Using nFlux, manufacturers gain access to real-time video analytics that assist operators in performing manual procedures across production, assembly, and inspection lines

nFlux

nflux

William Goldman, a two time Oscar-winning screenwriter, , “ ” famously said Nobody knows anything…Not one person in the entire motion picture field knows for a certainty what’s going to work. Every time out it’s a guess and, if you’re lucky, an educated one. However, due to the explosion of data and analytics tools, we now have the ability to such as viewing behaviour and user feedback (through social media) real-time. Over time, this data could allow creators to predict the most effective casting and plot lines. For example, when the Times Group used insights from a data analytics app, Parse.ly to reorder their gallery stories, their . The editors now use the tool to shape the direction of stories, using real-time data of audience engagement. analyse patterns page views went up by 70% Hollywood is already between the creator and consumer: various tools are allowing production houses to incorporate audience reactions into how content gets created, marketed and distributed. to gauge the emotional response to films through Twitter and Facebook responses. These tools can not only highlight the responses, but attempt to explain the reasons for these responses. redefining its relationship IBM offers social sentiment analysis This of, course, is limiting: if you use historical data to predict future behaviour, you are unlikely to support potentially game-changing scripts or talent. Moreover, key Hollywood executives such as Richard Plepler and Nina Jacobson, have publicly stated that they believe that : in the end, - such as the quality of story, talent and production value- matter more. data science can only be used to an extent in content creation the fundamentals Additionally, the literature on what makes a ‘hit’ TV show or film highlights that while there are you can follow to create appealing content, ultimately even the Silicon Valley players such as Netflix and Facebook agree that data analytics are better utilised in 1) content distribution and audience targeting/ recommendations and 2) understanding . certain formulas personalisation of content audience engagement And yet, the content production process itself given the 1) i , as tech players look to compete for high quality content and 2) changing audience behaviours and tastes and 3) the rapid globalisation of content distribution. In 2017 itself, Apple and Facebook both budgeted over $1 billion for original programming, and Netflix announced that it planned to . This year, there are over 500 scripted TV shows being made- which is 2x the number in 2012. needs to adapt, nflux of capital into original programming spend $8 billion on content The amount of content being made, the variety of content being made, and the locations at which the content is being created is increasing rapidly, while the supply of talent, and audience attentions spans stays constant. The industry has already been disrupted: it needs the tools to adapt. I believe data science can be used to disrupt the content production process itself. Given that the most can be 1) storyboarding and shot list generation 2) schedule optimisation and 3 budgeting: data science could be used to automate the more tedious processes, so that content creators can focus on the storytelling + other more creative parts of the process. time consuming parts of the process are already helping production teams collaborate across teams and locations. However, these apps face severe challenges when it comes to large-scale adoption, given that production teams are often freelance teams that work together for a period of time, and come from a non tech savvy culture. When Netflix introduced an ecosystem of apps to improve efficiency, it found encouraging the adoption of this new technology difficult at the start. Project management apps However, using could both reduce script rewriting time and improve production planning by running ‘what if’ scenarios to test script variations, and removing certain elements of production to reduce costs. This would also not require wholesale adoption across production teams, as is required in the case of production management apps. AI for ‘agile’ content creation Netflix is already pioneering this approach. As highlighted in it’s given the scale at which it is producing content: Medium Blog, this is a necessity, “Each production is a mountain of operational and logistical challenges that consumes and produces tremendous amounts of data. At Netflix’s scale, this is further amplified to levels seldom encountered before in the history of entertainment. This has created opportunities to organize, analyze and model this data that are equally singular in history. This is where data science can aid the art of producing entertainment.” To provide a few examples, the company models cost estimations of how much a production will cost, that can deal with data sparsity. It also generates schedules using mathematical optimisation. As the company expands globally, it is using visualisation to analyse resource dependency and anticipate production delivery patterns. Lastly it uses prediction algorithms to sequence and scale its content localisation slating across markets. Clearly, the exploration of applying data science to pre and post content production is a nascent field. As more tech platforms begin to invest in content at a large-scale globally, the use of data science will become a necessity, both in terms of efficiency of content production and content economics. Given this approach plays into these companies’ strengths, I think a large-scale change in culture is likely afoot. I’m excited to see whether AI can successfully be applied to analysing scripts and storylines over the next few years; to tackle this complex challenge. several ventures are already attempting A blue ocean space is using data science to identify new talent. The stars seem to be aligning in this area. The in Hollywood- across production, acting and writing- is resoundingly clear. The for this new crop of talent has already been validated at the box office. On the other hand, there is an entire generation of social media stars that has built up a following, and talent on Youtube that is waiting to be discovered. We’re already seeing companies attempting to use AI to identify future leaders: need for new, diverse voices appetite how long will it be before this is applied to future stars and influencers?

Getting Creative: More Content, More Hits?

Neural Network for Valuing Bitcoin: Numerical Results, Implementation and Discussion

This paper is under CC 4.0 license. available on arxiv Authors: (1) Hatem A. Alharbi, CSchool of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom; (2) Taisir E.H. Elgorashi, School of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom; (3) Jaafar M.H. Elmirghani, School of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom. Table of Links Abstract & Introduction Related Works Repealing Net Neutrality Profit-Driven Model Results Conclusions & References Biographies V. CONCLUSIONS In this paper, we developed a MILP model to optimize the pricing scheme used by ISPs to charge CPs for delivering their video content under the repeal of net neutrality where ISPs can treat data intensive traffic less favorably. A techno-economic Mixed Integer Linear Programming (MILP) model is developed to maximize the ISP profit by optimizing the ISP pricing scheme to charge different classes of service differently subject to PED. We considered three classes of service that represent different data rate requirements of video content. The analysis addressed three CP delivery scenarios; cloud-based delivery, cloud-fog based delivery and fog-based delivery. The results show that the discriminatory pricing scheme can increase the ISPs profit by a factor of 8. The results also show that by influencing the way end-users consume data-intensive content, the core network traffic and consequently power consumption are reduced by up to 49% and 55%, respectively, compared to the net neutrality scenario. Acknowledgements The authors would like to acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC), INTERNET (EP/H040536/1), STAR (EP/K016873/1) and TOWS (EP/S016570/1) projects. The first author would like to acknowledge the Government of Saudi Arabia and Taibah University for funding his PhD scholarship. All data are provided in full in the results section of this paper. REFERENCES Cisco, “The Zettabyte Era: Trends and Analysis,” 2017. , “AT&T Profit Margin (Quarterly),” 2018. [Online]. Available: . [Accessed: 01-Aug-2018]. Ycharts.com https://ycharts.com/companies/T/profit_margin Ycharts, “Netflix Profit Margin (Quarterly),” 2018. [Online]. Available: .
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Impact of the Net Neutrality Repeal on Communication Networks: Conclusions & References

Dividend stocks are a great way to generate income from your investments while also benefiting from capital appreciation. However, not all dividend stocks are created equal. Some may offer high yields but low growth prospects, while others may have erratic payouts or poor stock performance. To help you find the best dividend stocks under $50 in 2023, we have screened for companies that have: : This is an arbitrary threshold, but it helps us focus on stocks that are more accessible and less expensive than some of the high-priced dividend aristocrats or blue chips. A current share price below $50 This is also a subjective cutoff, but it ensures that we get a decent return on our investment. A yield above 2% is also higher than the average yield of the S&P 500 index, which is currently around 1.3%. A dividend yield above 2%: This shows that the company has a long-term commitment to rewarding shareholders with consistent and growing dividends. It also indicates that the company has a stable and profitable business model that can withstand various economic cycles and competitive pressures. A history of increasing dividends for at least 10 years: This demonstrates that the company has been able to grow its earnings over time, which supports its dividend payments and future growth prospects. A positive earnings growth rate also implies that the company has a competitive advantage or a strong market position in its industry. A positive earnings growth rate over the past five years: This measures how much of the company’s earnings are paid out as dividends. A lower payout ratio means that the company retains more earnings for reinvestment or debt reduction, which enhances its financial flexibility and sustainability. A higher payout ratio means that the company has less room to grow or maintain its dividends in case of an earnings decline. A reasonable payout ratio below 80%: Based on these criteria and a few more important ones listed by five of the best dividend stocks under $50 that you can explore right now. Disclaimer: The information provided in this article is for informational purposes only and e. Investing involves risk and you should carefully consider all risks and uncertainties before making any investment decisions. We do not guarantee the accuracy or completeness of the information presented and we are not responsible for any errors or omissions. You should consult with a financial advisor before making any investment decisions. should not be construed as professional investment advic List of best dividend stocks under $50 in 2023 (NYSE: PFE) Pfizer Pfizer is one of the world's largest pharmaceutical companies, with a of drugs and vaccines for various therapeutic areas. The company has been in the spotlight for its COVID-19 vaccine, which has generated strong sales and profits in 2021 and 2022. diversified portfolio Pfizer has a long history of paying and growing dividends, with 11 consecutive years of annual increases. The current dividend yield is 4%, and the payout ratio is 54%. The company has also delivered an impressive earnings growth rate of 36% over the past five years. Pfizer expects to grow its revenue by 6% to 9% annually through 2025, driven by its core products and pipeline opportunities. The company also plans to return more cash to shareholders through dividends and share buybacks. (NYSE: T) AT&T AT&T is a leading telecommunications company that provides wireless, broadband, video, and media services to millions of customers. The company also owns WarnerMedia, which includes HBO, CNN, Warner Bros., and other entertainment assets. AT&T has been paying dividends since 1984 and has increased them for 36 consecutive years. The current dividend yield is a whopping 6%, and the payout ratio is 58%. The company has also grown its earnings by an average of 5% per year over the past five years. AT&T is undergoing a major transformation as it plans to spin off WarnerMedia and merge it with Discovery (NASDAQ: DISCA) in mid-2023. The deal will create a new media giant that will compete with Netflix (NASDAQ: NFLX) and Disney (NYSE: DIS). AT&T will focus on its core connectivity business and reduce its debt load. AT&T expects to maintain its dividend at current levels after the spin-off and grow it modestly over time. The company also expects to generate strong free cash flow and invest in its wireless network and fiber broadband expansion. (NASDAQ: TXN) Texas Instruments Texas Instruments is one of the world's largest companies that designs and manufactures chips for various applications such as industrial equipment, automotive systems, personal electronics, communications devices, and more. semiconductor Texas Instruments has been paying dividends since 1962 and has increased them for 18 consecutive years. The current dividend yield is 2.8%, and the payout ratio is only 46%. The company has also achieved an impressive earnings growth rate of 21% per year over the past five years. Texas Instruments benefits from its diversified end markets, strong competitive position, high-quality products, efficient manufacturing capabilities, and robust cash generation. The company expects to grow its revenue by mid-to-high single digits annually over the long term and return more than 100% of its free cash flow to shareholders through dividends and share buybacks. (NYSE: XOM) Exxon Mobil Exxon Mobil is one of the largest oil and gas companies in the world, with operations spanning exploration, production, refining, chemicals and renewables. The company has been recovering from the impact of the COVID-19 pandemic on oil demand and prices, as well as facing pressure from investors and regulators to address climate change risks. Exxon Mobil has been taking steps to improve its profitability and sustainability by cutting costs, divesting non-core assets, investing in low-carbon technologies and increasing shareholder returns. The company expects to grow its earnings by more than four times by 2027, compared to its pre-pandemic level in 2019, while also reducing its greenhouse gas intensity by up to 20% by 2025. emissions Exxon Mobil pays a quarterly dividend of $0.87 per share, which translates to an annual yield of about 3.5% at the current stock price. The company has raised its dividend for 39 consecutive years, making it another long-standing dividend aristocrat. Exxon Mobil trades at a fair valuation of 15 times forward earnings, which is slightly above the industry average of 14 times. The company also generates solid cash flow and has a manageable debt-to-equity ratio of 0.8. (NASDAQ: CSCO) Cisco Systems Inc Cisco is a leading provider of networking equipment and software for enterprises and consumers. The company has been paying dividends since 2011 and has increased them every year since then. The current dividend yield is 3.05% and the payout ratio is 49%. Cisco has also grown its earnings per share (EPS) by an average of 9.6% annually over the past five years. The stock is trading at $48.19 as of March 22, 2023. Conclusion In conclusion, dividend stocks are a reliable way to generate income while benefiting from capital appreciation. However, not all dividend stocks are created equal. To find the best dividend stocks under $50, we have used specific criteria such as a current share price below $50, a dividend yield above 2%, a history of increasing dividends for at least 10 years, a positive earnings growth rate over the past five years, and a reasonable payout ratio below 80%. Based on these criteria, Pfizer, AT&T, Texas Instruments, and Exxon Mobil are some of the best dividend stocks under $50 in 2023. These companies have a long history of paying and growing dividends, a stable and profitable business model, and a strong market position in their respective industries. Moreover, they offer decent dividend yields and a potential for future growth, making them a good investment opportunity for income-seeking investors. Disclaimer: The information provided in this article is for informational purposes only and e. Investing involves risk and you should carefully consider all risks and uncertainties before making any investment decisions. We do not guarantee the accuracy or completeness of the information presented and we are not responsible for any errors or omissions. You should consult with a financial advisor before making any investment decisions. should not be construed as professional investment advic

Dividend Stocks Under $50 to Consider in 2023

How to Find, and Leverage Influencers To Market Your App Ever since iOS 14.5 in April of 2021, the process of having an influencer promote your product has become increasingly important. handicapped programmatic marketing influencer marketing — — In fact, i nfluencer marketing campaigns grew a staggering 26% in 2021 and the trend appears to be continuing in 2022. Many bootstrapped startup founders & indie entrepreneurs believe that influencer marketing is out of reach for them. Often I hear founders say: “Aren’t influencers expensive?” super “What would influencers want to do with me and my product?” “I can’t get in touch with influencers even if I tried.” I’m here to tell you that influencer marketing is more accessible than you think! Why? Because I was able to partner with NFL wide receiver Donovan Peoples-Jones to market my mobile game to the iOS top 100 free games list without paying a cent. DeepPassJam.com Here’s how I did it, and how you can do it too! Note: Even though our product was a mobile game, all these tips are applicable to mobile apps and “direct-to-consumer” products too! Step 1: Identify and Make A List Start by creating a spreadsheet of your top 50 ideal influencers to work with. You should separate your list into 4 columns: “Name” “Contact” “Passion” and “Status.” Under the contact column, write down the most convenient way to contact the influencer. A warm intro is most preferred, followed by email, followed by text, followed by in-browser “contact me” page, followed by cold social media DM. Quite often, smaller creators will have their business email available publicly if you scan their social media and website site. If you cannot find an avenue to contact them, then the influencer is likely too big — leave the contact column blank. Under the passion column, rate on a scale from 1 to 5 how much passion you would have to work with them if they said “yes.” Under the status column, write down the status of reaching out. All the influencers will start with a status of “have not contacted.” Once you reach out once, change to “Contacted x1” If you follow up once, change to “Contacted x2”. If they respond, then change to “Negotiating.” If they ultimately decide to pass, or you follow up 3 times without a response change this column to “Contact lost.” This column serves as a tool to keep you organized. Client Relationship Manager Sort the list by contact method quality. From there, sort the list again by passion. You should reach out to creators in this order. Eight creators at a time. You should follow up three times without a response before you give up on reaching that creator. A few tips to think about when creating your list: Big influencers cost big bucks. Smaller influencers are often very affordable or even “free” (more on this later). Target influencers with followings under 50k on YouTube/Instagram or 500k on Tik Tok to start. Target Smaller Influencers — Some influencers have astronomical follower counts but when you look at their content, it’s not engaged with or only being engaged by bots. Ensure Your Influencer Has The Right Influence — Beware of influencers like this! Also, it’s critical that the influencer has an audience that matches of people who use your product. the demographics It doesn’t matter how many followers Oprah Winfrey has, if she promotes a First Person Shooter game (something typically younger men enjoy), the campaign could perform catastrophically poorly since Oprah’s following tends to consist of older women! Prioritize influencers you can actually get in touch with: either via warm intro or because they have their business email readily available. Golden rule: avoid their agent at all costs! Agents care about one thing only, money upfront. Have An “In” — If you’re a startup founder, you likely don’t have the budget to be shoveling out loads of cash on influencer marketing campaigns. Instead, you could try contacting someone in the influencer’s orbit first: someone in their “entourage.” If you can convince them of a quality product, they’ll likely be willing to warm intro you to the influencer at that point. — You can reach out to marketing agencies such as or as these agencies are likely to have connections to influencers. Keep in mind, these agencies will likely require a fee for their services. But they might be affordable to you. If you’re really struggling to find an “in” small Homeplate Courtside It’s important to identify which creators you’d most like to work with because your passion for their brand will come off in the pitch. Don’t discount passion — your Step 2: The Pitch It’s time to reach out and pitch influencers you’ve identified. Influencer partnerships are . That is to say your reputation matters. Influencers only work with people they trust. Here are some items that can help give you credibility when you initially reach out: relationship based A strong portfolio of past products you’ve created that have good reviews. An active community — even if it’s small — of existing & happy users. Strong concept art of the future product — the more personalized to the influencer the better. A mutual acquaintance that can speak to your talents. A strong “why” or mission to illuminate why you’re doing what you’re doing. For instance, my initial text to Donovan read: Hey Donovan! I own a game studio called AppStop.io — we make sports games starring pro athletes. Our last moible game “QB Chase” starred Chase Winovich and is rated 4.9 stars on the iOS store. I’d love to build you a mobile game, completely free of charge. Curious if you have 30 minutes to discuss details next week? Full disclosure, I did have a warm intro to Donovan, but if I didn’t, I don’t believe I would’ve changed much about the initial text. I would’ve only included concept art in the initial message to grab attention, make the pitch more exciting, and make the pitch more personalized. In our next meeting, I showed off a short slide deck highlighting my game studio, what I envisioned for Donovan’s game, how AppStop.io partners with philanthropies to donate money (this turned out to be critical), and concept art for how the game would look with Donovan in it. A few pro tips to keep in mind when entering the final pitch: What is your product? What makes your product the next big thing? What is your “ask” for the influencer? Keep it lean. Keep it Short — There’s a common misconception that influencers only care about money. In my experience, influencers do care about money but what they care even more about is . Content is King — (IMPORTANT): content If you can convince the influencer that your product will inspire content that will thrill their community and that your company can actually that content on the influencer’s behalf, then they’re very likely to want to do business with you — perhaps even for free. create This could be a giveaway, custom digital art, or a cool video or Tik Tok. In our case, we let Donovan know that we would create Instagram content on his behalf and that this Instagram content would perform great (more on this in step 3) You don’t always need to pay the influencer an This is especially true if your product is remarkable, your intro is particularly warm, and the marketing activation is very easy for them to implement. Do You Need to Pay? — upfront guarantee. You need to offer them such as revenue share, content creation services, or philanthropic donations. do something Smaller influencers may also be fine with accepting an upfront guarantee as small as ~$500 simply so they can develop their own portfolio of successful marketing campaigns for when larger businesses reach out. If you reach out to 100 influencers cold and even three respond, then that’s a huge success. Influencers are flooded with entrepreneurs such as yourself (now more than ever), and they can’t get to every pitch. Have Thick Skin — Have patience, and don’t take rejection personally. Every influencer you work with gives you more credibility. The first deal is the hardest. After the pitch is over, be sure to sign a licensing agreement with the influencer(s) so that you have the ability to use their Name, Image, and Likeness (NIL) in app and on promotional content. Even though it’s a hassle, it’s important to sign these contracts so that each party is committed to following through on their end of the deal. Chapter 3: Implementing the Influencer Marketing Campaign The first thing to note is that the influencer’s fans are not the end all be all of your app’s users. Ideally speaking, you should think of influencers as a that can increase two important stats: marketing catalyst Get your app on the top charts of various AppStores — thereby increasing “ **growth” (**i.e., users naturally finding you online) organic Provide a solid foundation of users that will naturally share the app with their friends. Often, this is called the “ K-Factor.” The right marketing strategy should always have your organic growth and K-Factor be the primary source of users. For instance, our game, Deep Pass Jam, grew 213% from users naturally finding us on the top iOS charts. That means that all the marketing we did with the influencer accounted for less than half of our final total users! But, we still needed the influencer as a catalyst to get onto the top 100 charts to reap those benefits. The next thing to keep in mind is content delivery. Sometimes the influencers will want to create the content for the marketing campaign. Often, they will want you to create the content and then they will approve the content with edits. It is very critical to express is responsible for creating content and you plan to have the influencer post it. If you don’t express this in plain language, it will not be posted, or worse; the content could be posted incorrectly — having catastrophic consequences. who what when In our case, we expressed to Donovan that AppStop.io would be creating the content. We had a trick up our sleeve. We knew semi-realistic video game content performs on social media. unbelievably well It’s jarring and fun for the viewer to see the digital version of your favorite character inside a video game. This type of content increased Kim Kardashian, Connor McGregor, and Gordon Ramsay’s social media engagement. So, we had our animators get to work. In the end, Donovan got to relax for a week while his Instagram engagement increased a tremendous 300% because of the content we created on his behalf: https://www.instagram.com/p/CZU0aFQJfI_/?embedable=true Regardless, a few tips and tricks with any content you plan to have the influencer post: Ensure there’s an easy off-ramp from the content to have consumers download your app Include a Call-To-Action — The best social media content is content that can provide value to the viewer. Make the viewer laugh, give them valuable information, and show them something emotional. It’s important to study other apps’ high-performing content to see what worked for them and copy that format! Provide Value — Influencers often have strong ties to other influencers with followings. Make it easy for them to engage and re-share the content by having the art be high-quality, tying the product to a larger mission (possibly a philanthropic partnership), and highlighting ownership of the original influencer. Create a Network Effect — Balance the Influencer’s Presence —While having the influencer star in promotional content and in-app can help drive traffic from fans who know the influencer, it can also be off-putting to those who aren’t familiar with the influencer. That’s why it’s important for the influencer to have a “muted” presence. They shouldn’t be plastered on the front page of every piece of content, but they should be visible in of the content. some In addition to posting content, it’s important to know the data behind what you’re posting. Have a plan on exactly how many downloads you hope to gain from the influencer’s promotion. Stats matter because they can help advise content strategy. Here are some of the most important statistics every startup founder should know about the AppStore: Of course, these numbers can vary from day to day. According to Tech Crunch, it requires roughly 8,000 downloads in a 24-hour period to get on the U.S. top 100 iOS free games list. 26,000 downloads to get into the top 10. Business apps are double those numbers. 16,000 for the top 100 and 52,000 for the top 10 of any business category. Know what your genre’s average conversion rate is. If your app’s conversion rate is below average that means that you are missing out on important organic growth and need to improve your AppStore’s promotional content. Certain app genres have different AppStore conversion rates. Sometimes this process is called “AppStore Optimization” or “ASO.” The most important promotional content is the photo previews of your app. Ensure these are very high quality prior to launching an influencer campaign. In conclusion, influencer marketing can be a powerful tool for bootstrapped startups looking to scale their apps. By partnering with influential individuals within their target market, startups can tap into their existing audience and gain valuable exposure for their apps. This can help drive downloads and increase user engagement, ultimately helping the startup to grow and succeed. To get started with influencer marketing, startups should identify potential influencers within their target market, offer them incentives to promote their app, and track the results to see if the strategy is effective. By implementing influencer marketing as part of their growth strategy, bootstrapped startups can take their app to new heights.

How A Solopreneur Used Influencer Marketing to Reach the iOS Top 100 List

Cómo un solopreneur usó el marketing de influencers para llegar a la lista de los 100 principales de iOS

Comment un solopreneur a utilisé le marketing d'influence pour atteindre la liste des 100 meilleurs iOS

कैसे एक सोलोप्रेन्योर ने इन्फ्लुएंसर मार्केटिंग का उपयोग करके iOS शीर्ष 100 सूची तक पहुँचाया

個人事業主がインフルエンサー マーケティングを使用して iOS のトップ 100 リストに到達した方法

Como um empreendedor solo usou o marketing de influenciadores para alcançar a lista dos 100 melhores do iOS

Cách một Solopreneur sử dụng Tiếp thị người ảnh hưởng để lọt vào Danh sách 100 iOS hàng đầu

Solopreneur 如何利用影响者营销进入 iOS 前 100 名

👋 HEY, so my goal in this article is to reply to some important questions that usually beginners have with Flutter. Should you learn Flutter? Should you use it or not? When should you use it? not I’m a web developer with more than 5 years' experience, and I learned Flutter so I can develop applications for multiple platforms at the same time, BUT... I still make websites with Javascript, Node, HTML, etc. In this article, I’ll give you my personal experience. 😀 Prefer to Watch the Video Instead? Let’s talk about Flutter since it’s a technology that is getting more popular every day. Should you learn Flutter? When and Why? Multiple Platforms If you want to learn a technology that allows you to develop on multiple platforms at the same time then this is for you.nFlutter allows you to develop with the same codebase on multiple platforms, ! even the Web You can develop applications for Android, IOS, TVs, Web, Windows, Linux. And upcoming also for Fuscia! As you can see it works with all known technologies of today, using it will allow you to write with the same code and ship it for multiple platforms, which is a HUGE benefit in my opinion! Waste Less Time If you want to make any change you will not lose time having to build your application but you can see it changed in the same second you save with the . hot reload feature The most beautiful thing is that you will not even lose the state; so if you are working on the styling of a button after a popup opens you don’t have to reload every time to see the changes! I have also to add that since you develop for multiple platforms you will have more time free so you can chill out more... Just kidding, programmers never chill out, but maybe you'll have more time learning new technologies 😉 Flutter is FAST I’m not only referring to the fact that Flutter runs really fast and smoothly (I have tried it and I was impressed how it works soo good 🤯), I’m also referring to the fact that with it the development process is really fast compared to all my previous experiences! even in older devices(!) How Does it Feel to Work With? Sooo… Working with it is really enjoyable I have always worked with Web technologies like Js, Node, Sass and all this cool stuff, but Flutter was so cool to work with; probably for its different approach with all those widgets. But… Here is When and Why You Shouldn’t Learn Flutter In my opinion, you shouldn’t use Flutter if you want to create something that requires a deep dive into the device stuff. If you need to do that, it is better if you go with the native language, you'll have more open access to the device, or you can create your own packages that do your wanted feature. Since Flutter works with packages that means that you have to use a package that someone wrote in the native language, or you can write it yourself. But these are only rare cases, because for the majority of people you can absolutely work with Flutter without any problem. For example, for websites, I still use Node, JS, HTML, and CSS because I’m obsessed with SEO, so if you're like me and want a perfect performing SEO website and you want to stay in control at the minimum level you can manage fine with Flutter. Flutter is Backed and Used by Google Since Flutter is used by Google that means that they rely on it and it will not become an abandoned project, and even the community responded in a positive way. It is used even in the Fuchsia project, which means that Google will always push it and try to improve it! Yes That's it! Thanks for reading, let me know what I should improve about my writing or share your opinion about what I have said! In this way we can learn together. 👋🔥🔥🔥 Previously published here .

My Case for Why You Should Learn Flutter in 2021

Global financial markets are tumbling again as market sell-off accelerates due to fears of lockdowns occurring again in parts of Europe. As the hopes of a faster economic recovery die down, the situation for small and medium enterprises and individuals is becoming bleaker day by day due to a fall in demand and no hopes for a fiscal stimulus from the government. With a dip in the business activity, individuals must hedge themselves against various financial and budgetary risks that are arising in the market today. I sat down with Jon Squires, CEO of Currency.com; a CIS regulated exchange for trading tokenized stocks, indices, commodities, and FX pairs with fiat or crypto to talk about global financial markets, technology, and how investors should hedge themselves against the market downside. Ishan Pandey: Why is the sell-off in stocks, indices, and cryptocurrencies intensifying globally? Jon Squires: The pandemic-driven recession is turning out to be a huge obstacle, much more significant than what financial analysts predicted. The global markets were rallying after a massive sell-off in February based on hopes of recovery and an increase in demand after lockdowns are lifted. But, what we see right now is that the demand in the consumer market has more or less decreased and in some sectors has completely collapsed. There are various reasons for this; for example, the increase in unemployment has created a demand shock in the consumer markets. Individuals who are getting jobs again are spending less and saving more. This is a global trend, as now people are living on the principles of minimalism, not because they want but because of pay cuts, decrease in demand, and increase in coronavirus cases are forcing individuals to protect themselves against an unpredictable future. Fiscal and monetary stimulus-induced in the economy has had its results, but we are still not sure that such stimulus has actually propped up demand in the market. More fiscal stimulus is needed and we fear that the federal reserves have used most of their corrective measures simultaneously, leaving them with very few options right now. The central banks can’t print more money now or it is going to result in inflation at levels that we have not seen before. That’s why central banks must focus on fiscal stimulus and reforms wherever needed to stabilize the market. The best option for the government would be to put money directly in the hands of consumers and households. The truth is that there is a massive gap between the “stock market” and the “real market.” Financial Institutions, Banks, Hedge Funds, Investment Banks, high net worth individuals and retail investors are disconnected from the ground reality living in a bubble. Most are working remotely from homes, expecting consumers to go out and delve into comfort shopping, and that is not happening in various sectors as predicted. This drop in retail demand in turn puts more small businesses into financial distress, leading to more redundancies. Ishan Pandey: How can investors and individuals hedge themselves against the current uncertainties in the market? Jon Squires: Right now, the aim of a private individual or a retail investor should be to save what he/she has and allocate capital in less risk and volatile markets. Gold is a good option, with bets on technology stocks as they have witnessed continued growth even during the pandemic. Investing right now is very important for individuals because if their money is kept parked in their savings account, they are losing anyway due to inflation. Retail inflation has increased by more than 3-6% globally, and this is a worrying trend for investors. Gold, Silver, and Indices are the best bet right now. What we are seeing is that even the cryptocurrencies market is directly correlated to the global financial markets. I think this is due to the same reasons that the psychology of the market is changing. Ishan Pandey: What assets, bonds, and capital market instruments should investors look at? Right now, the portfolio of investors should be focussed on creating diversified holdings with a focus on sectors such as technology, e-commerce, pharma, etc. These sectors are really doing well during the pandemic. Even tokenized bonds, shares, and tokenized assets are an excellent option for investors to hedge themselves against any risk. Currency.com offers tokenized equity and debt instruments to investors as a hedge with tight spreads and excellent liquidity. Currently, high volatility is going to exist in markets, which is an opportunity for investors to create portfolio holdings that can yield high returns in the future. As they say, billionaires are made at times of recession. There is a reason for this that during a recession, investors with cash are in an enviable position, and they can purchase assets, companies, and products at a price lower than the market price and even in various cases, at a price lower than the fair market price. This is where opportunities lie for investors, and that’s why the current market strategy should be to save what you have and invest conservatively. Jon Squires: Ishan Pandey: Can you explain what tokenized assets are and how they work in financial markets? Tokenization is a method of materializing the ownership in a financial instrument by creating a “token” executed on a distributed ledger technology ( DLT) database. Jon Squires: Tokens created by Currency.com make it possible for investors to participate in top global price volatility. Tokenized assets are tokens that equate to a single underlying asset (e.g., share of Amazon, Adobe, Netflix, cash, oil, gold, etc.). When the price of the actual commodity increases, so does the tokenized instrument. When the price of the actual asset decreases, the tokenized security matches it exactly. As such, investing in tokenized assets gives the same potential for benefit as conventional assets. For example, a Netflix.cx token indicates the success of a NFLX share on the Nasdaq. Users of tokenized asset exchanges use their cryptocurrency holdings to acquire Netflix.cx and transfer it as though they were buying Netflix’s own equity. Ofcourse, the trades are carried out with strength, transparency, and high velocity with tight spread and volume. A tokenized security is a blockchain-powered commercial, financial commodity that satisfies all the regulatory criteria of the nation in which it is regulated. The great option here is that tokenized assets allow you to exchange and benefit from the underlying market price of conventional assets with your crypto holdings. You don’t need to trade them for fiat anymore. Robust and irreversible blockchain technologies underpin the tokenized properties. Making a trade would send you a token that travels according to the price of the underlying instrument. Essentially, they allow investors to take advantage of market-wide price action without converting the crypto portfolio into a fiat. Ishan Pandey: What are your views on the US dollar? Is the dollar more powerful now as the reserve currency of the world? It is a difficult question to answer right now as we are still in a pandemic. The winner would be chosen only after the dust settles but nevertheless, what we are seeing is that from an institutional point of view, there is less incentive to hold dollars now. For example, central banks in Europe, Japan, and South-Asian Countries used to hold dollars to provide them with a very secure, risk-free, and medium yielding source as compared to the interest rates in Europe and Japan. But right now, as the interest rates in the US have decreased to the levels similar to that of Europe and Japan, there is much less incentive for banks and governments to park their money in dollars. This is a problem which the dollar is facing couple that with the problem that the Federal Reserve is printing a lot of money, which is creating excess supply in the market. But on the other hand, there is no other market instrument that government institutions and banks can rely on. China is coming up with its digital currency, but that is just too risky for European banks, Syndicates, and Japanese financial institutions to even consider. Due to the absence of alternatives, the dollar is still going to be the king. Jon Squires: Ishan Pandey: Do you think that Yuan/Renminbi would be able to overtake the dollar as the currency of the world? Jon Squires: The Republic of China is giving a tough fight to the US, but the problem is that they are basing a lot of their strategy on digitizing Yuan on the blockchain. To be a top global reserve currency and to maintain your position, these actions won’t be enough. Maintaining hegemony globally is all about economics, foreign relations, and soft power. This type of politics is something which the Chinese government doesn't prioritise with the major Western financial centres. With stressed relations at borders at all fronts, be it Japan, India, and even Russia, it is highly unlikely Yuan would overtake the dollar. Why would Vietnam hold their reserves in Yuan when China is creating problems at their border? This is what the Chinese government is missing at the moment - building economic partnerships with influential markets. It lost a major opportunity with its actions in Hong Kong. Further, the recent gold scam committed by Kingold, where fake bullion worth 20 billion yuan was pledged, and later it turned out to be gilded copper, has only cemented the beliefs of various institutional investors that dealing with China comes with various critical risks. The gold had been inspected not only by the lenders and insurers involved but also by state organisations like the Hubei provincial assay office and gem certification center of China in Wuhan. Ishan Pandey: What trends, opportunities, and challenges do you see in 2020-2021? Jon Squires: Agri-tech is going to be a trend that we are watching. Agricultural practices have long been plagued by redundancy and they are due a complete overhaul. With locust attacks in Africa, the Middle East, and in South Asia, we can see a global food shortage pending due to which modernizing agriculture at an accelerated pace is going to become very important. No one is talking about this because right now, the world is facing multiple problems all at the same time due to which some issues are being brushed under the carpet. Financial markets are also seeing an overhaul with the introduction of tokenized instruments, which provides investors with better avenues to park and invest their wealth all at one venue. More companies are using unique and sophisticated tools in their business operations, and this trend is going to be continued. The purpose of this article is to remove informational asymmetry existing today in our digital markets by performing due diligence by asking the right questions and equipping readers with better opinions to make informed decisions. The material does not constitute any investment, financial, or legal advice. Please do your research before investing in any digital assets or tokens, etc. The writer does not have any vested interest in the company. Interviewer - Ishan Pandey

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Disclaimer: This is NOT a press release by Netflix. Just my honest review of tech that helps us binge great content without hassle. — , , , , and (formerly )—are known for creating addictive products and experiences that no user wants to let go of. Similarly, , Google Maps, or Amazon are admired by their users for how they solve daily problems or add value to our lives. FAANG Facebook Amazon Apple Netflix Alphabet Google Instagram Of the FAANG and FAANG-adjacent products included in the list above, I believe for being a technological marvel. Netflix isn't (comparatively) getting as much attention as it deserves Before writing this piece, I talked to a number of my colleagues, with whom I talk about tech and latest products from time to time. But never about Netflix. Netflix sure. shows, Netflix technology? Not as much. Maybe that’s the beauty of a truly magical product - users not even realising all the magic that’s happening. But it is. magic, Fair enough though, we are used to just passively WATCHING what’s being played in front on us. Whether you're a Peaky Blinders person or more of a MindHunter fan, chances are, you don't often give much thought to how it is you’re able to stream all of your favourite shows without any hassle. In this post, I unpack the Netflix model so you know more next time you get automatically sucked in to the next episode. Let’s get started! The OTT leader - NFLX With the digitization of video content, all new and existing OTT Platforms have been focusing on the simple formula of good content + latest recommendation algorithmic technologies = exceptional user experience. Of all the OTTs currently on the market, Netflix has no chill. Netflix believes in keeping the podiums of streaming technology and content at an equal level. The reason Netflix is top-of-mind the second someone talks about streaming content platforms, is its open-ended efforts of not only making the content widely accessible to all ranges of devices, but combining that with lesser network speed and data requirements, through cutting edge technology. Take the used by Netflix for an example. In early 2018, Netflix introduced its co-developed Dynamic Optimizer powered by AI techniques, which scrutinizes each frame of a video, then re-encodes, and compresses its size by an enormous amount without deteriorating its image quality. Dynamic Optimizer This increases their appeal to the Netflix users that stream content on portable devices like smartphones and tablets as they can use Netflix without exceeding their monthly bandwidth capacity. All of this is a result of amazing tech stack used by Netflix. Let’s take a look at Netflix’s robust tech stack and get a hold on the back-end reasons for its seamless user experience. Netflix Tech Stack Even with access to loads of highly addictive content, the success of an OTT provider wouldn’t be guaranteed if not backed up by a robust tech stack. To ensure an all-round support and compatibility, the Netflix tech stack comprises many programming languages (e.g. Java, JavaScript, Python, Kotlin and Swift). and security is owed to its use of Python. Kotlin imparts much required tooling support and also comes handy with other programming languages due to its interoperable nature. Python being the part of Netflix’s arsenal, also ensures the use of Machine Learning and Artificial Intelligence for features like user personalization and data-economical encoding respectively. Netflix’s much appreciated scaling culture Netflix tech stack also consists of utterly comprehensive libraries which polish user experience and frameworks to act as a spine for the development processes. The user friendly interfaces of Netflix are promised by Reactjs, the JavaScript UI library. It uses NodeJS as a framework and WinJS to facilitate the development of its Windows application. Being a digital content platform, Netflix tech stack has to consist of a backend tools, processes and architecture that shout competence and reliability through its reputation. Reliable Backend of Netflix Before 2008, Netflix used their own data centers to track customers, maintain inventory and customer billing. When they took the shot at cloud computing due to its advantages over data centers, they went with Amazon Web Services which seemed to be the perfect fit for Netflix in terms of security, scalability, flexibility and functionality. Netflix uses reliable Amazon EC2 Servers for cloud hosting and Amazon RDS and Amazon DynamoDB for Database-as-a-service. Apart from this, Dynomite acts as a Database Cluster Manager in Netflix tech stack. It offers great advantages by supporting pluggable persistent and in-memory storage engines.There are also tools like AWS elastic Transcoder used by Netflix to format videos appropriately which saves you from buffers. Netflix uses AWS for a plethora of services through different accounts for different aspects of their business such as subscriptions, content delivery and personalized recommendations. These multiple accounts in AWS ensure autonomy amongst teams and hence result in quick addition of features and updates. Apart from this, the sophisticated Continuous Integration and Continuous Deployment (CI/CD) also ensure quick deployment. Other Backend tools include Kafka which scrutinizes user history and stores data which can be accessed to compute personalized user recommendations through algorithms like Restricted Boltzmann Machines and SVD++. Spinnaker is another tool developed at Netflix’s inventory. it is an open source program which gives the developers room for experimentation and they can make small changes, test them over a subset of users and then implemented full-fledgedly after obliterating the bugs found during those automated tests. at Netflix - Tech Stack of Netflix DevOps Netflix tech stack may have all the important components, but it would still be incomplete without devops. Netflix tech stack and techniques are thoroughly drenched in DevOps. According to Dianne Marsh, director of engineering for engineering tools at Netflix, context is very important for the developers. It helps them wrap their head around the business needs and hence increases their productivity drastically. It also promises frequent and highly-automated code releases. Netflix tech stack uses GitHub for code collaboration and version control. This ensures that different teams get a hold of their responsibilities of themselves and their work and its impacts on the wider ecosystem. Jenkins is the part of the Netflix stack for ensuring Continuous Integration. Apart from this, Apache Mesos and Sumo Logic are used for Server Management and Log Management respectively. They also use Crittercism for mobile error monitoring and Boundary and LogicMonitor for Performance monitoring. Another great DevOps practice used at Netflix is building for failures. This means that they are finding new solutions for the plentitude of problems that can cause them downtime. For this, they have a tool called ‘Chaos Monkey’. All it does is randomly selects Netflix’s production instances and disables it so that their dedicated teams can find a solution to future proof any customer impact. Innovations in Content Production Even after having such a comprehensive tech stack of Netflix being a content creation company first and then a tech company, faces hindrance in adapting new technologies due to the fact that business of content creation is very, very slow to adapt to new technology. Although this slow acclimatization of the content creation business also gives Netflix an edge over its competitors. As Netflix is looking to put another leg into original content creation, it is amalgamating technology with content production to introduce tools for the production process. Tools like contacts manager and interactive breakdown tools for scripts can come in handy to the production crews. One such app that facilitates the production process is called Move which simplifies  crew management, scheduling shoots, etc. Conclusion With an ambitious innovation team, Netflix is the perfect example of a company keeping up with the . Apart from being a Digital Content Platform, Netflix surely will emerge as a leading tech company owing to its hefty investments and support in technology and innovation which is quite evident by its open source programs. pace of technological advances

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5 Major Challenges Faced by Web Application Development Teams Today and Solutions to Solve Them Without Breaking Your Company’s IT Budget The first challenge with web application development is Monoculture. What is monoculture? Even though there seem to be different approaches when it comes to developing web applications, companies are still focused on the main fundamental idea of shipping a web application to production while accounting for the scope of project, cost and time to deliver the scope. Let’s look at the above triangle. When you increase the scope of a project, you either will need to increase the cost or project will not hit the deadline as it’ll take more time. Thanks to agile development, software development teams are familiar with this fact. But let’s look at a different perspective outside of scope, cost and time. i.e. your app’s technical performance i.e. scalability, for example. Performance i.e. how the user perceives the performance of your application. User Experience (UX) i.e. how the developer feels with the tech stack used to build the application measured in terms of developer productivity, time to production, and subjective happiness or frustration of the developers. Developer Experience (DX) The tech giants like Google, FB, AMZN, NFLX have a strong focus on application performance. Large companies have a huge amount of concurrent users so they have to navigate scalability and performance issues regularly. But they also have lots of cash in the bank and they can hire more developers to fix the app’s performance. So DX is not as important for them. But for the rest of us, it’s cost-effective to add a bigger server than add an additional head-count as a developer. User Experience (UX) is another one that’s critical. Companies love to evangelize their way of doing a thing — whether it’s design or development. 98% of the time, that’s for recruitment purposes. But it also leads to developers drinking the cool-aid and they go — “React/Vue.JS/Angular etc is the right way to go.” The problem is that most of your applications don’t have to scale to serve 1M+ concurrent users. For that kind of setup, there are different tradeoffs relevant to what big tech companies have. So in order to address the challenge of monoculture, how about we: i.e. if there’s a choice between choosing something for increasing developer productivity versus optimizing for the server, choosing developer productivity could have greater long-term gains as it directly contributes to developers being happy and willing to stick around as they enjoy working on the tech stack. - Optimize for DX first Combining this with a framework that is built-in with good UX at its core, companies can get both, DX and UX without having to worry much about scalability from the get-go as there’s always one extra node you can add to your cluster. The second challenge with web application development is Hype-Cycle. Framework of the month — Angular, React, Vue, Flutter, etc. Architecture of the year — SOA, Serverless, Microservices, etc. As engineers, we like to use bleeding-edge technology. It makes us feel powerful and in control of keeping up with time. But companies prefer stability. They want to build an app and then put it in maintenance and don’t want to have to update from Angular 1 to 2 to 3 every year. Companies prefer to have minimal efforts to keep an application running. It also makes a lot of business sense to want to use the same tech stack for the next application in order to minimize training costs. When Google builds an application, it explicitly plans to deprecate the stack at the end of 5 years. So when the time comes, they’re not refactoring or redesigning their app and prefer to start from scratch. Another thing you end up with due to Hype-Cycle is the mashup of best practices. You pick the best template engine, best REST API Framework, best CSS pre-processor and then you integrate those because they’re all best practice. And we all know how complicated web development can become due to this mindset. So what’s the solution? Using an integrated solution. Focus on . It doesn’t matter which message bus you want to use. When you use Web Components, it is agnostic of whether you’re using LitElement or Polymer 3 or React or built the interface using low-level JS/HTML stuff. Web Standards Have an i.e. a full-stack solution that comes with a front-end framework, client-server communication layer, theming solution, set of web components based on web standards. Integration Solution When you get the above open-source solution from a single vendor, you mitigate the risk of not having stability or incurring extra costs due to mash-up of different tech stack across your engineering team. An additional advantage of choosing a vendor backed open-source solution is that when things break (and trust me it will) and it’s a critical situation where your CIO is up all night and having to scream at people on the phone — you can reach out to experts who’ve built the technology you’re using and get it fixed with an SLA versus letting your developers post on SOF and hope a community member comes and saves the day. : That’s the 3rd challenge with web application development today. JavaScript Why? Because it’s doing something totally different from what it was designed for. Sir Charles Anthony Richard Hoare is a British computer scientist who calls his invention of the null reference back in 1965 as a billion-dollar mistake. But programming languages started to copy it as well and the fact that JS doesn’t have 1 kind of null references but 2 different ones, could JS be a 2b mistake? What’s happening is that — JS isn’t used for what it was designed for. Back in 1995, 1996 — when both Java and JS were relased by Sun Microsystems and Netscape respectively, the plan in collaboration was that Jave would be universal app for building complex things but there’ll be JS for building smaller scripting kind of things. Today, Java has become write once, read everywhere. But they’re also using JS as a virtual machine similar to Java byte code. They write an app in other languages and then at compile time it’s translated into JS. One of the biggest reasons for this solution is to get static type-safety. Why have static type-safe code from your client to server-side logic? When you have explicitly defined types in your code, it makes it much easier for someone who’s not familiar with that code to still know what it does. Static typing often serves as documentation. Static typing also helps to use the compiler to make better and inlining things. So, the only thing you’re actually using ends up in compiled JS. optimization like dead code elimination Type safety is business-critical when you’re building a huge Enterprise application with lots of developers coming and leaving but you want the code to be optimized for end-users. So what’s the solution? Using static typing both, in the client-side and server-side logic. For example, TypeScript in FE and Java in BE. The 4th challenge is around Client-Server Communication. Yes, project managers face their own set of communication challenges during the SDLC. But an even more critical challenge is how the client and server communicate with each other. The big challenge is that we have a process boundary. We have different things that are separate with latency between them. We have to do things in a synchronous way. We have to do an optimistic update which comes with its own set of challenges you have to solve. Latency makes it even longer. If you have infinite latency and you have an offline situation, you have to deal with problems of how to keep things in sync. How do you ensure when users return online, things are put into the database and conflicts are resolved? It also causes a language barrier. What you typically have is that you have Java or C# on the server and on the client, you have JS. There’s the alternative of using NodeJS on the server or GWT on the client that gives you Java everywhere. Different programming languages come with separate code bases so there’s the difficulty of having shared validation rules or shared constants. So you end up duplicating things or doing it in a not so optimal way. When it comes to the web, the question for communication is — do we use REST or GraphQL? Both of these are for the use-case when you have front-end team doing FE and back-end team doing BE and the interaction between them is the communication layer. REST requires you to define what the client and the server will do. GraphQL gives slightly more power to FE teams but you still have a hard boundary between the client and the server Communication is difficult enough without having to add this encapsulation layer. So what’s the solution? Transparent communication from encapsulation between front-end and back-end. What if the front-end team is also doing server-side part of the communication which has a thin layer that talks to the business logic. In doing this way, you separate 2 complex things — encapsulation and overall communication challenge and helps to do things in a smoother way. By tightly coupling your FE and BE in your client-server communication layer, it lets you avoid all those problems like not being able to share constants and shared validation rules, etc. Mobile: The last of the major challenges with web application development today. In theory, you should just do mobile-first and everything will be awesome. Why? In many cases, you still need to do native apps. Because mobile-first web app won’t be good enough What you end with is multiple clients with different codebases — Web for Desktop iOS for iPhone Android 3 separate code bases (i.e. web, iOS, Android) also add up the development costs. What you want is a single code base so that you change things once when there’s a business requirement or when you have to fix bugs. Another challenge with mobile-first app development is how to deal with offline functionalities. In addition to the synchronization of data problem, you have the additional problem of how to cache static asset so that your app can be truly offline. So what’s the solution? Progressive Web Applications (PWA). Maybe it’s still a buzzword today. But the reason it will stick is that it’s the 3rd iteration by Google. Based on Google’s record, the 1st and 2nd time they build something, it’s not really good because they’re themselves learning what to keep in mind but the 3rd time is often a home run. Google’s 1st iteration with mobile app development was the same as everybody else does i.e. separate web, ios, and Android clients. Their 2nd iteration was — do as much as possible in Java. Android clients natively running java and web client using GWT to compile Java into JS. Google has a similar solution for compiling Java into iOS clients. Much of the client-side logic can be implemented in the same codebase. But they’d be doing UI in respective native tech for each stack. Google’s 3rd iteration is PWA. The Big Idea — Turn the problem upside down. What if we don’t need a native client by making the web browser strong that makes it easier to deal with caching of the static asset. So there you have it. The above are the 5 challenges based on our experience here at Vaadin helping companies with their business web application development needs and how we’re navigating it. Whether you’re a web app developer, architect, or engineering leader responsible for ensuring the business goals are met when selecting the tech stack for your team, what is your #1 single biggest challenge when it comes to building business web applications based on your current team dynamics? Share your thoughts below in comments.

How To Make The Web Great Again

Foreword: My intent for this article is to review recent events in the crypto market, starting with two data points that we encountered in the past week, and then reviewing the past year to understand what began and ended 2017’s parabolic bull run. We’ll then look at what happened to the last wave of crypto speculators, and who — if anyone — will replace them. Lastly, and most importantly, we’ll seek to understand what will need to happen before they enter. ======================================== Two events came to our attention this past week — one that we judge to be very good/bullish, and one that is most assuredly not. Let’s get the bad news out of the way first. First, the Bad News Barring an unexpected and unlikely move, this week is going to mark an occasion that has only two precedents over the past six years, and has not happened since November 2015. Unfortunately, you’re going to have to keep the champagne locked up in the cellar for now as this will be an event we would all just as soon forget. Why? A Halloween horror show, indeed. Assuming that its price remains in the current range, then on November 1st 2018, for the first time in three years, Bitcoin’s 12-month trailing return will move from positive into negative territory. I’ll follow that up with this little gem of a table. I don’t think there’s a better way to illustrate the wild ride that has been crypto for the past five years, than this: As you can see, anyone who bought their first in January 2013 had a very merry Christmas that year. Conversely, those who entered the market in January 2014 ended the year with a big lump of coal (or a lump of something else entirely) in their stockings. Bitcoin You may ask, why am I bringing this up? It’s not because I enjoy dwelling on the negatives. After all, my parents always encouraged me to seek out the positives in any setbacks or disappointments. Maybe that’s because I was raised in the upper Midwest, where the weather is consistently terrible. Nonetheless, the fact remains that we arrived at this milestone amidst a remarkably stagnant period. I didn’t start actively trading crypto because I expected it to be boring. Quite the contrary. After all, one of my favorite crypto quotes comes from Arthur Hayes, founder of BitMex, who recently argued that . Yet, as the charts below demonstrate, here we are. “for crypto, a decline in volume and volatility is deadlier than white wine and painkillers” In fact, Bitcoin’s annualized volatility is now below or on par with that of many of the largest US tech stocks, including Apple (AAPL) and Netflix (NFLX). Source: Kosmos Research, Coinbase, NASDAQ Not surprisingly, this has coincided with: (1) Bitcoin trading in an ever-narrower range over recent months. In fact, when I last checked the price an hour ago, the 24-hour change was precisely 0.0%. We try not to stare at the ticker all day, but that was a first for me. (2) Exchange-traded volumes are falling off a cliff. To take BTC as but one example, see below a table showing the lowest 10 daily volumes of 2018: Yes, you are reading the table correctly: four of the ten slowest days year-to-date occurred last week and nine of the ten came this month. To put this in perspective, over US$ 11 billion traded on January 1 of this year. Great — so the market is stuck in an almighty rut. How does that help us as investors? Hold that thought for a moment. First, let me tell you about a conversation that we had last week that brightened our mood considerably. Now, The Good News Amidst all the crypto doom and gloom (but definitely no boom, sorry Marc Faber) my partner recently caught up with one of his friends, a macro hedge fund manager based in London. The crypto market loves to obsess over when that “institutional wall of money” is going to arrive. Well, this guy is an integral part of that wall. So we’re always interested in hearing his thoughts on crypto, to the extent that he has any. After all, like most macro fund managers he doesn’t have much time for an asset class where the capitalization isn’t measured in trillions of dollars. As recently as the fall of 2017 he had admitted to knowing ‘next to nothing’ about crypto, and lacked the bandwidth or incentives to spend time learning more. But this time the conversation went differently. He told us that he has begun reading up on the space and had questions. And if he is working his way up the learning curve, we strongly suspect that he is not alone. Our friend is not the type to waste time or energy on a topic unless he has identified a compelling opportunity. To us, more than anything we have read on Crypto Twitter, this was a bullish market signal. Most importantly, we found it interesting that this conversation took place just as Bitcoin’s one-year trailing return was about to descend into negative territory. However it’s important to consider these two data points — one good, the other not so much — in the context of what has transpired in the past year. Let’s briefly recap what happened to the crypto market in 2017, and why. Past Is (Not) Prologue Like most greed-driven bubbles, Bitcoin’s historic 2017 move started slowly. BTC traded at less than $1,000 on January 1st, and was worth only a few dollars more at the end of March. But something happened in the second quarter — by the end of June BTC’s value had increased by over 250%. Three months later, it had doubled in value again. And December, of course, is when the frenzy went into full swing. Prices doubled in less than three weeks, and nearly touched $20,000 before finally collapsing. Now, some might argue that initial coin offerings (ICOs) are what sparked the market frenzy. To an extent, we agree with this position. After all, the ICO mania is what initially shone the spotlight on crypto and forced the mainstream investing public to take notice. Looking more closely though, we would argue that a more consequential trend emerged in the second half of 2017. Rumors of — and seeming steps toward — institutional market entry were what ultimately drove Bitcoin into its parabolic end-game. An Annotated (Recent) History of Bitcoin Source: Coinbase/Coinigy Simultaneously, announcements of Bitcoin futures contracts, paired with headlines regarding Wall Street interest and breathless predictions of imminent change, conspired to fuel a self-fulfilling narrative of ever-higher asset prices. CNBC, December 2017. Boo-yah! The hysteria peaked on December 18th, 2017. Bitcoin had just hit an all-time high of $19,783 on Coinbase the day before. Two weeks earlier the Chicago futures exchanges, CME and CBOE, had announced launch dates for their Bitcoin futures contracts. Predictably, the cryptoasset market went ballistic as new entrants flooded in ahead of the ‘wall of institutional capital’ that was widely rumored to be imminent and was going to propel Bitcoin to new heights. The price of Bitcoin doubled in the first two weeks of that month. CBOE futures debuted on December 10th and traded 19% higher on their first day. Trading was halted twice due to exchange ‘circuit breaker’ rules. The market continued to buy, waiting with bated breath for the CME launch a week later. The CME contract opened to much fanfare, and then…traded 2% lower. It was the embodiment of failed expectations. . And this was only the beginning of the pain. The institutional money never arrived in earnest and did not drive this bubble In short, 2017 was almost exclusively a retail-driven train, and the late-arriving punters got crushed in the derailment. The institutional capital has not yet joined the party. Where Is The Proverbial ‘Wall of Money’? Go to any crypto meetup or convention today and the same question will be asked. It will be repeated like a mantra — in the panels, during the keynote, and in the furtive conversations backstage: “When are the institutions coming in???” We’re like teenagers waiting by the phone, staring at it like Luke Skywalker stared at that X-Wing Fighter on Dagobah…just it to ring. willing Come on, Blackrock, show us some love! There are an abundance of different but credible theories to explain what might push Bitcoin below the well-defended price floor of 5,800 that has been maintained since late June. On the other hand, the smart people we talk to in the space as well as the “crypto media” are fairly unanimous in their view that the next bull run will be driven by widespread institutional adoption — the “wall of money” — that in most permutations of this vision arrives on the back of a long-awaited Bitcoin ETF. While we love being contrarians, on this point we wholeheartedly concur. For your average long-term retail HODLer, the initial reaction to this question is likely an eye-roll. Why? For a concrete example, take a guess at the dates when these headlines were published. The first article, from the Financial Times, was written on 12 August 2018. The WSJ story was published a little over a year ago. You see, we’ve been here before and we’re still waiting for the institutions to arrive. We all know what the reaction was to the Journal article — see chart above. And how did the market respond to the more recent FT piece? Source: Coinbase/Coinigy Ironically, the conviction that institutional capital is the rocket fuel needed to ignite another crypto moonshot is, if anything, stronger now than last year. So why did the possibility of institutional entry drive such mania in 2017, and why has it failed to move the needle this year? Really it all comes back to the specific inquiry we received from our friendly British hedge fund mogul: “who is buying Bitcoin here and now?” The Importance of Market Psychology Some of the smartest people I have ever met are working day and night to develop effective valuation approaches for cryptoassets. This is a monumental task, since crypto is unlike any other asset in human history. Market capitalization (sorry, CoinMarketCap) is generally useless. Certain equations that we learned in Economics 101, such as MV=PQ, are better but also have their limitations. So crypto doesn’t yet have a universally accepted valuation metric. But we do have quite a few proxies. One of them is the measurement of how many active users are in a blockchain’s ecosystem at a given point in time. We refer to this as Daily Active Addresses (DAAs), which records the number of Bitcoin (or other token) wallets that engaged in transactions on a given day. DAAs are easy to track on the Bitcoin . blockchain Source: Coinmetrics.io Take a hard look at this chart. Let it sink in. The number of active wallets is — literally — half of what it was just ten months ago. Now, if you’re reading this in late October 2018, you have most likely been in the crypto market for awhile. You probably enjoyed some — maybe even all — of the 2017 bull run and you’re still sitting on top of significant gains, even after this year’s drawdown. You’re in this for the long haul. But now, imagine you’re one of those poor souls who decided to join the Great Crypto Buying Frenzy of December 2017 — right at the top of that chart. Maybe you were smart and just invested a small percentage of your net worth. Or maybe you weren’t so smart, and you mortgaged your house to go ‘all-in’. If you decided to #HODL, like all of those other amateurs on Twitter, you’re staring at an unrealized loss of 61%. What do you suppose your feelings toward crypto are by now? Are you buying more? Averaging down your cost basis? Most likely not. You’re probably cursing the friend who told you to open a Coinbase account, and wondering how you will ever make that money back. And you’re definitely telling anyone who will listen to your rants that they should stay away, too. While we acknowledge this is an imperfect measure, let’s assume that each of those new December 2017 DAAs equates to one late entrant. If so, then over 600,000 people were burned in the latest crypto crash, and have left the market with their portfolio in a smoking ruin. For an asset class with a market cap below $250 billion, that is a LOT of people. And it’s going to take a lot of good news to bring them back — if ever. If anything, we believe this wallet count understates end users as many on-exchange transactions get netted before they are ever recorded on-blockchain. The damage was compounded by the fact that these people could have served as crypto ambassadors to the next tier of risk takers. That misery is now being further exacerbated in real time because, starting this week, people who bought 12 months ago — even before the last parabolic push higher — are now underwater too. In many ways this is an age-old story: an asset collapsed, people lost money and therefore are more cautious this time around. However the scale of the carnage, given the proportion of investors who have been burned, is nearly unprecedented. “ ” we were asked. The answer was immediate and obvious: . Who is buying Bitcoin here? No one The marginal retail buyer — the people who were trying to front-run “big institutional money” in Q4 2017 — do not exist. So who does that leave? The Wall of Money… yet again Are you as tired of this metaphor as we are yet? We’re not talking about Chicago high-frequency traders here, or ‘Mrs Watanabe’ in Japan. This refers to the real allocators. Pension funds. Sovereign wealth funds. Endowments. Powerhouses with asset pools that run to twelve digits, or more. These organizations are managed by inherently risk-averse people who know that investing into new and untested markets implies significant career risk. Portfolio managers rarely get fired for buying German Bunds or T-bills. Any fund managers who went long crypto in December 2017 are probably dusting off their CVs now. With no retail investors and no genuine prospect of them returning again before a big-time upside breakout that reinvigorates the FOMO on which crypto has historically thrived, it is these institutions who will have to carry the water to get things started. There is no crystal ball on my desk, and I won’t pretend to know when this will happen. The timing of this evolution depends on a host of factors that are both endogenous and exogenous to the crypto market. However, we do feel confident in saying that no other spark exists for the next crypto bull run. Are we there yet? Two conditions must be met before that spark can be lit: (1) Institutions must have the to participate in the crypto markets ability (2) Institutions must have the to participate in the crypto markets desire Here’s the irony: in 2017, the desire was certainly there. Having worked on Wall Street, I can confirm that bankers and traders were watching this market intensely, and in many cases they personally participated. But they had no ability to participate professionally because the key building blocks — qualified custodians, trusted trading counterparties, and (in some cases) leverage — were simply not there. (Remember, career risk is one of the most powerful forces in nature.) And now, less than a year later, the conditions have been reversed. Over the past ten months the crypto community has improved its infrastructure by leaps and bounds. From actual, live people answering customer queries ( to fully licensed custody solutions, this market is evolving more rapidly than ever. thanks, Coinbase! and what’s taking you so long, Binance?!?) And yet, even though institutions now have the ability to enter — desire has left the building as volatility, volumes and returns have all evaporated. It’s a sad day when Apple stock carries more vol than crypto… So where does that leave us? We’ve already established that the retail investor will not rescue the crypto market from its current plateau, and that institutional capital will eventually provide that needed boost. However, something needs to get them off the sidelines and into this asset class. And while it’s safe to say that a Bitcoin ETF certainly can help to increase market adoption, we don’t believe this is the that the crypto market really wants — or needs. deus ex machina According to the World Bank, institutional investors in developed economies currently manage over $100 trillion of assets. Think about what just fifty basis points of that capital would do to the crypto market. That capital won’t be allocated overnight — each institution needs to arrive at its own decision to do so. And in order to allocate, an institution must believe that cryptoassets have finally arrived as an asset class that is worthy of investment. But other things are happening out there, far beyond the reach of crypto exchanges. Dark clouds are forming over equity and fixed income markets, for the first time since Satoshi’s white paper was released to the world. What happens if Wall Street loses its appetite for equities or corporate debt? Where does that capital go? In the right circumstances, could Bitcoin even be considered a safe haven? I think it’s very possible, and in our next article we’ll take a close look at how that just might happen. ======================================== I work at Kosmos Capital Management , which actively trades the emergent class of digital assets. Follow me on Twitter @kvirgil ======================================== DISCLAIMER: Nothing in this column is intended as investment advice and you definitely should not interpret it as such. Don’t rely on my advice, or for that matter anyone else’s advice, when making investment decisions. Doing your own research is the key to success in any market. ========================================

As Bitcoin Hits A Major Milestone, What Happens Now?

This article is copublished with Grist. . Read on our collaborator's site This story was published in partnership with , a nonprofit media organization covering climate, justice, and solutions. You can subscribe to its weekly newsletter . Grist here New York State toward curbing the power of Big Tech when lawmakers passed the Digital Fair Repair Act, giving citizens the right to fix their phones, tablets, and computers. took a historic step For years, advocates for the “right to repair” have pushed for such legislation in statehouses nationwide. They argue that making it easier to repair gadgets not only saves consumers money but also reduces the environmental impact of manufacturing and electronic waste. Most of those bills have failed amid intense opposition from tech companies that want to dictate how and where their products are serviced. The passage of the Digital Fair Repair Act last June caught the tech industry off guard, but it had time to act before Gov. Kathy Hochul would sign it into law. Corporate lobbyists went to work, pressing Albany for exemptions and changes that would water the bill down. reportedly They were largely successful: While the bill Hochul in late December remains for the right-to-repair movement, the gives consumers and independent repair shops less access to parts and tools than the original proposal called for. (The state Senate still has to vote to adopt the revised bill, but it’s widely expected to do so.) signed a victory more corporate-friendly text The new version of the law applies only to devices built after mid-2023, so it won’t help people to fix stuff they currently own. It also exempts electronics used exclusively by businesses or the government. All those devices are likely to become electronic waste faster than they would have had Hochul, a Democrat, signed a tougher bill. And more greenhouse gases will be emitted manufacturing new devices to replace broken electronics. Draft versions of the bill, letters, and email correspondences shared with Grist by the repair advocacy organization reveal that many of the changes Hochul made to the Digital Fair Repair Act are identical to those proposed by , a trade association that includes Apple, Google, Samsung, and HP among its members. Repair.org TechNet Jake Egloff, the legislative director for Democratic New York state assemblymember and bill sponsor Patricia Fahy, confirmed the authenticity of the emails and bill drafts shared with Grist. “We had every environmental group walking supporting this bill,”  Fahy told Grist. “What hurt this bill is Big Tech was opposed to it.” That New York passed any electronics right-to-repair bill is “huge,” Repair.org executive director Gay Gordon-Byrne told Grist. But “it could have been huger” if not for tech industry interference. Reached for comment, the governor’s office sent Grist a copy of a statement that Hochul released when she signed the bill, outlining changes made to the text. Her staff declined to address questions about the potential negative impacts of those changes, or about the process behind them. For years, consumer technology companies like Apple have effectively monopolized the repair of their devices by limiting access to parts, tools, and manuals to “authorized repair partners,” which often only perform a small number of manufacturer-sanctioned fixes. Those limited services often force consumers to choose between continuing to use a broken device or obtaining a brand-new one. The that passed New York’s Senate and Assembly last spring sought to level the playing field for independent shops by requiring that companies make parts, tools, and documents available to everyone on fair and reasonable terms. version of the Digital Fair Repair Act A broad coalition of manufacturers opposed the bill in the spring, and its sponsors had to make significant compromises in order to pass it. “We made a lot of changes to get it over the finish line in the first day or two of June,” Fahy said. Those changes included explicit exclusions for everything from home appliances to police radios to farm equipment. Fahy says she was willing to omit those devices because she thought focusing on small electronics would give consumers “the biggest bang for their buck.” Data from the repair guide site iFixit shows that eight of the top 10 devices New Yorkers attempted to repair in 2020 were small consumer electronics, with cellphones and laptops topping the list. The passed the Assembly by a vote of 145 to 1, after clearing the Senate 59 to 4. Despite that overwhelming support, the tech industry was surprised by its passage, said Democratic state senator Neil Breslin, who sponsored the bill. Digital Fair Repair Act “There’s a number of people who were advocating on the parts of the [manufacturers] who really, in private chats, were not expecting it would be passed,” Breslin told Grist. At that point, the bill’s opponents approached Hochul seeking concessions. In particular, show TechNet held frequent meetings with the governor between June and December, when she signed the bill. state lobbying records Lobbyists representing Apple, Google, and Microsoft also met with the governor, state records show. All of these organizations have right-to-repair bills in other states, often citing intellectual property and cybersecurity concerns. lobbied against But some, most , have in recent years. Fahy said Microsoft “constantly tried to reach out” to her office to cooperate on the bill. notably Microsoft softened their stance In a letter sent to the governor in November, the company requested several edits but did not ask for a veto. (Microsoft, Google, and Apple declined to comment.) In letters sent to Hochul in July and August, Apple, IBM, and TechNet all asked the governor to veto the bill. (IBM also declined to comment.) When a veto didn’t immediately happen, TechNet sent Hochul a with edits attributed to , the trade organization’s vice president of state policy and government relations. trimmed-down version David Edmonson Among other things, TechNet requested that the law apply only to future products sold in the state, that it exclude products sold only through business-to-business or government contracts, and that it exclude printed circuit boards on the grounds that they could be used to counterfeit devices. It also sought a stipulation allowing manufacturers to offer consumers and independent fixers assemblies, such as a battery pre-assembled with other components, if selling individual parts could create a “safety risk.” Additionally, TechNet wanted a requirement that independent repair shops provide customers with a written notice of U.S. warranty laws before conducting repairs. Hochul’s office sent TechNet’s revised draft to repair advocates to get their reaction. Those advocates shared the TechNet-edited version of the bill with Fahy’s staff, which gave it to the Federal Trade Commission, or FTC, the agency charged with protecting American consumers. Documents that Repair.org shared with Grist show that FTC staff were highly critical of many of the changes. The parts assembly provision, one commission staffer wrote in response to TechNet’s edits, “could be easily abused by a manufacturer” to create a two-tiered system in which individual components like batteries are available only to authorized repair partners. Another of TechNet’s proposed changes—deleting a requirement that manufacturers give owners and independent shops the ability to reset security locks in order to conduct repairs—could result in a “hollow right to repair” in which security systems thwart people from fixing their stuff, the staffer wrote. “These particular TechNet edits all have a common theme—ensuring that manufacturers retain control over the market for the repair of their products,” Dan Salsburg, a chief counsel for the FTC’s Office of Technology, Research and Investigation, wrote in an email to Fahy’s office. Despite the agency’s stern warning, all of the changes described above, and numerous other edits TechNet proposed, appeared in Hochul signed—many of them verbatim. the bill Chris Gilrein, TechNet’s executive director for the Northeast, told Grist in an emailed statement that the bill the Legislature passed “presented unacceptable risks to consumer data privacy and safety,” and that his organization’s recommended changes “addressed the most egregious security issues.” Manufacturers often cite cybersecurity as a reason to restrict access to repair, an argument the FTC found “ ” to support in . scant evidence a report to Congress published in 2021 Gilrein disputed the notion that the final version of the bill favored the tech industry. “At its core, the law remains a state-mandated transfer of intellectual property that is unwarranted at a time when consumers have access to more repair options than ever before,” he said. Todd Bone, the president of , a company that maintains and repairs network and data center IT equipment for corporations and the federal government, says the law offers “nothing” to his business because of the governor’s carveout for devices sold under business-to-business or government contracts. XS International “It was very disheartening,” Bone told Grist, “to see the governor working with TechNet and not paying attention to the votes from the Congress and the Senate in the state of New York, [and] what the consumers of the state of New York wanted.” Jessa Jones, who founded iPad Rehab, an independent repair shop in Honeoye Falls, about 20 miles south of Rochester, N.Y., says the original bill included provisions that would have made it far easier for independent shops like hers to get the tools, parts, and know-how needed to make repairs. She pointed to changes that allow manufacturers to release repair tools that only work with spare parts they make while at the same time controlling how those spare parts are used, both of which were requested by TechNet. “If you keep going down this road, allowing manufacturers to force us to use their branded parts and service, where they’re allowed to tie the function of the device to their branded parts and service, that’s not repair,” Jones said. “That’s authoritarian control.” After repair advocates shared TechNet’s draft with Fahy’s office, they collaborated on a counterproposal that pushed back against many of the proposed changes. The last-minute negotiations with the governor’s office were “frustrating,” Fahy said, although she still ultimately wants to see the bill become law. Fahy hopes the New York Department of State will clarify aspects of the bill that got muddied by industry influence. The agency, which plays a role in consumer protection, will craft regulations dictating how the law will be implemented. Ultimately, Fahy says the bill will still help consumers save money and keep old devices out of landfills. And every little bit counts: In New York State alone, the U.S. Public Interest Research Group estimates that Americans discard roughly 23,600 cellphones per day. Fahy also believes the law—imperfect though it may be—will have a ripple effect beyond the state’s borders. It could give momentum to the efforts to pass similar laws in . dozens of other states Eventually, the passage of state bills could lead to a national agreement between electronics manufacturers and the independent repair community, similar to what happened after Massachusetts passed an auto right-to-repair law in 2012. in the car industry Other lawmakers agree that New York has provided a welcome starting point. “When you’re the first state, sometimes you have to pass something very small to get across the finish line,” Washington State representative , a Democrat who is sponsoring a digital in her state’s house, told Grist. Mia Gregerson right-to-repair bill New York’s Digital Fair Repair Act, Gregerson said, “gives us something to work from.” “We’re going to take that now and try to do a better piece of legislation,” Gregerson said. By of Grist Maddie Stone Also published here Photo by on @felipepelaquim Unsplash

Big Tech Rewrote the Nation’s First Cellphone Repair Law: Here's How They Did It

There was a time when businesses relied on academic education systems to hire employees for different roles. After a basic orientation, any graduate would be considered employable and fit for the relevant roles. Today, with technologies evolving every minute, you can never be sure if an employee who was hired a month ago, would possess the skills that you need for your next big project. To put it differently, you can never be sure if the academic syllabus is up-to-date enough to expect the latest skills you need for a role today. Employee Training: The Only Way to Bridge the Gap Truth is, institutions can’t update their academic curriculum as frequently as the technology and latest job requirements evolve. To remain on the top, companies, businesses, or organizations have no other option but to hire a competent talent and use employee training methodologies to instill the skills that formal education might have missed. Without an , most of the workforce would become unemployable within a few years due to evolution in the existing skill or job requirements. employee training program Besides skills, companies also need to educate their new and existing workforce on different governance, risk, and compliance metrics. Hence, every company needs a consistent learning program where they can adopt different training methods for employees to continually acquire the skills as per your changing job requirements, standards, and regulations. Employee Training is Different from Formal Education To implement a competent training program and drive excellence in employee performances, companies must obtain uncompromised engagement from the employees. Training delivery platforms promise a reliable channel to drive this engagement by collecting, measuring, analyzing the relevant metrics throughout employee training programs. A competent training delivery platform ensures that each employee gets as much value from a program tailored as per their personal competence. However, even the best of the programs can’t promise that employees would retain 100% of the training given to them at the time of joining and orientation. Hence, all your new or existing employees need regular refreshers that not only re-train the workforce but also introduce them to the latest updates in the old training modules. For example, you could create different micro-learning modules with learning resources that help your workforce deal with day-to-day jobs. You could create a general instructional workflow for all your employees, or you create personalized workflows customized according to the strengths and weaknesses of the individual employees. This is just one simple way to boost employee performances via a different training delivery method. Let’s evaluate three organized training delivery methods that you can adopt in your company or organization. 1. Training Delivery via Employee Performance Measurement Platforms Tracking training performance and delivery platform data is a good way to enhance training programs. However, as training data becomes more and more diverse, traditional data tracking methods get obsolete. That’s where you can implement a custom data-tracking mechanism and performance analytics to measure relevant aspects, such as: Rate of completion Time to complete Performance in the assessments The custom data and analytics on these aspects can help you to improve your learning assets by sorting out the less effective ones. Although a majority of training delivery technologies possess some kind of data-tracking capabilities, customized platforms display an even better experience by using real-time information with dynamic analytics. You could be using any of the following learning and training delivery technologies: A. : Traditionally, LMS solutions are responsible for hosting and delivering training materials . Such a solution allows you to in addition to basic data and user tracking capabilities. Learning Management Systems (LMS) digitally author, publish, share, and manage training materials B. : LXP is nothing but special LMS solutions generalized for . These solutions are personalized for corporations to provide a more intuitive and to the employees. Learning Experience Platforms (LXP) corporate training, learning, and development in organizations tailored learning experience C. : These are special LXP or LMS customized strictly according to the unique training requirements of an organization. It possesses a that are . Customized Learning Portals customized user-interface, access control, assessment methods, features, dashboards, and integrations unique to the training process, skill requirements, just-in-time assistance of an organization 2. Training Delivery via eLearning Platforms Most organizations rely on Learning Management Systems and learning portals as training delivery platforms. However, many fail to realize that even these platforms can be used effectively to create intuitive and unified learning experiences, spanning right from the employee onboarding to day-to-day jobs, and skill refresher crash courses. If you are using a learning portal, ensure that it supports different ways to cater to the learning requirement of different roles, teams, and departments within your organization. For instance, it must allow you to create dedicated dashboards based on different roles in the organization. This may include simple features like ways to measure learning metrics that are unique to the skills relevant to a specific job role. Besides, it’s also ideal to have advanced features such as: Role-specific learning path. Skills that are relevant to the role. Leader boards for different skillsets. Discussion boards for collaborations. Such a platform must not only track learning progress effectively but also allow trainers to analyze the effect of learning progress on employee performance. The more detailed you can get with your training data, the better you can map your training programs with employee performance. Any decent training platform should offer information on learning behaviors such as: Rate of course completion Scores in the assessments Rate of completion for each module/section/chapter/lecture As much as the data is important for analysis and reporting learning behaviors, a traditional learning portal may not be able to accommodate all the unique sets of data that you may require to generate your unique reports and analytics. That’s where you must work closely with an eLearning developer and create your own elearning platform tailored specifically to your needs. Having done that, customized platforms demand classroom or online training for employers as well. This is to train the trainers on how to use the platform with all its customized set of features, data, and analytics. 3. Creating an Entire Ecosystem of Interconnected Training Delivery Channels This is probably the most complex and comprehensive way to offer micro-personalized training to your employees. A learning ecosystem is a collection of different and relevant channels that combine to form a central hub of interconnected, unified systems. It may collectively include individual solutions for different tasks as such as: Author learning resources, Deliver learning resources, Deliver performance stats, and Deliver just-in-time job assistance to the right employee at the right time. Such ecosystems are not just eLearning portals but overall employee development platforms formed by an interconnected web of all the portals, tools, channels, and resources that facilitate personalized learning and support employees in their day-to-day jobs. The collected in a central hub can be used for devising personalized learning paths and pushing micro-modules just apt for the unique learning and task requirements of an employee. For example, a central hub that interconnects your LMS, career development platform, resource tools, knowledge base, and compliance guidelines of your company. How to Use Personalized Learning in Your Employee Training Strategy? Once you have a platform to deliver a personalized learning experience, tailor courses with navigations designed for individual needs. No one likes to waste their time going navigating through something they already know. An intuitive personalized learning path delivers the right learning materials to the right learner at the right time. As you work towards devising a competent employee training program for your company, remember that data about individual learners is important for engagement and performance improvements in your employees. Missing on these aspects will only produce poor results; fewer employees would be interested in training, and even lesser employees getting any kind of positive results such as a boost in the overall productivity.

Increase Employee Performance with Dedicated Training Programs

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?

The Noonification: How Atoms Fixed Flux (6/5/2023)

introduced the atomic model to the world. Its new powers came at the cost of a steep learning curve and sparse learning resources. Recoil React and later simplified various aspects of this new model, offering many new features and pushing the limits of this amazing new paradigm. Jotai Zedux Other articles will focus on the differences between these tools. This article will focus on one big feature that all 3 have in common: They fixed Flux. Table of Contents Flux Dependency Trees The Singleton Model Back to Basics The Law of Demeter The Heroes Zedux The Atomic Model Conclusion Flux If you don't know Flux, here's a quick gist: Besides , all Flux-based libraries basically followed this pattern: An app has multiple stores. There is only one Dispatcher whose job is to feed actions to all the stores in proper order. This "proper order" means dynamically sorting out dependencies between the stores. Redux For example, take an e-commerce app setup: When the user moves, say, a banana to their cart, the PromosStore needs to wait for CartStore's state to update before sending off a request to see if there's an available banana coupon. Or perhaps bananas can't ship to the user's area. The CartStore needs to check the UserStore before updating. Or perhaps coupons can only be used once a week. The PromosStore needs to check the UserStore before sending the coupon request. Flux doesn't like these dependencies. From the : legacy React docs The objects within a Flux application are highly decoupled, and adhere very strongly to the , the principle that each object within a system should know as little as possible about the other objects in the system. Law of Demeter The theory behind this is solid. 100%. Soo ... why did this multi-store flavor of Flux die? Dependency Trees Well turns out, dependencies between isolated state containers are inevitable. In fact, to keep code modular and DRY, you be using other stores frequently. should In Flux, these dependencies are created on-the-fly: // This example uses Facebook's own `flux` library
PromosStore.dispatchToken = dispatcher.register(payload => {
  if (payload.actionType === 'add-to-cart') {
    // wait for CartStore to update first:
    dispatcher.waitFor([CartStore.dispatchToken])

    // now send the request
    sendPromosRequest(UserStore.userId, CartStore.items).then(promos => {
      dispatcher.dispatch({ actionType: 'promos-fetched', promos })
    })
  }

  if (payload.actionType === 'promos-fetched') {
    PromosStore.setPromos(payload.promos)
  }
})

CartStore.dispatchToken = dispatcher.register(payload => {
  if (payload.actionType === 'add-to-cart') {
    // wait for UserStore to update first:
    dispatcher.waitFor([UserStore.dispatchToken])

    if (UserStore.canBuy(payload.item)) {
      CartStore.addItem(payload.item)
    }
  }
}) This example shows how dependencies aren't directly declared between stores - rather, they're pieced together on a per-action basis. These informal dependencies require digging through implementation code to find. This is a very simple example! But you can already see how helter-skelter Flux feels. Side effects, selection operations, and state updates are all cobbled together. This colocation can actually be kind of nice. But mix in some informal dependencies, triple the recipe, and serve it on some boilerplate and you'll see Flux break down quickly. Other Flux implementations like and improved the boilerplate and debugging experience. While very usable, dependency management was the one nagging problem that plagued all Flux implementations. Using another store felt ugly. Deeply-nested dependency trees were hard to follow. Flummox Reflux This e-commerce app could someday have stores for OrderHistory, ShippingCalculator, DeliveryEstimate, BananasHoarded, etc. A large app could easily have hundreds of stores. How do you keep dependencies up-to-date in every store? How do you track side effects? What about purity? What about debugging? Are bananas really a berry? As for the programming principles introduced by Flux, unidirectional data flow was a winner, but, for now, the Law of Demeter was not. The Singleton Model We all know how came roaring in to save the day. It ditched the concept of multiple stores in favor of a singleton model. Now everything can access everything else without any "dependencies" at all. Redux Reducers are pure, so all logic dealing with multiple state slices go outside the store. The community made standards for managing side effects and derived state. Redux stores are beautifully debuggable. The only major Flux Flaw that Redux originally failed to fix was its boilerplate. must later simplified Redux's infamous boilerplate. Then removed some fluff at the cost of some debugging power. All of these tools have become extremely popular in the React world. RTK Zustand With modular state, dependency trees grow so naturally complex that the best solution we could think of was, "Just don't do it I guess." And it worked! This new singleton approach still works well enough for most apps. The Flux principles were so solid that simply removing the dependency nightmare fixed it. Or did it? Back to Basics The success of the singleton approach begs the question, what was Flux getting at in the first place? Why did we ever want multiple stores? Allow me to shed some light on this. Reason #1: Autonomy With multiple stores, pieces of state are broken out into their own autonomous, modular containers. These stores can be tested in isolation. They can also be shared easily between apps and packages. Reason #2: Code Splitting These autonomous stores can be split into separate code chunks. In a browser, they can be lazy-loaded and plugged in on the fly. Redux's reducers are fairly easy to code-split too. Thanks to , the only extra step is to create the new combined reducer. However, more steps may be required when side effects and middleware are involved. replaceReducer Reason #3: Standardized Primitives With the singleton model, it's difficult to know how to integrate an external module's internal state with your own. The Redux community introduced the Ducks pattern as an attempt to solve this. And it works, at the cost of a little boilerplate. With multiple stores, an external module can simply expose a store. For example, a form library can export a FormStore. The advantage of this is that the standard is "official", meaning people are less likely to create their own methodologies. This leads to a more robust, unified community and package ecosystem. Reason #4: Scalability The singleton model is surprisingly performant. Redux has proven that. However, its selection model especially has a hard upper limit. I wrote some thoughts on this in . A big, expensive selector tree can really start to drag, even when taking maximum control over caching. this Reselect discussion On the other hand, with multiple stores, most state updates are isolated to a small portion of the state tree. They don't touch anything else in the system. This is scalable far beyond the singleton approach - in fact, with multiple stores, it's very difficult to hit CPU limitations before hitting memory limitations on the user's machine. Reason #5: Destruction Destroying state is not too difficult in Redux. Just like in the code-splitting example, it requires only a few extra steps to remove a part of the reducer hierarchy. But it's still simpler with multiple stores - in theory, you can simply detach the store from the dispatcher and allow it to be garbage collected. Reason #6: Colocation This is the big one that Redux, Zustand, and the singleton model in general do not handle well. Side effects are separated from the state they interact with. Selection logic is separated from everything. While multi-store Flux was perhaps colocated, Redux went to the opposite extreme. too With multiple autonomous stores, these things naturally go together. Really, Flux only lacked a few standards to prevent everything from becoming a helter-skelter hodge-podge of gobbledygook (sorry). Reasons Summary Now, if you know the OG Flux library, you know that it actually wasn't great at all of these. The dispatcher still takes a global approach - dispatching every action to every store. The whole thing with informal/implicit dependencies also made code splitting and destruction less than perfect. Still, Flux had a lot of cool features going for it. Plus the multiple-store approach has potential for even more features like Inversion of Control and fractal (aka local) state management. Flux might have evolved into a truly powerful state manager if somebody hadn't named their goddess Demeter. I'm serious! ... Ok, I'm not. But now that you mention it, maybe Demeter's law deserves a closer look: The Law of Demeter What exactly is this so-called "law"? From : Wikipedia Each unit should have only limited knowledge about other units: only units "closely" related to the current unit. Each unit should only talk to its friends; don't talk to strangers. This law was designed with Object-Oriented Programming in mind, but it can be applied in many areas, including React state management. The basic idea is to prevent a store from: Tightly coupling itself to another store's implementation details. Using stores . that it doesn't need to know about Using any other store without declaring a dependency on that store. explicitly In banana terms, a banana shouldn't peel another banana and shouldn't talk to a banana in another tree. However, it talk to the other tree if the two trees rig up a banana phone line first. can This encourages the separation of concerns and helps your code stay modular, DRY, and SOLID. Solid theory! So what was Flux missing? Well, inter-store dependencies are a natural part of a good, modular system. If a store needs to add another dependency, it should do that do it . Here's some of that Flux code again: and as explicitly as possible PromosStore.dispatchToken = dispatcher.register(payload => {
  if (payload.actionType === 'add-to-cart') {
    // wait for CartStore to update first:
    dispatcher.waitFor([CartStore.dispatchToken])

    // now send the request
    sendPromosRequest(UserStore.userId, CartStore.items).then(promos => {
      dispatcher.dispatch({ actionType: 'promos-fetched', promos })
    })
  }

  if (payload.actionType === 'promos-fetched') {
    PromosStore.setPromos(payload.promos)
  }
}) PromosStore has multiple dependencies declared in different ways - it waits for and reads from it reads from . The only way to discover these dependencies is to look for stores in PromosStore's implementation. CartStore and UserStore Dev tools can't help make these dependencies more discoverable either. In other words, the dependencies are too implicit. While this is a very simple and contrived example, it illustrates how Flux misinterpreted the Law of Demeter. While I'm sure it was mostly born of a desire to keep Flux implementations small (real dependency management is a complex task!), this is where Flux fell short. Unlike the heroes of this story: The Heroes In 2020, came stumbling onto the scene. While a little clumsy at first, it taught us a new pattern that revived the multiple-store approach of Flux. Recoil Unidirectional data flow moved from the store itself to the dependency graph. Stores were now called atoms. Atoms were properly autonomous and code-splittable. They had new powers like suspense support and hydration. And most importantly, atoms formally declare their dependencies. The atomic model was born. // a Recoil atom
const greetingAtom = atom({
  key: 'greeting',
  default: 'Hello, World!',
}) Recoil struggled with a bloated codebase, memory leaks, bad performance, slow development, and unstable features - most notably side effects. It would slowly iron out some of these, but in the meantime, other libraries took Recoil's ideas and ran with them. burst onto the scene and quickly gained a following. Jotai // a Jotai atom
const greetingAtom = atom('Hello, World!') Besides being a tiny fraction of Recoil's size, Jotai offered better performance, sleeker APIs, and no memory leaks due to its WeakMap-based approach. However, it came at the cost of some power - the WeakMap approach makes cache control difficult and sharing state between multiple windows or other realms almost impossible. And the lack of string keys, while sleek, makes debugging a nightmare. Most apps should add those back in, drastically tarnishing Jotai's sleekness. // a (better?) Jotai atom
const greetingAtom = atom('Hello, World!')
greetingAtom.debugLabel = 'greeting' A few honorable mentions are and . These libraries have explored more of the theory behind the atomic model and try to push its size and speed to the limit. Reatom Nanostores The atomic model is fast and scales very well. But up until very recently, there were a few concerns that no atomic library had addressed very well: The learning curve. Atoms are . How do we make these concepts approachable for React devs? different Dev X and debugging. How do we make atoms discoverable? How do you track updates or enforce good practices? Incremental migration for existing codebases. How do you access external stores? How do you keep existing logic intact? How do you avoid a full rewrite? Plugins. How do we make the atomic model extensible? it handle every possible situation? Can Dependency Injection. Atoms naturally define dependencies, but can they be swapped out during testing or in different environments? The Law of Demeter. How do we hide implementation details and prevent scattered updates? This is where I come in. See, I'm the principle creator of another atomic library: Zedux finally entered the scene a few weeks ago. Developed by a Fintech company in New York - the company I work for - Zedux was not only designed to be fast and scalable, but also to provide a sleek development and debugging experience. Zedux // a Zedux atom
const greetingAtom = atom('greeting', 'Hello, World!') I won't go into depth about Zedux's features here - as I said, this article won't focus on the differences between these atomic libraries. Suffice it to say that Zedux addresses all the above concerns. For example, it's the first atomic library to offer real Inversion of Control and the first to bring us full-circle back to the Law of Demeter by offering for hiding implementation details. atom exports The last ideologies of Flux have finally been revived - not only revived, but improved! - thanks to the atomic model. So what exactly the atomic model? is The Atomic Model These atomic libraries have many differences - they even have different definitions of what "atomic" means. The general consensus is that atoms are small, isolated, autonomous state containers reactively updated via a Directed Acyclic Graph. I know, I know, it sounds complex, but just wait till I explain it with bananas. I'm kidding! It's actually really simple: Updates ricochet through the graph. That's it! The point is, regardless of the implementation or the semantics, all of these atomic libraries have revived the concept of multiple stores and made them not only usable, but a real joy to work with. The 6 reasons I gave for wanting multiple stores are exactly the reasons why the atomic model is so powerful: Autonomy - Atoms can be tested and used completely in isolation. Code Splitting - Import an atom and use it! No extra considerations required. Standardized Primitives - Anything can expose an atom for automatic integration. Scalability - Updates affect only a small part of the state tree. Destruction - Simply stop using an atom and all its state is garbage collected. Colocation - Atoms naturally define their own state, side effects, and update logic. The simple APIs and scalability alone make atomic libraries an excellent choice for every React app. More power less boilerplate than Redux? Is this a dream? and Conclusion What a journey! The world of React state management never ceases to amaze, and I'm so glad I hitched a ride. We're just getting started. There is a lot of room for innovation with atoms. After spending years creating and using Zedux, I've seen how powerful the atomic model can be. In fact, its power is its Achilles heel: When devs explore atoms, they often dig so deep into the possibilities that they come back saying, "Look at this crazy complex power," rather than, "Look at how simply and elegantly atoms solve this problem." I'm here to change this. The atomic model and the theory behind it haven't been taught in a way that's approachable for most React devs. In a way, the React world's experience of atoms so far has been the opposite of Flux: This article is the second in a series of learning resources I'm producing to help React devs understand how atomic libraries work and why you might want to use one. Check out the first article - . Scalability: the Lost Level of React State Management It took 10 years, but the solid CS theory introduced by Flux is finally impacting React apps in a big way thanks to the atomic model. And it will continue to do so for years to come.

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