BeatBind

beatbind

With a beating heart and fearful, I knew not why

Passive Income 2.0 Making money as you sleep is the ultimate goal for many of us. Like it or not, it’s something that we have come to accept in this space we call blockchain gaming. Yes, for those of us in the business of building and development, some (like myself) insist that the focus is on gaming, and that’s a big reason why my gaming team at recently released the pre-alpha as a pure playable game without any sort of token model built in. But we also know that blockchain gamers want the benefits of blockchain-enabled models that make them part of the revenue generation – something they’ve never been able to do in the traditional gaming world easily. Cradles Throughout the years, investors have been seeking ways to earn a steady income while being actively involved with other types of businesses. Using the money that one already has to make more money by being patient for a certain amount of time became a popular way to side hustle. Whether we call it , it is a smart way to extend your wealth. investing, asset building, or asset sharing Digital innovations changed the way we live, interact and conduct business on a daily basis. Bending on new trends in the realm of digital technologies, we found a way to make the next best investment, whether actively or passively. There are so many things you could actively do with digital assets, NFTs in particular, yet NFT staking refers specifically to an NFT owner locking up their digital asset for a certain amount of time to earn passive income in the form of cryptocurrencies. The tech behind NFT staking isn’t hard to comprehend. Namely, staking per se is a crucial trait of many divergent blockchains. And we can observe many gaming projects involved in staking cryptocurrencies and NFTs. The most basic manner to earn interest in crypto was to stake coins for a predetermined lock-up period in time. It was like earning interest in the sense of traditional banking. Then, thanks in a large part to gaming Dapps, we got the opportunity to stake NFTs on compatible platforms. The genuine features of NFTs make them an ideal option for wait-and-HODL strategies even though it may take some time before such long-term investments come to their expected fruition. Such staking opens many possibilities for collectors to monetize their collections. Hence, we have that lock up their NFTs in decentralized finance platforms and even gaming platforms to receive monetary rewards with the passage of time without the need to sell or give up ownership in any other manner. Not at all dissimilar to the concept of DeFi yield farming since both are investment strategies. HODLers Profit Talks Nevertheless, NFT staking is a concept still in its infancy. The NFT craze carried most people away with headlines about sellers who earned insane amounts of money for a piece of digital art. We won’t forget easily about the who earned $400,000 by creating and selling digital pics of whales while Beeple managed to acquire $69 million in an auction for his art, turning him into one of the most financially successful living artists. 12-year-old kid At the same time incredible and borderline strange, the rate of success is proportionate to the degree of market demand and the ability to sell. Otherwise, you are just stuck with a pic. Despite the attraction of NFT staking, there are some particular drawbacks such as liquidity problems due to the infancy of the ecosystem and the practice of buying NFTs for long-term investments. At the moment, the concept is not as notorious as cryptocurrency staking, yet the forecast is somehow sunny with the predictions of ETH2’s Merge with staking taking over mining. Furthermore, most investors have been attracted to the NFT world because of the hype surrounding the concept while thinking of the solidity of its foundations and profitability calculations. NFT staking could be a good business venture following the right conditions and taking certain matters into account. As the story goes with every type of investment and earning passive income, one has to understand the system. For instance, the Annual Percentage Yield (APY) refers to the rate reflecting the rewards that may be earned over a year, based on the rewards rate of the current year. A good degree of knowledge of staking platforms and return rates helps tremendously. Furthermore, understanding price volatility and price fluctuations, with the exception of the reserve price of NFT collections, is the step that makes the difference. Let’s think of a puppy NFT locked up on a fictional platform called RisingStar and the puppy produces 5$ tokens per day, currently worth $5 on CoinMarketCap. The NFT is now earning $25 per day just from staking. Let’s assume that the puppy NFT costs you $15,000. The math goes like this: $25 per day for 365 days amounts to $9,125, and we get the APY number by dividing the cost of the NFT by $9,125. Hence, APY amounts to 61%. Not that bad, right? Only, it doesn’t always work that way when the crypto earned from staking keeps going down in value in a crypto winter, stripping away at the APY… NFT Staking and Gaming: A Whole New Level with Staking-into-NFTs So NFT staking in its original concept may be in its death throes because it’s not sustainable and cannot only hope to produce profit in a short-lived bull market. The concept may encompass a number of problems due to the infancy of the system. As it goes with everything, beginnings are always hard, but we overcome obstacles with a little help from our friends. For us, we can see how NFT staking goes hand-in-hand with blockchain-based games, if done in creative ways that are more sustainable, and more meaningful. My team love to come up with new solutions to keep you entertained, focused, and satisfied with numerous options that don’t sacrifice gameplay, yet also seek to meet the earning needs of less-active players. We know many others that want to do the same, and I’ll be the first to say I hope one of us succeeds. That’s a big part of why we made up a new tokenomics model, under which we are introducing a subscription-based game with 0% transaction fees. And for those less interested in actual gaming, but who still want to earn, we have the new Staking-into-NFT (SIN) mechanism that also involves gameplay, but passively! In this system, passive players with game tokens can aid active players by staking crypto INTO the players’ NFTs, making them more powerful. Stake crypto into Player A’s sword and it deals more damage, for example. This player is then able to perform better and earn more from gameplay. In return for the “staking boost”, rewards earned by Player A are also shared proportionately to those who staked into his sword NFT. It’s a win-win situation as both parties earn more in-game coins along with broader rewards in the game itself. Additionally, live streamers are going to be rewarded with large sums of tokens and the possibility to call on their audience to Staking-into-NFTs on their behalf, further expanding on potential growth opportunities within the game. NFT staking may be dying, but long live Staking into NFTs! *I am the founder of blockchain MMORPG Cradles, and this is my introduction. I plan to write about the industry, much more about insight, much less about my company.

Staking NFTs – A Beating Heart Among Stillness or Clinically Dead?

By now, we can hopefully all agree that producing sustainable energy from renewable sources is something humanity should strive for. Though it’s taken us way too long to get started, great leaps have been made in that direction over the last decade. However, the main energy challenge of the 21st century is not making it sustainably. That part is easy. that energy . This is where come in. As we try to “beat” climate change, they will become ever-more important by helping to move cars, trucks and the power sector away from oil, coal and natural gas. Storing is hard and expensive new and improved batteries New battery technologies take many forms, and the world has not yet decided which technology will be the winner. Below is short a primer on the most promising ones. How do batteries work? It’s impossible to understand the below without basic engineering knowledge. Electricity is produced by electrons traveling from point A to point B. This movement creates an electrical current which can then be harnessed to power everyday objects. In batteries, point A is a “negative electrode” called the anode, and point B is a “positive electrode” called a cathode. Because batteries are not directly connected to a power source, they need a way to create electrons so they can travel. This is done thanks to “electrolytes”. This substance interacts with the anode, producing electrons and ions (you need both for balance). The electrons travel and produce power, while the ions are released into the electrolyte to balance the charge at both ends of the battery. When we recharge a battery, the chemical reaction that occurred during use is reversed. Pretty simple, right? Lithium-ion Batteries is the technology used in the majority of electric cars, PCs and mobiles today. In these batteries, the anode is generally made of either (lower costs), carbon or ( ), while the cathode is typically made of a lithium-cobalt or compound. These batteries have a high , and low , which is why they’re so widespread. A lot of Lithium-ion batteries varieties exist. Lithium iron phosphate (LFP) batteries, for example, offer worse performances, but are cheaper and safer. Lithium-ion graphite silicon the supposed best option lithium-nickel energy density self-discharge Despite their benefits, most lithium-ion batteries are safety hazard as they contain . If they are damaged or incorrectly charged, this can lead to explosions and fires. They are also expensive: today, these batteries can make up a quarter to a third of the cost of electric cars. flammable electrolytes Safety and costs are not the only downside to this technology : components from batteries come from mining, which is extremely harmful to the environment. There are also sociological and political aspects to the issue. Cobalt, for example, comes from , where it is mined by or by freelancers who sometimes employ children. Lithium mining harms Argentinian and American natives. The nickel industry, meanwhile, relies heavily on Russian suppliers. . the Democratic Republic of Congo Chinese-financed companies Other options need to be explored Lithium-sulfur Batteries As the name indicates, Lithium-Sulfur batteries still use lithium, but at least do away with cobalt. They instead use sulfur to make up the batteries’ cathodes. As such, these batteries lower environmental impacts and manufacturing costs while reducing the battery’s weight and providing high energy density. In fact, Li–S batteries offer twice the amount of energy per kilogram than Li-i batteries use. For all these reasons, Lithium–sulfur (Li-S) batteries may commercially replace lithium-ion cells in the future. Metal-Air Batteries A uses an anode made from pure metal and an external cathode of ambient air. As the battery is discharging, the anode is going through oxidation (losing electrons), while oxygen is in the cathode to induce a current flow. metal–air battery reduced The specific capacity and energy density of metal–air batteries is higher than that of lithium-ion batteries, making them a prime candidate for use in electric vehicles. are the most promising metal-air batteries. They have the highest energy densities of all batteries. They are however not widely used because of high costs. They also tend to be single-use (non-rechargeable). This has restricted their use to mainly military applications. However, a car with aluminium batteries has the potential for up to eight times the range of a lithium-ion battery with a significantly lower total weigh. As such, investments in research seem to be worth it. Aluminium–air and Lithium-air batteries Sodium-Ion Batteries The ( or ) is (very) similar to the lithium-ion battery, but uses sodium ions as the charge carriers instead of lithium. sodium-ion battery NIB SIB In fact, lithium, cobalt, copper and nickel are not strictly needed to make sodium-ion batteries. As such, this type of battery has received a lot of interest over the past decade because of the uneven geographic distribution, high environmental impact and high cost of these elements (as mentioned earlier). The largest advantage of sodium-ion batteries is the high natural abundance of sodium (salt is cheap). This would make commercial production of sodium-ion batteries far less costly than lithium-ion batteries. There are however many challenges to mass adoption : these batteries have low energy density, and a limited number of . Nevertheless, they may yet have a future as lithium-ion complements for lower-quality products. charge-discharge cycles Nanowire Batteries Regardless of the chemical make-up of future batteries, a nanowire battery would increase the surface area of the electrodes in contact with the electrolyte, thereby increasing the anode’s power density and allowing for faster charging and higher delivery. Nanowires are usually made of silicon, which tends to expend and damage the battery. In 2016, however, researchers at the University of California, Irvine announced the invention of a nanowire made of capable of over 200,000 charge cycles without any breakage. The technology could lead to batteries that never need to be replaced in most applications. gold, Solid-State Batteries The batteries above use liquid electrolytes, which cannot be compressed. The Holy Grail, as such, is — batteries with solid electrolytes. They would first and foremost improve safety levels: solid electrolytes are non-flammable and will work it harsher environments, unlike their liquid counterparts. Secondly, it permits the use of (such as carbon or ), enabling denser, lighter, 3D batteries with better shelf-life. Moreover, at system level, it will bring additional advantages such as simplified mechanics as well as thermal and safety management. As the batteries can exhibit a high power-to-weight ratio, they may be ideal for use in electric vehicles. solid-state batteries new materials glass Challenges however abound, especially if mass adoption is the goal. These batteries are difficult to mass-produce, and are very expensive. This isn’t surprising, as this is the trend for all new technologies. Many of these technologies are not new at all. Lithium-ion and Lithium-sulfur batteries, in fact, were first developed in the 60s. But as our needs and manufacturing capabilities evolves, so do our interests in various battery technology. Whatever the best technology, NextGen batteries will need to be cheaply produced at a large scale, with manufacturing capacities we do not have. They will need to have a long life-span to avoid them ending in landfills after a couple of charges. They will also be dependent on the chargers we use, a technology the still needs to evolve. We’ve got our work cut out for us. Good luck out there. Also Published . Here

New Battery Technologies and the Race to Beating Climate Change

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Digital Transformation articles tell us about Amazon putting bricks-and-mortar bookstores out of business or about Netflix killing video rental stores. Big game-changing moves. But business moves can't all be game-changers. What should companies which aren't tech giants be aiming at with Digital Transformation? What businesses should aim for is to become more adaptable so that they can avoid getting outpaced by a new competitor. The point is to avoid ending up like the now departed bookstores or the video rental stores. The authors of offer a succinct definition of what the goal of adaptability looks like - they call it : The Technology Fallacy Digital Maturity “Aligning an organisation’s people, culture, structure, and tasks to compete effectively by taking advantage of opportunities enabled by technological infrastructure, both inside and outside the organisation.” Digital Transformation is, or should be, about reaching Digital Maturity. But what does Digital Maturity mean in detail? And why is it such a mammoth task that companies are spending huge sums on? How Disruption Happens: The Complacency Trap Why was Blockbuster video on the wrong side of history when Netflix came along? It’s not that Blockbuster didn’t have the opportunity to do what Netflix did. Blockbuster famously even . declined on the chance to buy Netflix (Image from .) runningremote.com Blockbuster underestimated the threat posed by video streaming. But this was more than just an isolated case of an error in judgement. It is an example of what is called . 'The Complacency Trap' Companies tend to get large because their initial idea has proven successful. They find a market of customers and need to get big order to service more of that market. Most companies try to do this efficiently and so they keep operations focused around the core product. A specialised focus on the core idea/s of the company helps it maximise the competitive advantage. But specialisation also means that alternative paths become less visible to the company. A classic Complacency Trap example is how Wal-Mart overtook Kmart to become the largest chain of low-cost retail stores. Kmart had operated on a model where stores largely sourced their own supplies and set their own prices. This was part of Kmart’s philosophy which prized the instincts of local store managers and allowed stores to be suited to their local markets. Wal-Mart radically changed this by creating linked chains of stores supplied by a shared network. That made it viable to open stores in areas of lower population density (since supply costs were shared across the network) and access new economies of scale. “Kmart saw Wal-Mart like Goliath saw David - smaller and less experienced in the big leagues. But Wal-Mart’s advantages were not inherent in its history or size. They grew out of a subtle shift in how to think about discount retailing. Tradition saw discounting as tied to urban densities, whereas Sam Walton saw a way to build efficiency by embedding each store in a network of computing and logistics. Today we call this supply-chain management, but in 1984 it was an unexpected viewpoint.” Richard Rumelt, Good Strategy / Bad Strategy Technology was certainly part of Wal-Mart’s success. But KMart could in principle have leveraged the same technology. They didn’t because KMart had become specialised towards a particular model of operating and that led them to underestimate the potential of alternative approaches. The Complacency Trap is a key dynamic in business and is played out many times over many industries. Other classic examples are or how . What is unusual about the current period in history is how much change is happening and how frequently - companies that enter the S&P 500 Index (image from ). Kodak’s underestimation of digital photography Xerox underestimated small-scale printing technology do not stay there as long as they used to peerinsight Technology is becoming more widely available and advancing more rapidly. This is creating new business situations and new players are sometimes able to disrupt established markets very quickly. So how can companies become more adaptable and give themselves a better chance of surviving in times of change? Culture, Priorities and the Complacency Trap As a company becomes specialised around a particular operating model, its whole way of working becomes tailored to that approach. It will affect the way the company hires, the kinds of skills and perspectives that it sees as important, the way the organisation’s hierarchy is structured, the culture, the executive team and who it is that has most influence over the executive team. So the company self-selects for the skills and way of thinking that it prizes. Becoming more adaptable has to mean widening perspectives. It may mean more training, bringing in more tech-savvy younger staff, hiring more wizz-kid engineers and looking at how much voice they have in the organisation. But the way in which perspectives are expanded might need a specific focus. This is because organisations (and individuals) can struggle to learn new things that they don’t have adequate background for. call this : It is not simply about fostering general creativity - the organisation needs to target the kinds of knowledge and skills it wants to grow its capabilities for. Cohen and Levinthal Absorptive Capacity Ideas in nuclear physics are unlikely to be accessible to anyone who has not first studied foundational physics. This kind of learning barrier can apply in lots of ways. Some fields of knowledge are accessible at a basic level to the uninitiated but require deep background in order to apply them in new ways. Software engineering techniques are an example - more experienced developers able to do a wider range of more creative things using techniques that less experienced developers are aware of but aren't able to use so creatively. The absorptive capacity of an organisation is not simply the sum of the knowledge of the individuals. An individual may arrive at a brilliant new insight and find themselves unable to convince others at the organisation of the insight’s value. For example, and arrived at innovations such as GUIs and the mouse (images from ): Xerox was a pioneer of early personal computer research wikipedia But Xerox shut down that line of work rather than put a focus on the computing market, missing a huge opportunity. Xerox had done some brilliant computing product R&D. But . Xerox was a printer company, not a computing company, and never aligned enough around the venture to make it a commercial success Organisations with higher absorptive capacity will be better placed to spot new opportunities as they open up. But no organisation can master every skill and domain of knowledge. Companies need to be clear about their key domains of knowledge and what kinds of spaces to be watching for opportunities. Each Company is Different Not every organisation needs to become a tech company. Specific industries have their own opportunities and threats from technological change. Across many industries a key change is that consumer expectations for commercial interactions have been reshaped by digital media and e-commerce. People have grown accustomed to seeing searchable purchasing information clearly available to them, to being able to purchase with a click and to be managing future interactions through easy to use software. Not every industry has fully caught up to these expectations yet. That presents opportunities for those who can master it and risks for those who don’t master it faster enough. In other industries there are anticipated technologies in development with great potential for change. For example, driverless technologies look set to revolutionise the car industry, . according to the Boston Consulting Group It is not yet clear exactly how or who will be the main beneficiaries. This could mean making a list of the key changes they see or anticipate, what the potential impacts of those changes are. Not every technological change can be relevant or concrete enough to justify dedicating an initiative to. Each company needs to choose which areas are most important to them and how to reorganise to be best positioned. Companies need to tailor their digital transformation priorities to their own situation. Digital Maturity If Digital Transformation is about achieving Digital Maturity, it does not have to be a process of upheaval at every company. It can be a gradual process of evolution. It may involve running small pilot projects on particular concepts before working changes into the core business model. Becoming more responsive to changes in the business environment means becoming more experimental. To avoid that trap, companies need to look at their situation, their organisational structure and culture and how they gather and respond to customer feedback. depicts the interaction of these elements in the following organisation dynamics diagram (my rendition): Having a well-planned strategy and executing on it can be highly profitable but on its own it can also lead into the complacency trap. The Technology Fallacy Culture, people and structure will be set up to facilitate work in accordance with a particular strategy. As the company learns more from its customers and as the commercial environment changes, that strategy may need to change also. If it does then this can mean changing the culture, people and structure to fit the new strategy and the new work that it entails. Change may not necessarily come all at once or in a wholesale way. And further change later might mean going through another rethink and more restructuring. Reaching digital maturity means always being on the lookout for the next cycle of change - creating room for experimentation and treating change itself as a normal part of the company’s operation. We can now better understand the definition of Digital Maturity offered at the beginning. Digital Maturity is: “Aligning an organisation’s people, culture, structure, and tasks to compete effectively by taking advantage of opportunities enabled by technological infrastructure, both inside and outside the organisation.” Kane, Copulsky et al., The Technology Fallacy Successful tech companies exhibit digital maturity. They each have a clear strategy with a core set of products and services. They also experiment and adjust to market conditions - they improve existing offerings, add new ones and retire old ones. Tech companies are able to do this faster because much of their operation is around software rather than physical structures and arrangements. The pattern is broad and the particulars are unique to a particular company’s strategy and circumstances. This is part of what makes the challenge of Digital Transformation . Each company must confront the difficult details of its situation. Digital maturity is this broad pattern of using technology to be more adaptive to opportunities and challenges. so difficult Despite the hype, there’s no copy-paste formula for success. Title Image by from . Dmitry Abramov Pixabay If you liked this you can vote for me for Hacker Noon Contributor of the Year - Project Management

Digital Transformation: Beating the Complacency Trap

Beating Amazon with Blockchain

For Entrepreneurs, Endurance is more Important than Intellect 

AI writing tools have drastically streamlined the content creation process across a wide range of fields and professions. However, the rise of AI detectors like GPTZero that work to detect AI content stands in the way of that. To make matters worse, these platforms aren’t foolproof. In other words, your content can still be falsely flagged even if you entirely wrote it yourself. This is why knowing how to bypass GPTZero is extremely vital, so let’s explore how to do that in detail. What Is GPTZero? GPTZero is an AI content detector initially launched in January 2023 by Princeton student, Edward Tian as part of his senior thesis project. Within the first week of release, it managed to successfully pull in over 30,000 active users. Since then, the company managed to raise $3.5 million in a seed round from several VC firms. This enabled its developers to further enhance the platform’s accuracy and even provide advanced capabilities like in-depth analysis reports, among other things. This made it a leading choice, especially among educators and academic institutions looking to identify students submitting AI-generated essays and papers. How To Bypass GPTZero AI Detection? While it is true that GPTZero is a powerful AI detector, the fact is that it is not unbeatable. There are several ways to go about making your AI-generated articles, essays, reports, and papers sound human-like enough to bypass GPTZero completely. Let’s explore them in detail below. Use An AI Humanizer Like BypassGPT Using an AI humanizer like BypassGPT is the most effective and easiest way to avoid GPTZero AI detection. Trained on millions of datasets of human-written texts, the advanced tool instantly rewrites AI content by mirroring authentic human-writing styles. This enables it to produce 100% undetectable output that can bypass even the most stringent AI detector including GPTZero. Best of all, BypassGPT does well to maintain content uniqueness and contextual accuracy at all times. Here are the key features and benefits of using BypassGPT: Features: Powerful AI humanization techniques that make AI content sound authentically human.
Multiple AI bypass modes that make AI text bypass any AI detection model.
Works with any type of AI-generated content including articles, essays, ad copy, etc. Benefits: Avoids GPTZero AI detection without fail.
Highly intuitive and user-friendly interface.
100% plagiarism-free and contextually accurate output. Aside from using an AI humanizer, there are a few other ways to make your AI content sound human-like enough to bypass GPTZero AI detection. Use More Specific AI Prompts Being specific with AI prompts can make a huge difference in the quality of output. For instance, if you include “In the style of…” when using an AI writer, it will usually match your desired tone and style. This can make the output sound less generic and robotic, which significantly reduces the likelihood of being flagged by AI detectors. Add More Sentence Variation AI detectors like GPTZero are trained to spot predictable word patterns, which is often seen in AI-generated content. This means implementing the use of varied sentences and paragraph lengths, as this will mirror how typical human conversation flows. In doing so, you are more likely to get high human scores on GPTZero and other AI detectors. Edit Using More Human Expression AI writing is easy to detect primarily because it lacks any distinctive human nuances. The content often sounds robotic and lifeless, which enables AI detectors like GPTZero to spot it. Instead, you can edit any AI-written text and implement more emotional cues like joy, humor, frustration, etc. This will help make the text sound more human and engaging. Focus On Active Voice AI text generators often use passive voice in the output, which makes the text unnecessarily wordy and harder to read. Most AI detectors are trained to look out for this but you can prevent that by editing the content using more active voice. This will help make the content sound more natural and human-like enough to bypass AI detection. Include Personal Anecdotes Unlike humans, AI writing tools can’t come up with personal stories or opinions. To this end, adding personal anecdotes can often help to make AI content sound authentic. In most cases, this can mean including case studies, testimonials, quotes, etc. As a result, you will give the text a more personal feel that AI detectors will recognize as human. Why Is It Important To Avoid GPTZero AI Detection? Avoid Penalties: Numerous academic institutions and publications use GPTZero to detect AI content. Moreover, Google’s policies on AI content are murky at best. Knowing how to beat GPTZero reduces the risk of facing consequences for using AI writing tools. Boost Reader Engagement: AI content can be bland and lifeless, which discourages audiences from reading any further. Beating GPTZero AI detection can be a great way to ensure that your content sounds more natural and relatable, which boosts reader engagement.


Maintain Originality: AI-generated content is often known to be generic and unoriginal. This can discourage teachers and readers from giving your work a chance. However, bypassing GPTZero will generally convey that the content has something unique to offer. Conclusion It has become increasingly necessary to avoid GPTZero AI detection, especially considering the rapid advancement of these AI detectors. If you are unable to make your content undetectable, then it will become very difficult for you to make full use of AI writing tools. In this article, we’ve summed up the different ways that you can use to bypass GPTZero effectively. The best option to consider is heading to Bypass GPT because it can help you humanize AI content in a flash until it is 100% undetectable. AI writing tools have drastically streamlined the content creation process across a wide range of fields and professions. However, the rise of AI detectors like GPTZero that work to detect AI content stands in the way of that. To make matters worse, these platforms aren’t foolproof. In other words, your content can still be falsely flagged even if you entirely wrote it yourself. This is why knowing how to bypass GPTZero is extremely vital, so let’s explore how to do that in detail. What Is GPTZero? GPTZero is an AI content detector initially launched in January 2023 by Princeton student, Edward Tian as part of his senior thesis project. Within the first week of release, it managed to successfully pull in over 30,000 active users. Since then, the company managed to raise $3.5 million in a seed round from several VC firms. This enabled its developers to further enhance the platform’s accuracy and even provide advanced capabilities like in-depth analysis reports, among other things. $3.5 million $3.5 million This made it a leading choice, especially among educators and academic institutions looking to identify students submitting AI-generated essays and papers. How To Bypass GPTZero AI Detection? While it is true that GPTZero is a powerful AI detector, the fact is that it is not unbeatable. There are several ways to go about making your AI-generated articles, essays, reports, and papers sound human-like enough to bypass GPTZero completely. Let’s explore them in detail below. Use An AI Humanizer Like BypassGPT Using an AI humanizer like BypassGPT is the most effective and easiest way to avoid GPTZero AI detection. Trained on millions of datasets of human-written texts, the advanced tool instantly rewrites AI content by mirroring authentic human-writing styles. BypassGPT BypassGPT This enables it to produce 100% undetectable output that can bypass even the most stringent AI detector including GPTZero. Best of all, BypassGPT does well to maintain content uniqueness and contextual accuracy at all times. Here are the key features and benefits of using BypassGPT: Features: Powerful AI humanization techniques that make AI content sound authentically human. Multiple AI bypass modes that make AI text bypass any AI detection model. Works with any type of AI-generated content including articles, essays, ad copy, etc. Powerful AI humanization techniques that make AI content sound authentically human. Multiple AI bypass modes that make AI text bypass any AI detection model. Works with any type of AI-generated content including articles, essays, ad copy, etc. Benefits: Avoids GPTZero AI detection without fail. Highly intuitive and user-friendly interface. 100% plagiarism-free and contextually accurate output. Avoids GPTZero AI detection without fail. Highly intuitive and user-friendly interface. 100% plagiarism-free and contextually accurate output. Aside from using an AI humanizer, there are a few other ways to make your AI content sound human-like enough to bypass GPTZero AI detection. Use More Specific AI Prompts Being specific with AI prompts can make a huge difference in the quality of output. For instance, if you include “In the style of…” when using an AI writer, it will usually match your desired tone and style. This can make the output sound less generic and robotic, which significantly reduces the likelihood of being flagged by AI detectors. Add More Sentence Variation AI detectors like GPTZero are trained to spot predictable word patterns, which is often seen in AI-generated content. This means implementing the use of varied sentences and paragraph lengths, as this will mirror how typical human conversation flows. In doing so, you are more likely to get high human scores on GPTZero and other AI detectors. Edit Using More Human Expression AI writing is easy to detect primarily because it lacks any distinctive human nuances. The content often sounds robotic and lifeless, which enables AI detectors like GPTZero to spot it. Instead, you can edit any AI-written text and implement more emotional cues like joy, humor, frustration, etc. This will help make the text sound more human and engaging. Focus On Active Voice AI text generators often use passive voice in the output, which makes the text unnecessarily wordy and harder to read. Most AI detectors are trained to look out for this but you can prevent that by editing the content using more active voice. This will help make the content sound more natural and human-like enough to bypass AI detection. Include Personal Anecdotes Unlike humans, AI writing tools can’t come up with personal stories or opinions. To this end, adding personal anecdotes can often help to make AI content sound authentic. In most cases, this can mean including case studies, testimonials, quotes, etc. As a result, you will give the text a more personal feel that AI detectors will recognize as human. Why Is It Important To Avoid GPTZero AI Detection? Avoid Penalties: Numerous academic institutions and publications use GPTZero to detect AI content. Moreover, Google’s policies on AI content are murky at best. Knowing how to beat GPTZero reduces the risk of facing consequences for using AI writing tools. Avoid Penalties: Numerous academic institutions and publications use GPTZero to detect AI content. Moreover, Google’s policies on AI content are murky at best. Knowing how to beat GPTZero reduces the risk of facing consequences for using AI writing tools. Google’s policies on AI content Google’s policies on AI content Boost Reader Engagement: AI content can be bland and lifeless, which discourages audiences from reading any further. Beating GPTZero AI detection can be a great way to ensure that your content sounds more natural and relatable, which boosts reader engagement. Maintain Originality: AI-generated content is often known to be generic and unoriginal. This can discourage teachers and readers from giving your work a chance. However, bypassing GPTZero will generally convey that the content has something unique to offer. Boost Reader Engagement: AI content can be bland and lifeless, which discourages audiences from reading any further. Beating GPTZero AI detection can be a great way to ensure that your content sounds more natural and relatable, which boosts reader engagement. Boost Reader Engagement: AI content can be bland and lifeless, which discourages audiences from reading any further. Beating GPTZero AI detection can be a great way to ensure that your content sounds more natural and relatable, which boosts reader engagement. Maintain Originality: AI-generated content is often known to be generic and unoriginal. This can discourage teachers and readers from giving your work a chance. However, bypassing GPTZero will generally convey that the content has something unique to offer. Maintain Originality: AI-generated content is often known to be generic and unoriginal. This can discourage teachers and readers from giving your work a chance. However, bypassing GPTZero will generally convey that the content has something unique to offer. Conclusion It has become increasingly necessary to avoid GPTZero AI detection, especially considering the rapid advancement of these AI detectors. If you are unable to make your content undetectable, then it will become very difficult for you to make full use of AI writing tools. In this article, we’ve summed up the different ways that you can use to bypass GPTZero effectively. The best option to consider is heading to Bypass GPT because it can help you humanize AI content in a flash until it is 100% undetectable. Bypass GPT Bypass GPT

How to Bypass GPTZero AI Detection

কিভাবে GPTZero AI সনাক্তকরণ বাইপাস করবেন

So umgehen Sie die GPTZero-KI-Erkennung

Cómo evitar la detección de IA GPTZero

Comment contourner la détection GPTZero AI

GPTZero AI डिटेक्शन को कैसे बायपास करें

GPTZero AI検出を回避する方法

GPTZero AI 탐지를 우회하는 방법

Como ignorar a detecção GPTZero AI

Как обойти обнаружение AI GPTZero

GPTZero Yapay Zeka Tespiti Nasıl Atlanır?

Cách vượt qua tính năng phát hiện GPTZero AI

如何绕过 GPTZero AI 检测

Why Humans Are Drawn to Games

কেন মানুষ গেমের প্রতি আকৃষ্ট হয়

Warum Menschen sich zu Spielen hingezogen fühlen

Por qué los humanos se sienten atraídos por los juegos

Pourquoi les humains sont attirés par les jeux

मनुष्य खेलों की ओर क्यों आकर्षित होते हैं?

人間がゲームに惹かれる理由

인간이 게임에 끌리는 이유

Por que os humanos são atraídos pelos jogos

Почему людей привлекают игры

İnsanlar Neden Oyunlara Çekilir?

Tại sao con người bị thu hút bởi trò chơi

人类为何热衷于游戏

How To Resolve Conflicts With Your Superiors At Work

Hey everyone! and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon or my personal website . In today’s article, we’ll be looking at the case study of how Klarna leveraged Gen AI and what other companies can learn from it. , I’m Nataraj 100 days of AI here here How is Klarna using generative AI? There are lots of ways generative AI is being used by companies, and we have explored some of them . In case of Klarna, they launched an AI customer support assistant that is available 24*7 and supports 30+ languages. They launched the assistant using Open AI as their LLM provider. If we have to guess, they have finetuned it using their own customer support interaction data set that they have collected over the years. in a previous post What features does the Klarna AI assistant support? The assistant is designed to handle wide range of questions related to refunds, returns, payment-related issues, cancellations, disputes, and invoice inaccuracies, ensuring swift and effective solutions. Like any tech feature, its available 24*7 across all geographies. For customers who want to know what they can afford and not afford, it also provides info related to purchase power, spending limits and the reasons why it exists. All the info of a customer account is with the assistant to help any questions related to it. Is the new AI assistant effective? Its cool to say that we have used gen AI and see the stock pop up, but the real question is, does the feature deliver value to the company. And from the numbers, it looks like it is beating expectations. Here are some of the numbers. Two-thirds of all customer service chats are handled by the assistant, which is an impressive 2.3M conversations. Customer satisfaction same as human conversations. 25% drop in repeat inquiries Estimated to drive $40M in profit improvements to the company. What are the takeaways from Klarna’s gen AI assistant? Its clear that generative AI is being adopted and creating value for companies at all stages. Customer support will get more effective and cheaper. If the new assistant is handling two-thirds of all conversations, it means the next set of companies which start their customer support teams will not require the same number of people in their teams. And this also means the existing customer support teams might be larger than needed. We will see a lot of growth stage startups follow Klarna to boost their profitability and reduce expenses. For companies like Klarna whose stocks are down due to the concern of profitability, companies with similar concerns will start to look at leveraging AI to cut costs and boost profitability. Open AI’s board drama didn’t effect its trust among companies to use them for production scale deployments. When Sam Altman was fired and re-hired at Open Ai, one of the concerns was that this would reduce the trust among developers to use Open Ai to create AI applications. When a large public company publishes such a case study its clear that the board drama at Open Ai didn’t effect Open AI’s abilities. Expect more companies to announce improvements because of using gen AI technology in fields outside customer support. More case studies using generative AI will come from more public companies showing how they are leveraging Ai. This is a function of every company wanting to get a piece of the AI narrative and the fact that gen AI features are actually delivering on value. If you are a company with large data set related to customer support, you should explore creating an AI assistant for support interactions. That’s it for Day 19 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, . subscribe to it Follow me on , or for latest updates on 100 days of AI or . If you are in tech you might be interested in joining my community of tech professionals . Twitter LinkedIn HackerNoon bookmark this page here

100 Days of AI, Day 19: Klarna’s AI Chatbot and The Rise of Generative AI in Startups

এআই-এর 100 দিন, 19তম দিন: ক্লারনার এআই চ্যাটবট এবং স্টার্টআপে জেনারেটিভ এআইয়ের উত্থান

100 Tage KI, Tag 19: Klarnas KI-Chatbot und der Aufstieg der generativen KI in Startups

100 días de IA, día 19: El chatbot de IA de Klarna y el auge de la IA generativa en las empresas emergentes

100 jours d'IA, jour 19 : le chatbot IA de Klarna et l'essor de l'IA générative dans les startups

एआई के 100 दिन, दिन 19: क्लार्ना का एआई चैटबॉट और स्टार्टअप्स में जनरेटिव एआई का उदय

100日間のAI、19日目: KlarnaのAIチャットボットとスタートアップにおける生成AIの台頭

AI 100일, 19일차: Klarna의 AI 챗봇과 스타트업에서 생성 AI의 부상

100 dias de IA, dia 19: AI Chatbot de Klarna e a ascensão da IA generativa em startups

100 дней искусственного интеллекта, день 19: чат-бот Klarna с искусственным интеллектом и рост генеративного искусственного интеллекта в стартапах

100 Gün Yapay Zeka, 19. Gün: Klarna'nın Yapay Zeka Sohbet Robotu ve Yeni İşletmelerde Üretken Yapay Zekanın Yükselişi

100 ngày của AI, Ngày 19: Chatbot AI của Klarna và Sự trỗi dậy của AI sáng tạo trong các công ty khởi nghiệp

人工智能 100 天，第 19 天：Klarna 的人工智能聊天机器人和初创企业中生成式人工智能的兴起

Ishan Pandey: Hi John, welcome to our "Behind the Startup" series. Could you share some insights into your transition from a traditional investment banking background to becoming a FinTech entrepreneur and how your experiences have influenced the vision and direction of MANTRA? I had been in crypto for. For a long time before I actually joined a bank. I bought my first bitcoin in 2013, which was when I was back in university. So I think I've been pretty crypto native in technology, technologically driven, since a very young age. Even when I was at the bank, I was researching fintech and blockchain and other types of financial technology applications. So it was more about the culture and the type of business I wanted to work in. John Patrick Mullin: I definitely like the convergence of both the tech and the finance part, but it was more about this. I think the reason that I ended up shifting out and going into entrepreneurship is the ability to build something from scratch, lead people, work with people on incredibly tough challenges every day, and I'm just a bit of a workaholic, so entrepreneurship suits me. Ishan Pandey: Could you elaborate on the specific products and features that MANTRA is planning to launch to facilitate DeFi participation for both institutional and retail investors? At MANTRA we are building our Module layer which has MANTRA Token Service Module, MANTRA Assets Module, Guard Layer, MANTRA Compliance Module that enable creation, management and trading of RWAs for institutions, businesses, retailers, developers and users at ease. John Patrick Mullin: Ishan Pandey: How does MANTRA collaborate with regulatory authorities and industry partners to establish best practices and standards for tokenizing RWAs within the DeFi ecosystem? MANTRA is in the process of applying for requisite licensing for on chain exchange and brokerage, as well as asset investment management products in the UAE. We also work with regulated partners in other jurisdictions. One of the ways that we're able to cooperate and adhere to regulatory requirements is through our unique custom guard module on the MANTRA Chain, which allows us to create a compliant cocoon for many of the on chain applications that would require oversight, regulatory oversight and compliance. John Patrick Mullin: Ishan Pandey: How do tokenized real-world assets (RWAs) contribute to MANTRA’s strategy and offer unique opportunities for investors? Can you provide examples of tokenized RWAs that  MANTRA Finance plans to offer? MANTRA plans to offers a variety of RWAs to offer unique and extensive opportunities that includes stocks, bonds, commodities, real estate, art work and varied illiquid Traditional Assets. John Patrick Mullin: Ishan Pandey: What motivated the decision to debut yield-bearing DeFi products initially, followed by the launch of a Central Limit Order Book (CLOB) DEX and derivative products? Initially, we decided that it would make the most sense to launch with vault style products or yield bearing products, which obviously allow users to get exposure to not just RWAs, but other types of crypto yield bearing instruments. I think the two things in crypto that people are interested in is both the yield seeking part as well as the speculative part. So we want to cater to both parts of this user experience. We believe that naturally an exchange is really important to have within an ecosystem, whether that's a DEX, an order book exchange, etc. but we also believe in bringing finance onchain. So it made sense to launch an onchain sentiment order book that sits on top of an AMM, allowing for both. Simple swapping as well as more sophisticated trading structures. John Patrick Mullin: Ishan Pandey: What role does MANTRA Chain play within the MANTRA ecosystem, and how does it generate revenue? John Patrick Mullin: MANTRA Chain is the underpinning of everything within the MANTRA ecosystem. The OM token is the center of all this, which is the native token of the MANTRA Chain. We believe in this idea of the app chain thesis. So the protocol that we're developing, which is MANTRA Chain, has created specifically purpose built technology and software that allows applications that build on top of it to comply with local regulations across the globe. It's really the protocol for the entirety of our ecosystem. Ishan Pandey: As MANTRA moves towards its initial equity financing round, what are the key priorities for the company in terms of investor relations and fundraising activities? We raised $11 million, led by Shorooq Partners, which is a leading fintech VC in the UAE. Some of the priorities for the company, now that we've raised this capital, is hiring, expanding the team, growing our licensing capabilities, etc. John Patrick Mullin: Ishan Pandey: How does MANTRA ensure the integrity and authenticity of tokenized RWAs on its platform, especially considering the potential for fraud or misrepresentation in the tokenization process? MANTRA has its own Guard Module and Passportable DIDs that ensures a walled garden of KYC/KYB and Anti Money Laundering system. John Patrick Mullin: Ishan Pandey: Could you elaborate on the potential challenges associated with cross-border compliance and regulatory differences when dealing with tokenized RWAs from various jurisdictions, and how MANTRA plans to address them? One of the things that is obviously incredibly important when it comes to dealing with RWAs and other types of products is the ability to adhere to local regulations. So because of that, we built this idea of the guard module, which allows for permissioning across the wallet, the product, the pool, the asset, etc. and we have this customizable ability to allow and permission usage from individuals from different jurisdictions and also block them from others. So we can actually stop people who are not able to touch and interact with products at the smart contract level via this guard module. John Patrick Mullin: Ishan Pandey: How does MANTRA plan to educate investors about the benefits and risks of investing in tokenized RWAs compared to traditional financial instruments? Education is a really important thing when you're creating a new market, and we're definitely beating the drum for RWAs and tokenized on chain financial products. We're doing interesting things with respect to various hackathons. Obviously a lot of in person engagement, educational content from our social media team and marketing team, and we'll also have some unique incubator style arrangements where we'll be actually supporting teams to build on this RWA focused ecosystem. John Patrick Mullin: Additionally, we're cooperating with major academic institutions, particularly their blockchain clubs, that will allow us to educate the next generation about onchain financial products. Ishan Pandey: How does MANTRA perceive the role of RWAs in the future of crypto? Additionally, how does MANTRA aim to bring RWAs into the mainstream investor's radar? John Patrick Mullin: I believe that RWAs are just an extension of the financial system bringing it on chain. RWAs is frankly a bad acronym, it was called STO not too long ago. So I think there's a better way to actually describe these type of products and it's mainly just geared around tokenization. So I believe almost everything can be tokenized. That doesn't mean everything should be tokenized, but most financial products and platforms in my opinion in the future will be on some degree of a blockchain, although you may not know that it's on a blockchain. So I think this is incredibly important for our strategy. We believe the financial ecosystem is moving onchain and we'll be at the forefront of that. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR

Bridging Traditional Finance and Crypto: The Rise of MANTRA's Tokenization Ecosystem

ঐতিহ্যগত অর্থ এবং ক্রিপ্টো ব্রিজিং: MANTRA এর টোকেনাইজেশন ইকোসিস্টেমের উত্থান

Brücke zwischen traditionellem Finanzwesen und Kryptowährungen: Der Aufstieg des Tokenisierungs-Ökosystems von MANTRA

Uniendo las finanzas tradicionales y las criptomonedas: el auge del ecosistema de tokenización de MANTRA

Faire le lien entre la finance traditionnelle et la cryptographie : l'essor de l'écosystème de tokenisation de MANTRA

पारंपरिक वित्त और क्रिप्टो को जोड़ना: MANTRA के टोकनाइजेशन इकोसिस्टम का उदय

従来の金融と仮想通貨の橋渡し: MANTRA のトークン化エコシステムの台頭

전통적인 금융과 암호화폐 연결: MANTRA 토큰화 생태계의 부상

Unindo finanças tradicionais e criptografia: a ascensão do ecossistema de tokenização do MANTRA

Соединение традиционных финансов и криптовалюты: развитие экосистемы токенизации MANTRA

Geleneksel Finans ve Kripto Arasında Köprü Kurmak: MANTRA'nın Tokenizasyon Ekosisteminin Yükselişi

Kết nối tài chính truyền thống và tiền điện tử: Sự trỗi dậy của hệ sinh thái mã thông báo của MANTRA

连接传统金融和加密货币：MANTRA 代币化生态系统的崛起

Before I elaborate on my experiment, let me explain my proficiency in Chess. I am no advanced-level player. I know a few openings and sometimes fumble with chess notations. I mostly play blitz games against Stockfish. A few months ago, I started playing against Stockfish Level 8, which is the highest level of difficulty offered at Lichess, the open Chess platform that comes with the most beautiful UI/UX. As a player with limited chess knowledge and skills, I always found beating Stockfish Level 8 a daunting task. For those who are not aware of Stockfish Level 8 prowess, here is more. You need to be a super GM or someone with an ELO rating of 2600+ to achieve that feat. Again, I am not sure of what I said because Stockfish Level 8 usually plays with an accuracy of 99 percent with an average centipawn loss of almost 20. In the past, I have challenged Stockfish Level 8 in a variety of ways. Once, I gathered a group of 5 Chess enthusiasts comprising all good players, and still, Stockfish Level 8 defeated us in 22 moves. My best performance against Stockfish Level 8 is being checkmated after 47 moves. Lol. With that said, I thought, why shouldn’t I employ the power of ChatGPT? In the experiment, The game had no time limits, and I was assigned white pieces. I have summoned the powers of ChatGPT 3.5 against Stockfish Level 8. My very first prompt to ChatGPT was the following: hey, I am playing the game of chess against the chess engine stockfish level 8, which is the hardest level of difficulty offered. I am playing with white pieces so suggest me moves. Guide me throughout the game and now suggest me the opening. Here is what it responded with Sure, here’s a classic opening you can use as White: the Queen’s Gambit. It’s a solid opening that focuses on controlling the center of the board and developing your pieces efficiently. Here’s how you can start: d4: This move is the start of the Queen’s Gambit. It immediately fights for control of the center and opens lines for your pieces. Now, let’s see how Stockfish responds. It might play: 1… d5: Black also aims to control the center. Now, you can continue with: c4: This move is the Queen’s Gambit proper, offering a pawn sacrifice to gain central control. Stockfish might accept the gambit with: 2… dxc4: Accepting the gambit pawn. And then you continue with: e4: This move aggressively reinforces your center and gains space on the board. It also threatens to regain the pawn on c4 with e4xd5. Now, you’ve established a strong central presence and initiated an aggressive game. Keep developing your pieces and look for opportunities to exploit weaknesses in Stockfish’s position. Let me know how the game progresses, and I can provide further guidance as needed. Sure, here’s a classic opening you can use as White: the Queen’s Gambit. It’s a solid opening that focuses on controlling the center of the board and developing your pieces efficiently. Here’s how you can start: d4: This move is the start of the Queen’s Gambit. It immediately fights for control of the center and opens lines for your pieces.
Now, let’s see how Stockfish responds. It might play: 1… d5: Black also aims to control the center. Now, you can continue with: c4: This move is the Queen’s Gambit proper, offering a pawn sacrifice to gain central control.
Stockfish might accept the gambit with: 2… dxc4: Accepting the gambit pawn. And then you continue with: e4: This move aggressively reinforces your center and gains space on the board. It also threatens to regain the pawn on c4 with e4xd5.
Now, you’ve established a strong central presence and initiated an aggressive game. Keep developing your pieces and look for opportunities to exploit weaknesses in Stockfish’s position. Let me know how the game progresses, and I can provide further guidance as needed. I inadvertently played d5, a move not suggested by ChatGPT. The move by Stockfish was f5. Curious to know the implication of this, I updated ChatGPT about my move. Here is the guidance from ChatGPT. It seems Stockfish is opting for a somewhat unorthodox response with 1… f5, which is known as the Dutch Defense. This move aims to control the e4 square and potentially fianchetto the bishop on g7 to create a solid pawn structure on the kingside. Here’s how you can respond: e4: This move challenges Black’s pawn on f5 and aims to open up lines for your pieces. It also gains more control of the center. Now, Stockfish might respond with: 2… e6: This move supports the pawn on f5 and prepares to develop the bishop to d6 or e7. You can continue with: Nf3: This move develops a knight and prepares for further centralization of your pieces. It also indirectly supports the e4 pawn. At this point, you have a solid position and are ready to continue developing your pieces. Look for opportunities to expand your control of the center and prepare for potential pawn breaks to create imbalances in the position. Let me know how Stockfish responds, and I’ll be here to guide you further. Clearly, both responses showcase ChatGPT’s power to analyze the information and offer insights. Sadly I failed to follow through the advice and played some other move. However, this could not be the end of the experiment. Thus, I made up my mind to start a game afresh. I quickly told ChatGPT this: Me : I have begun a new game. suggest me an opening ChatGPT : Certainly! Let’s try a different opening this time. How about the Italian Game? It’s a classical opening that focuses on developing your pieces rapidly while exerting pressure on Black’s position. Here’s how you can start: e4: This move controls the center and frees your bishop and queen for future development. Now, Stockfish might respond with: 1… e5: This is a symmetrical response, aiming to control the center and mirroring your moves. You can continue with: Nf3: This move develops your knight and attacks the e5 pawn. Now, Stockfish might continue with: 2… Nc6: This move develops a knight and defends the e5 pawn. You can now play: Bc4: This move develops your bishop, aiming it at the vulnerable f7 square. It’s a key move in the Italian Game, often leading to aggressive attacking possibilities. I began with white pieces and played e4. My idea was to control the central block of squares, and ChatGPT had already suggested that. Stockfish moved a pawn to d6. ChatGPT inferred the motive as developing bishop and predicted the next step would be using Pirc Defense or the Philidor Defense. It suggested D4 as a response, but I did not find any merit in this move. Another suggestion was Nc3. I found this move to be better as it brings the knight to the front, and thus, e4 gets secured. Stockfish responded with e5, and ChatGPT suggested the development of the Pirc Defense, as in the last attempt. I played Nf3. But to our surprise, Stockfish came up with c5. As I have played so many times against the Stockfish, I have witnessed how it quickly develops bishop and queen. The motive is to checkmate you in the next 4 or 5 moves. I was suggested d5, and I found it to be a typing error as the pawn could move to d4 at most. Here, the game position was this: No brainer for the above-average AI assistant. cxd4 was the obvious choice, and ChatGPT anticipated this move as expected. Like a reflex action, I would move the knight to b1. However, ChatGPT had something else in the mind. It suggested me Nxd4. And I did it with zero regard for a less of a sacrifice. I paid a little more price as I lost the knight to a pawn. In order to salvage this situation, I was suggested Bb5+, which is nothing but forcing a check on Stockfish’s king. Left with no choice, Stockfish had to bring in its bishop to d7. Though not among ChatGPT’s suggestions, I played Qxd4. After this move, I updated ChatGPT with the moves I had played till then. And I was reverted with: After this, I castled and asked about the next move. ChatGPT gave a response that was somewhat similar to its previous one. I was disappointed after casting. I could sense more trouble as I had lost a piece more than Stockfish. Finally, the position was this: The suggestions were not clear. They were repetitions and thus stopped my experiment. This was the battle between a generalist (ChatGPT) and a specialist (Stockfish). In my opinion, ChatGPT fares well initially and excels at analyzing the moves, but the analysis lacks substantiated knowledge. It fails to advance you to the mid-game. If you are thinking of hiring a bot or AI tool as your chess coach, then nothing could help you. Here is the score line according to me: Stockfish Level 8 vs ChatGPT 3.5 : 1–0 Also published . here

A Game of Chess: Pitting ChatGPT Against Stockfish

Dust on Crust Part Deux

ভূত্বক অংশ দুই উপর ধুলো

Staub auf der Kruste Teil Zwei

Polvo sobre la corteza, segunda parte

पपड़ी पर धूल भाग दो

クラスト上のダスト パート 2

지각 위의 먼지 2부

Poeira na Crosta Parte Dois

Пыль на корке, часть вторая

Kabuktaki Toz İkinci Bölüm

Bụi trên lớp vỏ Phần thứ hai

地壳上的灰尘第二部分

It was 1895 when Willem Einthoven, a Dutch doctor, made a discovery that would charge cardiology for the next century. Fiddling with wires and voltages, he traced the electric currents flowing through a beating heart. This became the (ECG), a device that visualizes the heart’s inner workings. first practical electrocardiogram For decades, ECG technology remained much the same, with leads patching onto the skin to record the heart’s electrical impulses. But human perception has limits. Now, AI is taking medical analysis to profound new levels, unlocking lifesaving discoveries in terabytes of data. For example, were used in a Nature research article to train deep neural networks to classify arrhythmias more accurately than cardiology specialists. 2,322,513 ECG records Let’s rewind for a moment. Heart disease has become the cause of death globally, causing around 51,000 deaths a day. Visualizing this data is striking. leading Many show no prior symptoms, the first sign being their last. But what if we could detect threats early and prevent these deaths? This is the promise of firms like and , medical companies harnessing AI to transform the humble ECG into a cutting-edge screening tool. HeartScience’s flagship product, MyoVista Wavelet ECG, incorporates sophisticated machine learning to uncover hidden heart problems. And a new partnership with Mount Sinai Hospital — home to pioneering AI research — could be the catalyst that saves lives worldwide. HeartSciences Anumana Deep Neural Networks to Save Hearts The standard 12-lead ECG has served cardiologists well, visualizing electrical signals as squiggly lines on graph paper. But it has limitations. The test often misses two major disease categories — ischemia (clogged blood vessels) and structural issues like weakened heart muscles. This is where MyoVista steps in. Its spotlight subtle ECG patterns missed by the human eye, acting as an early warning system. AI algorithms One model uses a set of 51 ECH features, 26 of which come from Continuous Wavelet Transform (CWT) frequency features—the remaining come from traditional ECG parameters, along with clinical data like age and medical history. This data makes it possible to train a DNN (deep neural network), boasting areas under the receiver operating characteristic curve (AUC) ranging between 0.80 and 0.87. In other words–these neural networks can accurately predict MACE (major adverse cardiovascular events). These models have been trained and validated on patient data from institutions like the Icahn School of Medicine at Mount Sinai and West Virginia University. Such machine learning techniques are transforming medical imaging and diagnosis across specialties. But cardiology is particularly ripe for disruption as heart disease causes ever more deaths globally. MyoVista promises a quick, non-invasive test to uncover threats in routine doctor visits. And this early detection can make all the difference. Algorithms Making Their Way Into Hospitals ECG electrodes have become ubiquitous, deployed far beyond cardiology units. General practitioners, ER doctors, and specialists of all stripes snap ECG leads onto patients. But most lack specialized expertise to maximize this tool and miss subtle signs of cardiac dysfunction. MyoVista fills in these analytical gaps with AI acting as a digital cardiologist that spots what human doctors cannot. In one validation study, MyoVista achieved 94% accuracy in prediction of LV diastolic dysfunction, as referenced in a recent . But the algorithms powering MyoVista require hefty data resources to develop — far beyond most companies’ capacity. This is where HeartSciences’ recent partnership with New York’s Mount Sinai Hospital proves game-changing. report The Icahn School of Medicine at Mount Sinai has emerged as a global leader in AI-driven cardiology research. Their elite has cultivated databases of curated heart patient records — an unparalleled asset. Now, HeartSciences has to this goldmine, including 13 Mount Sinai algorithms spanning major cardiac diseases. This agreement catalyzes their ambitions to transform ECG screening worldwide. data science team licensed exclusive access Like most AI software penetrating healthcare, HeartSciences needs to run a gauntlet of quality checks before commercializing MyoVista. Previously, novel digital diagnostic tools like theirs required lengthy De Novo FDA applications before clearance. But there’s a faster 510(k) pathway for HeartSciences’ model. This simplified process means that HeartSciences’ algorithms could soon be in your local hospital. Additionally, HeartSciences has proactively engaged the FDA multiple times to optimize MyoVista for compliance. They also recently completed patient enrollment for their pivotal validation study spanning five US research sites and over 600 subjects. This data will demonstrate MyoVista’s capabilities on a wide demographic, paving the way for approval. The Road Ahead Heart disease deaths continue rising yearly, hastened by modern lifestyles and aging populations. Better prevention through earlier detection has become imperative. HeartSciences leads a growing field of companies centered on this mission — leveraging AI’s pattern recognition to uncover what standard tests miss. The ECG is now well over a century old. But it has now outgrown the bulky monitors and needle graphs conceived by its Dutch inventor. AI is writing the next era of cardiac diagnostics with software smarts. In the right hands, this old tool may gain new power to prevent the #1 killer from claiming lives too soon.

AI-Powered Healthcare Could Save Your Life

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