” and with military promptitude a second head protruded from the rubbish. “Have you any notion what has happened, Ben Zoof?” “I’ve a notion, captain, that it’s all up with us.” “Nonsense, Ben Zoof; it is nothing but a waterspout!” “Very good, sir,” was the philosophical reply, immediately followed by the query, “Any bones broken, sir?” “None whatever,” said the captain. Both men were soon on their feet, and began to make a vigorous clearance of the ruins, beneath which they found that their arms, cooking utensils, and other property, had sustained little injury. “By-the-by, what o’clock is it?” asked the captain. “It must be eight o’clock, at least,” said Ben Zoof, looking at the sun, which was a considerable height above the horizon. “It is almost time for us to start.” “To start! what for?” “To keep your appointment with Count Timascheff.” “By Jove! I had forgotten all about it! “By Jove! I had forgotten all about it!” exclaimed Servadac. Then looking at his watch, he cried, “What are you thinking of, Ben Zoof? It is scarcely two o’clock.” “Two in the morning, or two in the afternoon?” asked Ben Zoof, again regarding the sun. Servadac raised his watch to his ear. “It is going,” said he; “but, by all the wines of Medoc, I am puzzled. Don’t you see the sun is in the west? It must be near setting.” “Setting, captain! Why, it is rising finely, like a conscript at the sound of the reveille. It is considerably higher since we have been talking.” Incredible as it might appear, the fact was undeniable that the sun was rising over the Shelif from that quarter of the horizon behind which it usually sank for the latter portion of its daily round. They were utterly bewildered. Some mysterious phenomenon must not only have altered the position of the sun in the sidereal system, but must even have brought about an important modification of the earth’s rotation on her axis. Captain Servadac consoled himself with the prospect of reading an explanation of the mystery in next week’s newspapers, and turned his attention to what was to him of more immediate importance. “Come, let us be off,” said he to his orderly; “though heaven and earth be topsy-turvy, I must be at my post this morning.” “To do Count Timascheff the honor of running him through the body,” added Ben Zoof. If Servadac and his orderly had been less preoccupied, they would have noticed that a variety of other physical changes besides the apparent alteration in the movement of the sun had been evolved during the atmospheric disturbances of that New Year’s night. As they descended the steep footpath leading from the cliff towards the Shelif, they were unconscious that their respiration became forced and rapid, like that of a mountaineer when he has reached an altitude where the air has become less charged with oxygen. They were also unconscious that their voices were thin and feeble; either they must themselves have become rather deaf, or it was evident that the air had become less capable of transmitting sound. The weather, which on the previous evening had been very foggy, had entirely changed. The sky had assumed a singular tint, and was soon covered with lowering clouds that completely hid the sun. There were, indeed, all the signs of a coming storm, but the vapor, on account of the insufficient condensation, failed to fall. The sea appeared quite deserted, a most unusual circumstance along this coast, and not a sail nor a trail of smoke broke the gray monotony of water and sky. The limits of the horizon, too, had become much circumscribed. On land, as well as on sea, the remote distance had completely disappeared, and it seemed as though the globe had assumed a more decided convexity. At the pace at which they were walking, it was very evident that the captain and his attendant would not take long to accomplish the three miles that lay between the gourbi and the place of rendezvous. They did not exchange a word, but each was conscious of an unusual buoyancy, which appeared to lift up their bodies and give as it were, wings to their feet. If Ben Zoof had expressed his sensations in words, he would have said that he felt “up to anything,” and he had even forgotten to taste so much as a crust of bread, a lapse of memory of which the worthy soldier was rarely guilty. As these thoughts were crossing his mind, a harsh bark was heard to the left of the footpath, and a jackal was seen emerging from a large grove of lentisks. Regarding the two wayfarers with manifest uneasiness, the beast took up its position at the foot of a rock, more than thirty feet in height. It belonged to an African species distinguished by a black spotted skin, and a black line down the front of the legs. At night-time, when they scour the country in herds, the creatures are somewhat formidable, but singly they are no more dangerous than a dog. Though by no means afraid of them, Ben Zoof had a particular aversion to jackals, perhaps because they had no place among the fauna of his beloved Montmartre. He accordingly began to make threatening gestures, when, to the unmitigated astonishment of himself and the captain, the animal darted forward, and in one single bound gained the summit of the rock. “Good Heavens!” cried Ben Zoof, “that leap must have been thirty feet at least.” “True enough,” replied the captain; “I never saw such a jump.” Meantime the jackal had seated itself upon its haunches, and was staring at the two men with an air of impudent defiance. This was too much for Ben Zoof’s forbearance, and stooping down he caught up a huge stone, when to his surprise, he found that it was no heavier than a piece of petrified sponge. “Confound the brute!” he exclaimed, “I might as well throw a piece of bread at him. What accounts for its being as light as this?” Nothing daunted, however, he hurled the stone into the air. It missed its aim; but the jackal, deeming it on the whole prudent to decamp, disappeared across the trees and hedges with a series of bounds, which could only be likened to those that might be made by an india-rubber kangaroo. Ben Zoof was sure that his own powers of propelling must equal those of a howitzer, for his stone, after a lengthened flight through the air, fell to the ground full five hundred paces the other side of the rock. The orderly was now some yards ahead of his master, and had reached a ditch full of water, and about ten feet wide. With the intention of clearing it, he made a spring, when a loud cry burst from Servadac. “Ben Zoof, you idiot! What are you about? You will break your back!” And well might he be alarmed, for Ben Zoof had sprung to a height of forty feet into the air. Fearful of the consequences that would attend the descent of his servant to , Servadac bounded forwards, to be on the other side of the ditch in time to break his fall. But the muscular effort that he made carried him in his turn to an altitude of thirty feet; in his ascent he passed Ben Zoof, who had already commenced his downward course; and then, obedient to the laws of gravitation, he descended with increasing rapidity, and alighted upon the earth without experiencing a shock greater than if he had merely made a bound of four or five feet high. terra firma Ben Zoof burst into a roar of laughter. “Bravo!” he said, “we should make a good pair of clowns.” But the captain was inclined to take a more serious view of the matter. For a few seconds he stood lost in thought, then said solemnly, “Ben Zoof, I must be dreaming. Pinch me hard; I must be either asleep or mad.” “It is very certain that something has happened to us,” said Ben Zoof. “I have occasionally dreamed that I was a swallow flying over the Montmartre, but I never experienced anything of this kind before; it must be peculiar to the coast of Algeria.” Servadac was stupefied; he felt instinctively that he was not dreaming, and yet was powerless to solve the mystery. He was not, however, the man to puzzle himself for long over any insoluble problem. “Come what may,” he presently exclaimed, “we will make up our minds for the future to be surprised at nothing.” “Right, captain,” replied Ben Zoof; “and, first of all, let us settle our little score with Count Timascheff.” Beyond the ditch lay a small piece of meadow land, about an acre in extent. A soft and delicious herbage carpeted the soil, whilst trees formed a charming framework to the whole. No spot could have been chosen more suitable for the meeting between the two adversaries. Servadac cast a hasty glance round. No one was in sight. “We are the first on the field,” he said. “Not so sure of that, sir,” said Ben Zoof. “What do you mean?” asked Servadac, looking at his watch, which he had set as nearly as possible by the sun before leaving the gourbi; “it is not nine o’clock yet.” “Look up there, sir. I am much mistaken if that is not the sun;” and as Ben Zoof spoke, he pointed directly overhead to where a faint white disc was dimly visible through the haze of clouds. “Nonsense!” exclaimed Servadac. “How can the sun be in the zenith, in the month of January, in lat. 39 degrees N.?” “Can’t say, sir. I only know the sun is there; and at the rate he has been traveling, I would lay my cap to a dish of couscous that in less than three hours he will have set.” Hector Servadac, mute and motionless, stood with folded arms. Presently he roused himself, and began to look about again. “What means all this?” he murmured. “Laws of gravity disturbed! Points of the compass reversed! The length of day reduced one half! Surely this will indefinitely postpone my meeting with the count. Something has happened; Ben Zoof and I cannot both be mad!” The orderly, meantime, surveyed his master with the greatest equanimity; no phenomenon, however extraordinary, would have drawn from him a single exclamation of surprise. “Do you see anyone, Ben Zoof?” asked the captain, at last. “No one, sir; the count has evidently been and gone.” “But supposing that to be the case,” persisted the captain, “my seconds would have waited, and not seeing me, would have come on towards the gourbi. I can only conclude that they have been unable to get here; and as for Count Timascheff—” Without finishing his sentence. Captain Servadac, thinking it just probable that the count, as on the previous evening, might come by water, walked to the ridge of rock that overhung the shore, in order to ascertain if the were anywhere in sight. But the sea was deserted, and for the first time the captain noticed that, although the wind was calm, the waters were unusually agitated, and seethed and foamed as though they were boiling. It was very certain that the yacht would have found a difficulty in holding her own in such a swell. Another thing that now struck Servadac was the extraordinary contraction of the horizon. Under ordinary circumstances, his elevated position would have allowed him a radius of vision at least five and twenty miles in length; but the terrestrial sphere seemed, in the course of the last few hours, to have become considerably reduced in volume, and he could now see for a distance of only six miles in every direction. Dobryna Meantime, with the agility of a monkey, Ben Zoof had clambered to the top of a eucalyptus, and from his lofty perch was surveying the country to the south, as well as towards both Tenes and Mostaganem. On descending, be informed the captain that the plain was deserted. “We will make our way to the river, and get over into Mostaganem,” said the captain. The Shelif was not more than a mile and a half from the meadow, but no time was to be lost if the two men were to reach the town before nightfall. Though still hidden by heavy clouds, the sun was evidently declining fast; and what was equally inexplicable, it was not following the oblique curve that in these latitudes and at this time of year might be expected, but was sinking perpendicularly on to the horizon. As he went along, Captain Servadac pondered deeply. Perchance some unheard-of phenomenon had modified the rotary motion of the globe; or perhaps the Algerian coast had been transported beyond the equator into the southern hemisphere. Yet the earth, with the exception of the alteration in its convexity, in this part of Africa at least, seemed to have undergone no change of any very great importance. As far as the eye could reach, the shore was, as it had ever been, a succession of cliffs, beach, and arid rocks, tinged with a red ferruginous hue. To the south—if south, in this inverted order of things, it might still be called—the face of the country also appeared unaltered, and some leagues away, the peaks of the Merdeyah mountains still retained their accustomed outline. Presently a rift in the clouds gave passage to an oblique ray of light that clearly proved that the sun was setting in the east. “Well, I am curious to know what they think of all this at Mostaganem,” said the captain. “I wonder, too, what the Minister of War will say when he receives a telegram informing him that his African colony has become, not morally, but physically disorganized; that the cardinal points are at variance with ordinary rules, and that the sun in the month of January is shining down vertically upon our heads.” Ben Zoof, whose ideas of discipline were extremely rigid, at once suggested that the colony should be put under the surveillance of the police, that the cardinal points should be placed under restraint, and that the sun should be shot for breach of discipline. Meantime, they were both advancing with the utmost speed. The decompression of the atmosphere made the specific gravity of their bodies extraordinarily light, and they ran like hares and leaped like chamois. Leaving the devious windings of the footpath, they went as a crow would fly across the country. Hedges, trees, and streams were cleared at a bound, and under these conditions Ben Zoof felt that he could have overstepped Montmartre at a single stride. The earth seemed as elastic as the springboard of an acrobat; they scarcely touched it with their feet, and their only fear was lest the height to which they were propelled would consume the time which they were saving by their short cut across the fields. It was not long before their wild career brought them to the right bank of the Shelif. Here they were compelled to stop, for not only had the bridge completely disappeared, but the river itself no longer existed. Of the left bank there was not the slightest trace, and the right bank, which on the previous evening had bounded the yellow stream, as it murmured peacefully along the fertile plain, had now become the shore of a tumultuous ocean, its azure waters extending westwards far as the eye could reach, and annihilating the tract of country which had hitherto formed the district of Mostaganem. The shore coincided exactly with what had been the right bank of the Shelif, and in a slightly curved line ran north and south, whilst the adjacent groves and meadows all retained their previous positions. But the river-bank had become the shore of an unknown sea. Eager to throw some light upon the mystery, Servadac hurriedly made his way through the oleander bushes that overhung the shore, took up some water in the hollow of his hand, and carried it to his lips. “Salt as brine!” he exclaimed, as soon as he had tasted it. “The sea has undoubtedly swallowed up all the western part of Algeria.” “It will not last long, sir,” said Ben Zoof. “It is, probably, only a severe flood.” The captain shook his head. “Worse than that, I fear, Ben Zoof,” he replied with emotion. “It is a catastrophe that may have very serious consequences. What can have become of all my friends and fellow-officers?” Ben Zoof was silent. Rarely had he seen his master so much agitated; and though himself inclined to receive these phenomena with philosophic indifference, his notions of military duty caused his countenance to reflect the captain’s expression of amazement. But there was little time for Servadac to examine the changes which a few hours had wrought. The sun had already reached the eastern horizon, and just as though it were crossing the ecliptic under the tropics, it sank like a cannon ball into the sea. Without any warning, day gave place to night, and earth, sea, and sky were immediately wrapped in profound obscurity. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jules Verne (1998). Off on a Comet! a Journey through Planetary Space. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/1353/pg1353-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

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