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Elaborate

“If you hire a fraudster to defraud someone, you’ll have to expect getting defrauded.” - Horst Evers Earlier, I wrote an article for CryptoCoin.News about . What struck me were the sheer lengths some crypto scammers are apparently willing to go, just to rip people off their hard-earned money. frontrunning DEX trades After all, we live in a world where you could just impersonate some famous crypto celebrity, upload one of his videos to a fake YouTube account, drop your wallet address in the video description and promise the viewer to return twice the amount sent to the address. Easy bucks. Typically, crypto scams don’t reward effort. They usually target inexperienced and gullible users in such a way that these schemes can be repeated over and over again. This is how scammers maximize their return on investment. The fake frontrunning bot is not one of these. These are highly sophisticated scams targeting advanced crypto users and boy, does this rabbit hole run deep. Here’s what I found. The Frontrunning Scam Analyzed Over the last two months, quite a few YouTube videos have been uploaded that appear to be tutorials for how to operate a frontrunning bot. These videos instruct the viewer to deploy and fund a smart contract, which will then supposedly carry out the frontrunning transactions. As “proof” that the bot works, the scammer then funds the contract with 0.4 BNB and magically, a few minutes later, his wallet shows a balance of almost 10 BNB. What makes this scam so peculiar is that the scammer actually tells a convincingly believable story. While making an almost 25x return in just a few minutes is still way out there, frontrunning is actually a multi-million dollar unethical activity that is taking place around the clock, which is basically an open secret in DeFi. Also, having the victims deploy their own smart contract gives them a false feeling of security. Here is an example a fake frontrunning bot scam: There’s actually a plethora of these videos out there on YouTube. Somehow, they usually manage to stay online for weeks, so cheers to YouTube’s response speed. I picked this one since that scammer made an extra effort to look legit in his comments, even commenting how all the other bots are scams, but this is finally the true one. Of course, all of the accounts that commented were created on the same day the comment was written. Let’s Take a Look at the Smart Contract Now, I’m not really a Solidity coder, but what immediately sticks out is that most code lines are commented out, which should be a telltale sign that something fishy is going on here. Within the code lines that are not commented out, there isn’t much to see either, except some variable declarations. Then, there is the action() function the scammer prompts us to call in his video. This function consists almost entirely out of comments and several lines that simply state manager;. Also, there is this line, which I guess will ultimately send the funds to the scammer’s address. But there is no address anywhere in the code that would point at the scammer, except the WBNB contract address, which is commented out. The answer can be found in the import statements. Besides three contracts that are imported from Uniswap’s Github, there is also a fourth import from an IPFS URL. Another red flag. On first glance, that contract looks exactly the same, except that there’s now even more lines that are commented out. However, the contract is called “Manager”, so I guess that this is what is called over and over in the original contract. Here, we can also find the scammer’s address in an uncommented line. Great, so we can now take a look at this address on and find that the scammer received a total of more than 40,000 USD in BNB already, oftentimes in tranches of 0.4 BNB, which he advises in the video as the minimum funding amount. Scam confirmed! bscscan So why all This Effort? The question remains though why someone would come up with a scam so elaborate, while it seems far easier and more rewarding to just spam people on social media with fake airdrops or phishing messages. My best guess is that the dubious nature of frontrunning provides an extra layer of security from law enforcement for the scammers. Nobody who loses 250 USD to a scammer will ever go to the police and say “Hey, I got ripped off while trying to engage in some morally questionable and potentially illegal crypto practice”. Also, it might be easier on the scammer’s own conscience if they go after people who are apparently trying to make money using immoral methods. Of course that doesn’t make it OK though. The victims who fall for this scam are still ordinary and mostly inexperienced crypto users. Anyway, if I were to judge which is more morally wrong, using a frontrunning bot or scamming people with fake frontrunning bots, I’d definitely say the latter. Another theory I have, although I think that it’s a lot less probable, is that some of the scammers are actually operating frontrunning bots and plant the scam videos as a decoy to deter other people from actually going into frontrunning and becoming competitors. Also, the real work was coming up with this scam type, but it is extremely easy to replicate. Just take the scammer’s code, swap his wallet address with your own, replicate the video word by word and upload your lure to YouTube. Maybe curate the comments a bit (not everyone does it) and wait for the money to trickle in. This video from Chris Daniels, who also analyzed this new scam type, actually showcases how most of the videos contain exactly the same text that is read by people with different voices, so apparently, that scam has already found its copycats: Are there any legitimate frontrunning bots? Define “legitimate”. I’m not going to comment on the ethics of frontrunning here, but let’s just say that the whole frontrunning scene has quite a few characteristics of organized crime. Exclusivity is one of them. Most of the open-source DEX trading (sniping) bots I’ve seen so far just listen for an external event, like a DEX listing or listing on CoinMarketCap and try to be the first in line for buying a token early on. I would say that this is in fact a legitimate use case for automated trading, but your mileage may vary. Among the bots that claim to be able to actually frontrun DEX trades, I have only seen one that is free, but Windows Defender doesn’t let me execute it, stating that it’s a trojan. I’ve uploaded the files to VirusTotal and they confirmed that the two executables both contain malware, the trojans Wacatac and Uwamson, in addition to a coin miner. Other frontrunning bots are for sale with their supposed developers sometimes charging thousands of Dollars. And of course you cannot be sure that these people won’t either try to scam you as well, or send you a bot that is also laced with malware. Occasionally, you’ll even come across YouTube videos that say “Hey, don’t fall for fake frontrunning bots, they changed the code, here’s the real one” or something like that. But we can definitely rule that out. Conducting frontrunning attacks with just a smart contract is impossible. First of all, in order to pull off a frontrun, you need to have knowledge of an upcoming DEX trade, in other words, you need to have access to the mempool. Smart contracts can only see data that is already published in the blockchain, but they can’t see the mempool. Also, smart contracts don’t really do anything unless one of their functions is called. They’re not actively scanning the blockchain waiting for transactions. Even if you would somehow gain knowledge of a DEX trade and communicate that knowledge to a smart contract which is supposed to carry out the attack, this method would be way too slow for a successful frontrun. At the very least, you’d need to have a script running that actively checks the mempool for incoming swaps and then directly calls the DEX smart contracts at a higher gas price. Could it be? And that brings me back to the the scammers from YouTube present us with, especially the lines that are commented out. phony smart contract code At first, I thought that these are just garbage code to bulk up the contract and make it look like it is actually doing something. Upon closer inspection, I noticed something though. I want to stress once more that I am not a developer, but even with my limited coding knowledge, I can see that this isn’t Solidity code at all. If I were to guess, I would say that it’s JavaScript. And lo and behold, that commented out code actually does make references to frontrunning attacks. It also seems to connect to an Infura node, which indeed has access to the mempool. I can’t say whether this is really true, I hope that someone who can understand what that code does can help me out here, but could it be that these scammers have actually hidden the real frontrunning bot in plain sight? Now that would be too comical, wouldn’t it?

Inside Crypto’s Most Elaborate Scams: Fake Frontrunning Bots 

painting of me by , commissioned by a scammer Elena Malva Software is eating the world, but blockchains are kicking the asses of scammers. If you haven’t heard about by now, you’re likely living under a rock. Blockchain ICOs make Silicon Valley bros wet their pants and it’s like a new religion has been created overnight. the blockchain Very few people understand what a blockchain is, let alone what a blockchain can do in the real world, but the story I’m about to tell you will hopefully illustrate it. This is a crazy story I’m about to tell you. It involves art, multiple identity thefts, the Ukraine, the Steem blockchain, myself and Sherlock Holmes. Well, it’s not the Sherlock Holmes, but an account in named @sherlockholmes. real Steemit Here goes: A number of weeks ago, a user named painted a very detailed portrait of myself. I didn’t know this user as she was not my friend at the time in Steemit. Here’s the portrait she painted of me (as my Steemicide Hotline character). It’s quite detailed and pretty good: Steemit @elena2017 art by Elena Malva I upvoted her post which resulted in her gaining some Steem, reputation score increases and also name recognition in the community. After she painted my portrait, I began supporting and sharing more of her posts in Steemit. She began attracting more followers because her artistic talent was pretty impressive. Here’s one of my favorites of hers: art by Elena Malva Fast forward several weeks….. Yesterday, a user named appropriately, , revealed his shocking findings about the account, @elena2017: it was a total fake. And he had the evidence to prove it. @elena2017 had stolen the identity of a real artist from the Ukraine named and had been posting her photos, paintings and drawings on Steemit for months. But how was my portrait painted, and who painted it? Who was the person holding the portrait of me? Someone painted my portrait, but who? @sherlockholmes Elena Malva This is where the story gets super weird. The scammer had contacted the real Elena ( ) and paid her $15 to create a portrait of me. The scammer had also requested that the real Elena take photos of herself holding the portrait of me. Here is a photo of the real Elena holding the portrait of me: Elena Malva Elena holds painting of me After the scammer had paid the real Elena to paint a picture of me, she posted it on Steemit and milked this thing like no tomorrow. The scammer wrote several posts that glorified me as “Steemit’s Best Blogger” and other stuff like that, which I naturally upvoted. A quick visit to the real reveals the disturbing reality of being smack in the middle of an identity theft. She clearly states that she has never joined Steemit, and that someone has stolen her identity and is posting her artwork for monetary gain on Steemit: Elena’s Facebook page Sherlock Holmes had also posted another update to his earlier post about Elena. It revealed that was not the only artist who was being impersonated. The scam ring extended to 4 other Ukrainian artists, and Sherlock was untangling the story behind each one. All of the identity theft artist accounts were tied to , which is a real person. Sherlock had reached out to @annart both on Steemit and on (Russian Facebook) but unlike the artists whose identities were stolen, this person never responded back to Sherlock. Elena Malva @annart vk.com https://vk.com/id57240151 You can read @sherlockholmes’ full story here: https://steemit.com/steemit/@sherlockholmes/case-6-busting-annart-s-ukrainian-fake-artist-ring It was at this time I decided to do a little searching on the blockchain, just to ensure that all this information was correct. Since I had never heard of @sherlockholmes until recently, I wanted to make sure his evidence was rock solid. How Money Flows In And Out of Steemit It’s important to know how money flows in and out of . In order to withdraw your Steem from , you need to set up an account at one of the cryptocurrency exchanges, like . Since this scammer used Bittrex, let’s go over how that works. Steemit Steemit Bittrex.com Every Bittrex account for Steem has a memo identification associated with it. So, each time you withdraw Steem from Steemit into your Bittrex account, you have to use your memo id. If you don’t use it, Bittrex will not know where to send your Steem, and you will lose your money. The memo id is like your personal address in Bittrex. It’s your identification. These memo id’s show up in everyone’s account, and because Steemit runs on a blockchain, this data is available for everyone to study. This also means that everyone can see everyone’s account, as all wallets and money transactions are transparent. In fact, you can see all activity on the Steem blockchain, even deleted comments. So, I took a look at @annart’s transactions on the Steem blockchain in order to find a memo id connected to her withdrawal to Bittrex: @annart’s Bittrex memo: (notice the memo id: 462ccc1af1f64901aa8) If you’ve never seen a blockchain before, here’s your chance: And here’s even a more in-depth look at the blockchain structure, when we click on the raw block data: Next, I wanted to find a Bittrex memo id from the other accounts which Sherlock had accused of being run by @annart. Here’s a transaction from @elena2017 and sure enough, the memo id is exactly the same as @annart’s. (notice the memo id: 462ccc1af1f64901aa8) This means the money from these two Steemit accounts is going into the same Bittrex account. In fact, all the fake accounts: @elena2017, @nellyhandmade, @katrinart and use the exact same memo id, , as @annart does. The money from all 5 Steemit accounts is going into 1 Bittrex account. @juliyahandwork 462ccc1af1f64901aa8 The expression, “Follow The Money” applies very well in this case. Sherlock went the extra mile and hunted down all the artists on legacy social media sites (Facebook, Instagram, VK.com) whose identities were thought to be stolen to confirm that they were not on Steemit. All the artists in question told him they were not on Steemit. The @annart account was the only one which never replied to him. It became crystal clear that an elaborate scam ring involving 4 identity thefts was being run by @annart. I did a little extra investigating and discovered that all these accounts tended to upvote each other, too. This was to be expected since getting noticed in Steemit requires upvotes and comments. After using the blockchain to confirm Sherlock’s evidence, I began flagging the posts made by these accounts, thereby taking away any monetary rewards they had made. I tend to avoid flagging people in Steemit unless it’s absolutely necessary, as in this case of an actual identity thief. But my voting and flagging power doesn’t last forever. After flagging more than 15–20 different posts by @elena2017 on top of a regular day’s voting for authors, my voting strength was nearly wiped out. The algorithm that controls this voting strength behavior was created intentionally to prevent abuse from individuals. In my case, because I’ve worked very hard for over a year in Steemit and gained the trust of many in the Steemit community, I wrote (whales in steemit are those who have large accounts and the ability to remove monetary rewards plus lower the reputation of others.) After the news was spread that a scammer had been busted, others swooped in and began flagging the 5 accounts. a post requesting the help of other whales Without the blockchain, none of this fraudulent activity would be possible to know Having access to this immutable blockchain data makes it possible for ordinary citizens to investigate suspicious activity. for certain. This is the real reason why everyone is wetting their pants about right now. the blockchain This has never been possible before, because money transactions have always been hidden away from ordinary citizens…… until now. But make no mistake, the blockchain does not do the work of busting up a scam ring by itself. The blockchain is only a tool. The blockchain is a tool for humans. The blockchain is a tool that can be utilized or ignored. The blockchain is only as useful as the person using it. If the world, and all the people in it stop giving a crap about deception, identity theft, scams, and corruption, guess what? Blockchains become useless. Moreover, if all of us don’t take responsibility for ourselves and society, and always think: “Let someone else take care of it,” blockchains will become useless. One of my Facebook friends remarked after reading about the Ukrainian scam ring: “Scammer from Ukraine? This stinks because there is no system there that will deal with her. Hope your Steem Team blast her!” I answered: “Scams exist everywhere but since all our transactions are transparent on the blockchain, frauds can easily be caught. There is a system: it’s called a passionate community.” A passionate virtual community means people actually giving a shit what happens to people. I never had a tool like the blockchain before and I admit that this is a brand-new powerful combination: Giving a shit + the blockchain = radical change to make society better. It’s quite possible that someone like Trump wouldn’t even be able to coexist in the future world of blockchains. The best part of this story is that Sherlock and I reached out to the real Elena to let her know that her scammer is being punished will soon become a non-entity in Steemit. Furthermore, I have personally invited Elena to Steemit, and hopefully, when she joins, I’ll introduce her to the Steemit community, so people will know that she’s the real deal.

What I Learned About The Blockchain While Helping To Bust An Elaborate Scam in Steemit

In this exclusive interview, Andrey Nayman, co-founder of Magic Square, shares his journey in the blockchain industry and the inspirations behind creating a community-driven App Store. Ishan Pandey: Hi Andrey, great to have you here. To start off, could you share a bit about your background and what inspired you to co-found Magic Square? Andrey Nayman: I've been in the blockchain industry since 2013. My experiences leading various tech companies inspired me to start Magic Square. We're building a community-driven App Store that makes using decentralized apps simpler and safer. I’m passionate about using my blockchain knowledge to create something valuable and innovative for users worldwide. Ishan Pandey: Magic Square offers a unique ecosystem for discovering Web3 projects. Can you explain what sets Magic Store apart from other platforms in the space? Andrey Nayman: Magic Square is all about putting users first. Imagine it like a big online store, but instead of selling physical items, we present Web3 Apps. Magic Store is a way for users to discover all trusted Dapps and engage with them in one place. What makes us different is that we check every app really carefully before putting it in our store. This makes our platform safe and easy to use, whether you're new to Web3 or already an expert. Ishan Pandey: Given the diverse offerings within the Magic Square ecosystem like Magic Karma and Hot Offers, how do these features enhance the user experience and engagement? Andrey Nayman: Magic Karma and Hot Offers are innovative features designed to enhance the user experience on Magic Square. Magic Karma serves as our reputation system – users receive daily rewards for contributing to the Magic Ecosystem, such as trying out new apps or participating in community activities, earning them points. These points can then be exchanged for exciting rewards. On the other hand, Hot Offers form our engagement layer, where users can complete tasks provided by the listed projects and receive real payments for their efforts. Together, these features keep our users happy and engaged while using our platform. Ishan Pandey: The $SQR token plays a central role in the Magic Square community. Could you discuss how it integrates into the ecosystem and what its benefits are for users? Andrey Nayman: The $SQR token is like the heart of Magic Square. Users earn $SQR as a reward for doing things on our platform every day. You can stake $SQR to unlock special benefits if you're a member. You'll get paid in $SQR when you earn rewards through Hot Offers. We also use $SQR to reach the right people in our marketing efforts. To join Launchpad sales, you must stake even more $SQR. So, $SQR is important for everyone using Magic Square. It's what keeps everything running smoothly and helps our community grow. Ishan Pandey: Community-driven platforms depend heavily on user participation. How does Magic Square encourage community involvement in project voting and validation? Andrey Nayman: Community is at the core of every crypto project. At Magic Square, we believe in bringing the crypto community together in one place. Here, users can decide which projects make it onto our platform, shaping their future. Our community moderators actively gather feedback, which our product team uses to create a roadmap aligned with their needs. To make our community feel valued and engaged, we offer daily rewards through Karma Points and exciting opportunities through Hot Offers. We also host regular surveys where users can share their ideas and feedback, ensuring our platform evolves based on their input. Ishan Pandey: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Can you elaborate on how this program works and what its advantages are for both users and developers? Andrey Nayman: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Here's how it works: Users can easily monetize their communities by sharing affiliate offers from listed projects. With one click, they share these offers on social media. When their friends engage and convert, users receive instant payouts. This benefits the user by allowing them to earn effortlessly while supporting their favorite projects. For developers, Magic Boost expands their reach and boosts user acquisition, enhancing app visibility and credibility. Ishan Pandey: Looking forward, what are some key developments or milestones that the Magic Square community can anticipate in the near future? Andrey Nayman: In the near future, our Launchpad will be a big focus. It's designed to help projects grow steadily and connect with our community. We'll customize our approach, using both public and private sales, to give projects the best chance of success. With our active community, we'll make sure these projects get plenty of attention. Stay tuned for more updates as we work together to shape the future of Web3! Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. In this exclusive interview, Andrey Nayman, co-founder of Magic Square, shares his journey in the blockchain industry and the inspirations behind creating a community-driven App Store. Ishan Pandey: Hi Andrey, great to have you here. To start off, could you share a bit about your background and what inspired you to co-found Magic Square? Ishan Pandey: Hi Andrey, great to have you here. To start off, could you share a bit about your background and what inspired you to co-found Magic Square? Ishan Pandey: Hi Andrey, great to have you here. To start off, could you share a bit about your background and what inspired you to co-found Magic Square? Andrey Nayman: I've been in the blockchain industry since 2013. My experiences leading various tech companies inspired me to start Magic Square. We're building a community-driven App Store that makes using decentralized apps simpler and safer. I’m passionate about using my blockchain knowledge to create something valuable and innovative for users worldwide. Andrey Nayman: Ishan Pandey: Magic Square offers a unique ecosystem for discovering Web3 projects. Can you explain what sets Magic Store apart from other platforms in the space? Ishan Pandey: Magic Square offers a unique ecosystem for discovering Web3 projects. Can you explain what sets Magic Store apart from other platforms in the space? Ishan Pandey: Magic Square offers a unique ecosystem for discovering Web3 projects. Can you explain what sets Magic Store apart from other platforms in the space? Andrey Nayman: Magic Square is all about putting users first. Imagine it like a big online store, but instead of selling physical items, we present Web3 Apps. Magic Store is a way for users to discover all trusted Dapps and engage with them in one place. What makes us different is that we check every app really carefully before putting it in our store. This makes our platform safe and easy to use, whether you're new to Web3 or already an expert. Andrey Nayman: Ishan Pandey: Given the diverse offerings within the Magic Square ecosystem like Magic Karma and Hot Offers, how do these features enhance the user experience and engagement? Ishan Pandey: Given the diverse offerings within the Magic Square ecosystem like Magic Karma and Hot Offers, how do these features enhance the user experience and engagement? Ishan Pandey: Given the diverse offerings within the Magic Square ecosystem like Magic Karma and Hot Offers, how do these features enhance the user experience and engagement? Andrey Nayman: Magic Karma and Hot Offers are innovative features designed to enhance the user experience on Magic Square. Magic Karma serves as our reputation system – users receive daily rewards for contributing to the Magic Ecosystem, such as trying out new apps or participating in community activities, earning them points. These points can then be exchanged for exciting rewards. On the other hand, Hot Offers form our engagement layer, where users can complete tasks provided by the listed projects and receive real payments for their efforts. Together, these features keep our users happy and engaged while using our platform. Andrey Nayman: Ishan Pandey: The $SQR token plays a central role in the Magic Square community. Could you discuss how it integrates into the ecosystem and what its benefits are for users? Ishan Pandey: The $SQR token plays a central role in the Magic Square community. Could you discuss how it integrates into the ecosystem and what its benefits are for users? Ishan Pandey: The $SQR token plays a central role in the Magic Square community. Could you discuss how it integrates into the ecosystem and what its benefits are for users? Andrey Nayman: The $SQR token is like the heart of Magic Square. Users earn $SQR as a reward for doing things on our platform every day. You can stake $SQR to unlock special benefits if you're a member. You'll get paid in $SQR when you earn rewards through Hot Offers. We also use $SQR to reach the right people in our marketing efforts. Andrey Nayman: To join Launchpad sales, you must stake even more $SQR. So, $SQR is important for everyone using Magic Square. It's what keeps everything running smoothly and helps our community grow. Ishan Pandey: Community-driven platforms depend heavily on user participation. How does Magic Square encourage community involvement in project voting and validation? Ishan Pandey: Community-driven platforms depend heavily on user participation. How does Magic Square encourage community involvement in project voting and validation? Ishan Pandey: Community-driven platforms depend heavily on user participation. How does Magic Square encourage community involvement in project voting and validation? Andrey Nayman: Community is at the core of every crypto project. At Magic Square, we believe in bringing the crypto community together in one place. Here, users can decide which projects make it onto our platform, shaping their future. Our community moderators actively gather feedback, which our product team uses to create a roadmap aligned with their needs. To make our community feel valued and engaged, we offer daily rewards through Karma Points and exciting opportunities through Hot Offers. We also host regular surveys where users can share their ideas and feedback, ensuring our platform evolves based on their input. Andrey Nayman: Ishan Pandey: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Can you elaborate on how this program works and what its advantages are for both users and developers? Ishan Pandey: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Can you elaborate on how this program works and what its advantages are for both users and developers? Ishan Pandey: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Can you elaborate on how this program works and what its advantages are for both users and developers? Andrey Nayman: Affiliate programs are common in Web3, but Magic Boost offers a unique twist. Here's how it works: Users can easily monetize their communities by sharing affiliate offers from listed projects. With one click, they share these offers on social media. When their friends engage and convert, users receive instant payouts. This benefits the user by allowing them to earn effortlessly while supporting their favorite projects. For developers, Magic Boost expands their reach and boosts user acquisition, enhancing app visibility and credibility. Andrey Nayman: Ishan Pandey: Looking forward, what are some key developments or milestones that the Magic Square community can anticipate in the near future? Ishan Pandey: Looking forward, what are some key developments or milestones that the Magic Square community can anticipate in the near future? Ishan Pandey: Looking forward, what are some key developments or milestones that the Magic Square community can anticipate in the near future? Andrey Nayman: In the near future, our Launchpad will be a big focus. It's designed to help projects grow steadily and connect with our community. We'll customize our approach, using both public and private sales, to give projects the best chance of success. With our active community, we'll make sure these projects get plenty of attention. Stay tuned for more updates as we work together to shape the future of Web3! Andrey Nayman: Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

Andrey Nayman Reveals the Vision Behind Magic Square's Unique Web3 Ecosystem

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Question about plasma, a state of matter *: my teacher said that plasma is the fourth state of matter. but isn't plasma that thing they inject into a vein in the hospital?* P1 *: Your teacher is correct, and I understand the confusion. The term "plasma" is used in both physics and medicine, but they refer to entirely different concepts. Let's break them down:* ChatGPT ***1. Plasma (State of Matter): *** • In physics, plasma is often referred to as the "fourth state of matter" after solids, liquids, and gases. • Plasma is like a gas but with some key differences. In plasma, a significant number of atoms are ionized, meaning they have lost or gained electrons. This gives plasma unique properties, like the ability to conduct electricity and respond strongly to electromagnetic fields. • Examples of plasmas include the sun, lightning, and neon signs. The sun is essentially a giant ball of plasma, with hydrogen atoms undergoing fusion to form helium, releasing a tremendous amount of energy in the process. ***2. Plasma (Biological): *** • In a biological or medical context, plasma refers to the clear, yellowish fluid component of blood. It's what's left after you remove the red and white blood cells and platelets from blood. • Plasma makes up about 55% of total blood volume and contains water, salts, enzymes, hormones, and waste products. It serves as a transport medium for delivering nutrients to the cells and carrying waste products away. • When people donate "plasma" at a donation center, they're donating this component of their blood. So, while the terms are the same, the contexts are quite different. It's essential to know which "plasma" is being referred to based on the topic of discussion. Does this distinction between the two concepts of plasma clear things up for you? *: That’s a very good question. Plasma is indeed the fourth state of matter, but it is also a term used in medicine to describe the liquid part of blood. Let me explain the difference between these two types of plasma.* BingChat Plasma as a state of matter is a gas that has been heated or electrified to the point where some or all of its atoms lose their electrons. This creates a mixture of positively charged ions and negatively charged electrons that can conduct electricity and respond to magnetic fields. Plasma is very common in the universe, as it makes up most of the stars, including the sun. Plasma is also found in lightning, neon lights, and plasma displays[ ]. 123 Plasma as a part of blood is a yellowish fluid that carries water, salts, enzymes, proteins, hormones, and other substances throughout the body. It also helps with immunity, blood clotting, blood pressure, and pH balance. Plasma can be donated to help people who have lost blood due to injury, surgery, or disease. Plasma can also be used to make medicines for people who have certain conditions that affect their blood[ ] 456 So, as you can see, plasma can mean different things depending on the context. Both types of plasma are important for life and science, but they are not the same thing. I hope this helps you understand the difference between plasma as a state of matter and plasma as a part of blood. *: Yes, plasma is the fourth state of matter. It is a highly energized state of matter in which some or all of the atoms have been stripped of one or more of their electrons. This results in a gas of positively charged ions and negatively charged electrons.* Bard Plasma is the most abundant form of matter in the universe, accounting for over 99% of the visible universe. It is found in stars, nebulae, and other celestial objects. Plasma is also found on Earth, in lightning bolts, auroras, and other natural phenomena. Plasma is also used in a variety of industrial applications, such as welding, plasma cutting, and semiconductor manufacturing. The plasma that is injected into veins in the hospital is a type of blood plasma. Blood plasma is the liquid portion of blood that remains after the red blood cells, white blood cells, and platelets have been removed. It is a yellowish liquid that contains proteins, antibodies, and other nutrients. Blood plasma is used to treat a variety of medical conditions, including dehydration, malnutrition, and shock. It is also used to make plasma products, such as albumin and immunoglobulin. So, to summarize, plasma is both the fourth state of matter and a type of blood plasma. The two are not related, but they both have important roles. I hope this helps to clarify things. Please let me know if you have any other questions. *: Great observation! Plasma does indeed have two different meanings in science:* Claude 1. In chemistry and physics, plasma is considered the fourth state of matter, distinct from solids, liquids and gases. Plasma consists of highly ionized gas containing a mix of free electrons, positive ions, and neutral atoms. It can be created by heating a gas to very high temperatures. Natural examples include lightning and the Sun. 2. In medicine, plasma refers to the liquid portion of blood that contains proteins, nutrients, and ions like sodium and chloride. This plasma carries blood cells and helps regulate bodily processes. It makes up about 55% of total blood volume. So in summary: • Scientific plasma is a distinct state of ionized gas, created at extremely high temps. • Medical plasma is the liquid part of blood that suspends blood cells and transports useful substances. While both are important in their respective fields, they have very different definitions and properties. The medical usage of the term is probably more familiar to most people. But the concept of plasma as a state of matter is critical in physics and chemistry when studying things like nuclear fusion reactions. Let me know if this explanation helps differentiate the two meanings! It's an important distinction to understand. ChatGPT starts reassuringly with “Your teacher is correct” and "I understand the confusion," providing . It then proceeds to , addressing the need to differentiate the two meanings systematically with "Let's break them down" and expounding extensively a clear distinction between plasma as the fourth state of matter and blood plasma in the medical context with , as well as with the , recurring to real-world examples to explain the concept, like the “sun, lightning, and neon signs” as well as of people donating “‘plasma’ at a donation center”. It ends the explanation with Engagement & Interactivity by asking "Does this distinction ... clear things up for you?", inviting a response. also starts by giving positive feedback and personal recognition of the user's query with “That’s a very good question," providing . It then proceeds to with "Let me explain the difference," setting the tone for a structured explanation with strategy that contextualizes the significance of both plasmas in the universe and medical science, the referencing the sun, “lightning, neon lights, and plasma displays”, and links to external resources, offering It ends with , emphasizing the significance of the dual meaning of the word, by affirming that "Both types of plasma are important for life and science" and “I hope this helps you understand the difference” followed by an emoticon for a friendly touch of Engagement & Interactivity. Bard begins its Instructional Strategies with the straightforward “Yes” affirmation followed by a detailed distinction of both concepts with Detail Depth & Content Recommendation, progressing from the Use of Analogy & Comparative Illustrations with examples of “lightning bolts, auroras, and other natural phenomena” to a discussing the broader applications “in a variety of industrial applications, such as welding, plasma cutting, and semiconductor manufacturing”, as well “to treat a variety of medical conditions, including dehydration, malnutrition, and shock” to make products, “such as albumin and immunoglobulin”. It ends with in "Please let me know if you have any other questions" and with "I hope this helps to clarify things." initiates its response with a straightforward affirmation, "Yes", demonstrating its Instructional Strategies. It then elaborates in depth about the concepts, highlighting Detail Depth & Content Recommendation. Utilizing the , it gives examples like “lightning bolts, auroras, and other natural phenomena”. Venturing into , it underlines the broader applications in sectors such as “welding, plasma cutting, and semiconductor manufacturing”, and the medical utility “to treat a variety of medical conditions, including dehydration, malnutrition, and shock” and the creation of products like “albumin and immunoglobulin”. Wrapping up, it imparts a with "I hope this helps to clarify things” and fosters with "Please let me know if you have any other questions." also appreciates the user's observation with "Great observation!" demonstrating . It then turns to Instructional Strategies to make a clear distinction between the concepts, utilizing the by giving the examples of “lightning” and the “Sun”. Expanding into , it underlines the concept “is critical in physics and chemistry” with applications to “nuclear fusion reactions”. It ends with a with “Let me know if this explanation helps” and provides , by affirming that “It's an important distinction to understand.” Personalization & Personable Touch Instructional Strategies Detail Depth & Content Recommendation Use of Analogy & Comparative Illustrations BingChat Personalization & Personable Touch Instructional Strategies Meta-discussion & Perspective Framing Use of Analogy & Comparative Illustrations, Detail Depth & Content Recommendation. Reinforcement & Feedback Meta-discussion & Perspective Framing Engagement & Interactivity Personalization & Personable Touch Bard Use of Analogy & Comparative Illustrations Meta-discussion & Perspective Framing Personalization & Personable Touch Engagement & Interactivity Claude Personalization & Personable Touch Use of Analogy & Comparative Illustrations Meta-discussion & Perspective Framing Personalization & Personable Touch Meta-discussion & Perspective Framing This paper is under CC BY-SA 4.0 DEED license. available on arxiv

GenAIbots Answer Questions About Plasma, a State of Matter

GenAIbots প্লাজমা সম্পর্কে প্রশ্নের উত্তর দেয়, একটি পদার্থের অবস্থা

GenAIbots beantworten Fragen zu Plasma, einem Materiezustand

GenAIbots responde preguntas sobre el plasma, un estado de la materia

Les GenAIbots répondent aux questions sur le plasma, un état de la matière

GenAIbots पदार्थ की एक अवस्था, प्लाज्मा के बारे में सवालों के जवाब देते हैं

GenAIbotsがプラズマという物質の状態に関する疑問に答える

GenAIbots는 물질의 상태인 플라즈마에 관한 질문에 답변합니다.

GenAIbots respondem a perguntas sobre o plasma, um estado da matéria

GenAIbots отвечают на вопросы о плазме — состоянии материи

GenAIbot'lar Maddenin Bir Hali Olan Plazma Hakkında Soruları Yanıtlıyor

GenAIbots trả lời các câu hỏi về Plasma, một trạng thái của vật chất

GenAIbots 回答有关等离子体（物质的一种状态）的问题

Authors:
(1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Materials And Methods This study aimed to assess the efficacy of GenAIbots, including ChatGPT, Bing Chat, Bard, and Claude, as tools to augment Chemistry learning when characterised as agents-to-think-with. Chemistry students can harness the capabilities of GenAIbots in diverse ways to elevate their academic journey. They can pose complex questions to obtain thorough explanations on difficult subjects, leverage the bot as a supplemental aid for challenging areas, or seek visual aids—including images, graphs, simulations, or even interactive games—to enhance their understanding of chemical concepts. Additionally, they can seek clarity on laboratory protocols or engage in interactive discussions to solidify their understanding. In this article, we specifically hone in on GenAIbots' utility as agents-to-think-with, virtual intelligent tutors addressing students' doubts, rectifying misconceptions, and providing in-depth insights into complex concepts. Our focus also centres on the primary challenges encountered by Chemistry students, as highlighted by Timilsena et al. (2022), encompassing chemical reactions, chemical equilibrium, phase changes, gases, stoichiometry, atoms and molecules, acids and bases, and covalent bonding. We undertook a comprehensive single case study, aligning with Yin's (2011) guidelines, to evaluate and contrast the performance of ChatGPT, Bing Chat, Bard, and Claude. In analysing the responses of these AI systems, we adopted the Content Analysis methodology according to Bardin (1977) to delve into participants' experiences and viewpoints. This method offers insightful observations on student interactions with these GenAIbots. Prompting, the process of giving instructions, is crucial in interacting with language models. The process of meticulously precise, well-crafted sentences that elicit meaningful and valuable responses, or prompt-crafting, as Mishra et al. (2023) call it, is crucial for ensuring deep iterative reflections and engagements with GenAIbots as agents-to-think-with. Mollick (2023) offers a comprehensive guide to prompting, complete with detailed annotations and expanded examples. Two illustrative examples of prompt, crafted by ChatGPT itself, is presented below. The second one adds the intention of fostering profound iterative reflections and engagement in chemistry learning: Please provide a clear and comprehensible explanation of the various types of chemical bonding (ionic, covalent, and hydrogen), covering the theoretical concepts behind them and offering real-world examples suitable for an undergraduate student’s understanding. In the realm of chemistry, the concept of chemical bonding can be intricate, blending both theoretical principles and real-world applications. Walk me through the nuances of covalent, ionic, and hydrogen bonds. Additionally, challenge me with thought-provoking questions and analogies that can help solidify my understanding and encourage further exploration. The initial prompt in the upcoming dialogue, refined through a series of AI experiments, serves as another example of engaging in a meaningful conversation with the GenAIbot rather than asking isolated questions that might merely yield standard textbook responses. Nevertheless, while this initial prompt serves to 'set the stage' for the dialogue, the subsequent interactions with the simulated student are more straightforward and devoid of any elaborate prompting. This design reflects a typical student's approach: they may lack expertise in crafting detailed prompts and simply seek answers to their chemistry doubts. The dialogue intends to capture this organic flow of inquiry rather than a meticulously structured question sequence. GenAIbots can maintain context within a particular session, drawing upon and building on topics or responses discussed earlier. Even if a user returns to a previously accessed session that has not been deleted, the chatbot can still recall and refer to past interactions from that session. This continuity lets users pick up right where they left off, facilitating a more seamless and cohesive conversation. However, it's crucial to understand that this retention is exclusive to the individual session and doesn't transfer to separate chat sessions, ensuring user privacy and data security. Dunlop et al. (2020) highlight the absence of philosophical dialogue in Chemistry Education and propose its integration into Higher Education. GenAIbots like ChatGPT, Bing Chat, Bard, and Claude can facilitate Socratic-like, philosophical dialogues, encouraging user reflection, critical thinking and a deeper understanding of Chemistry's principles, assumptions, and ethical implications. GenAIbots can bridge the gap between theory and practice by promoting meaningful discussions and providing a holistic educational experience. Using GenAIbots as agents-to-think-with is new and innovative. Consequently, finding teachers willing to incorporate it into their classrooms for experimental purposes has been challenging. Due to this, the investigation did not involve real students. Instead, the researcher, acting as a STEM teacher at a Brazilian university, assumed the role of a student (identified as P1) in the interaction sessions. Empathy was incorporated into the research methodology to enable the researchers to act like students and understand their perspectives. Four sessions were held, each emulating the learning experiences of Chemistry students using ChatGPT, Bing Chat, Bard, or Claude and focusing on their main difficulties, as discussed above. After the initial prompt to engage in a meaningful conversation with the GenAIbot and characterise the agents intervening in the dialogue, a simulated student begins in the dialogues with the widely recognised difficulty of balancing chemical reactions. The discussion then evolves in a somewhat unstructured order, where the response to the previous one inspires each new question. Data collection involved GenAIbot interaction logs, which recorded the participant's prompts and responses, and reflective journals maintained by the participant. These materials were later analysed to identify recurring themes and patterns, shedding light on the perceived impact of GenAIbots as an agent-to-think-with in Chemistry learning. From the initial readings of the participant's prompts and responses and reflective journals, the following seven categories of analysis emerged: 1. Instructional Strategies: o Methods used by AI to impart knowledge. 2. Engagement & Interactivity: o Prompting critical thinking and further exploration. o Asking questions, inviting responses, and encouraging deeper dives. 3. Use of Analogy & Comparative Illustrations: o Using parallels, metaphors, and real-world examples to explain concepts. 4. Reinforcement & Feedback: o Recognizing and affirming user input. o Correcting or building upon user understanding. o Reiteration of essential concepts. 5. Detail Depth & Content Recommendation: o The extent of detail provided, whether it's concise or expansive. o Suggesting additional learning materials and providing relevant content. 6. Personalization & Personable Touch: o Tailoring responses to individual needs. o Using emoticons, casual tones, or other elements for a more personalised feel. 7. Meta-discussion & Perspective Framing: o Addressing the broader relevance of concepts outside strict contexts. o Contextualizing abstract concepts using familiar frameworks. These categories will be used to comparatively analyse the answers of each GenAIbot to the individual participant’s questions below. This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Authors: Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Abstract and Introduction Materials And Methods Materials And Methods Results and Analyses Results and Analyses Prompts and generated texts Prompts and generated texts Conceptualizing chemical reactions Conceptualizing chemical reactions Deepening on understanding of chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about combustion Question about a graph of gases turning into water over time Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Deepening on the concept of mole Question about changing of state Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about plasma, a state of matter Question about chemical bondings Question about chemical bondings Question about illustration of chemical bonds Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Question about the essence of the type of chemical bonding Further analysis Further analysis Conclusions Conclusions Limitations of the study and possible future studies Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Author Contributions, Conflicts of interest, Acknowledgements, and References Materials And Methods This study aimed to assess the efficacy of GenAIbots, including ChatGPT, Bing Chat, Bard, and Claude, as tools to augment Chemistry learning when characterised as agents-to-think-with. Chemistry students can harness the capabilities of GenAIbots in diverse ways to elevate their academic journey. They can pose complex questions to obtain thorough explanations on difficult subjects, leverage the bot as a supplemental aid for challenging areas, or seek visual aids—including images, graphs, simulations, or even interactive games—to enhance their understanding of chemical concepts. Additionally, they can seek clarity on laboratory protocols or engage in interactive discussions to solidify their understanding. In this article, we specifically hone in on GenAIbots' utility as agents-to-think-with, virtual intelligent tutors addressing students' doubts, rectifying misconceptions, and providing in-depth insights into complex concepts. Our focus also centres on the primary challenges encountered by Chemistry students, as highlighted by Timilsena et al. (2022), encompassing chemical reactions, chemical equilibrium, phase changes, gases, stoichiometry, atoms and molecules, acids and bases, and covalent bonding. We undertook a comprehensive single case study, aligning with Yin's (2011) guidelines, to evaluate and contrast the performance of ChatGPT, Bing Chat, Bard, and Claude. In analysing the responses of these AI systems, we adopted the Content Analysis methodology according to Bardin (1977) to delve into participants' experiences and viewpoints. This method offers insightful observations on student interactions with these GenAIbots. Prompting, the process of giving instructions, is crucial in interacting with language models. The process of meticulously precise, well-crafted sentences that elicit meaningful and valuable responses, or prompt-crafting, as Mishra et al. (2023) call it, is crucial for ensuring deep iterative reflections and engagements with GenAIbots as agents-to-think-with. Mollick (2023) offers a comprehensive guide to prompting, complete with detailed annotations and expanded examples. Two illustrative examples of prompt, crafted by ChatGPT itself, is presented below. The second one adds the intention of fostering profound iterative reflections and engagement in chemistry learning: Please provide a clear and comprehensible explanation of the various types of chemical bonding (ionic, covalent, and hydrogen), covering the theoretical concepts behind them and offering real-world examples suitable for an undergraduate student’s understanding. Please provide a clear and comprehensible explanation of the various types of chemical bonding (ionic, covalent, and hydrogen), covering the theoretical concepts behind them and offering real-world examples suitable for an undergraduate student’s understanding. In the realm of chemistry, the concept of chemical bonding can be intricate, blending both theoretical principles and real-world applications. Walk me through the nuances of covalent, ionic, and hydrogen bonds. Additionally, challenge me with thought-provoking questions and analogies that can help solidify my understanding and encourage further exploration. In the realm of chemistry, the concept of chemical bonding can be intricate, blending both theoretical principles and real-world applications. Walk me through the nuances of covalent, ionic, and hydrogen bonds. Additionally, challenge me with thought-provoking questions and analogies that can help solidify my understanding and encourage further exploration. The initial prompt in the upcoming dialogue, refined through a series of AI experiments, serves as another example of engaging in a meaningful conversation with the GenAIbot rather than asking isolated questions that might merely yield standard textbook responses. Nevertheless, while this initial prompt serves to 'set the stage' for the dialogue, the subsequent interactions with the simulated student are more straightforward and devoid of any elaborate prompting. This design reflects a typical student's approach: they may lack expertise in crafting detailed prompts and simply seek answers to their chemistry doubts. The dialogue intends to capture this organic flow of inquiry rather than a meticulously structured question sequence. GenAIbots can maintain context within a particular session, drawing upon and building on topics or responses discussed earlier. Even if a user returns to a previously accessed session that has not been deleted, the chatbot can still recall and refer to past interactions from that session. This continuity lets users pick up right where they left off, facilitating a more seamless and cohesive conversation. However, it's crucial to understand that this retention is exclusive to the individual session and doesn't transfer to separate chat sessions, ensuring user privacy and data security. Dunlop et al. (2020) highlight the absence of philosophical dialogue in Chemistry Education and propose its integration into Higher Education. GenAIbots like ChatGPT, Bing Chat, Bard, and Claude can facilitate Socratic-like, philosophical dialogues, encouraging user reflection, critical thinking and a deeper understanding of Chemistry's principles, assumptions, and ethical implications. GenAIbots can bridge the gap between theory and practice by promoting meaningful discussions and providing a holistic educational experience. Using GenAIbots as agents-to-think-with is new and innovative. Consequently, finding teachers willing to incorporate it into their classrooms for experimental purposes has been challenging. Due to this, the investigation did not involve real students. Instead, the researcher, acting as a STEM teacher at a Brazilian university, assumed the role of a student (identified as P1) in the interaction sessions. Empathy was incorporated into the research methodology to enable the researchers to act like students and understand their perspectives. Four sessions were held, each emulating the learning experiences of Chemistry students using ChatGPT, Bing Chat, Bard, or Claude and focusing on their main difficulties, as discussed above. After the initial prompt to engage in a meaningful conversation with the GenAIbot and characterise the agents intervening in the dialogue, a simulated student begins in the dialogues with the widely recognised difficulty of balancing chemical reactions. The discussion then evolves in a somewhat unstructured order, where the response to the previous one inspires each new question. Data collection involved GenAIbot interaction logs, which recorded the participant's prompts and responses, and reflective journals maintained by the participant. These materials were later analysed to identify recurring themes and patterns, shedding light on the perceived impact of GenAIbots as an agent-to-think-with in Chemistry learning. From the initial readings of the participant's prompts and responses and reflective journals, the following seven categories of analysis emerged: 1. Instructional Strategies: 1. Instructional Strategies: o Methods used by AI to impart knowledge. 2. Engagement & Interactivity: 2. Engagement & Interactivity: o Prompting critical thinking and further exploration. o Asking questions, inviting responses, and encouraging deeper dives. 3. Use of Analogy & Comparative Illustrations: 3. Use of Analogy & Comparative Illustrations: o Using parallels, metaphors, and real-world examples to explain concepts. 4. Reinforcement & Feedback: 4. Reinforcement & Feedback: o Recognizing and affirming user input. o Correcting or building upon user understanding. o Reiteration of essential concepts. 5. Detail Depth & Content Recommendation: 5. Detail Depth & Content Recommendation: o The extent of detail provided, whether it's concise or expansive. o Suggesting additional learning materials and providing relevant content. 6. Personalization & Personable Touch: 6. Personalization & Personable Touch: o Tailoring responses to individual needs. o Using emoticons, casual tones, or other elements for a more personalised feel. 7. Meta-discussion & Perspective Framing: 7. Meta-discussion & Perspective Framing: o Addressing the broader relevance of concepts outside strict contexts. o Contextualizing abstract concepts using familiar frameworks. These categories will be used to comparatively analyse the answers of each GenAIbot to the individual participant’s questions below. This paper is available on arxiv under CC BY-SA 4.0 DEED license. This paper is available on arxiv under CC BY-SA 4.0 DEED license. available on arxiv

Analyzing GenAIbots' Efficacy in Chemistry Education

How Jonas Simanavicius Went from J.P. Morgan to Revolutionizing Web3 with Synternet

কীভাবে জোনাস সিমানাভিসিয়াস জেপি মরগান থেকে সিন্টারনেটের সাথে ওয়েব 3 বিপ্লবে গিয়েছিলেন

Wie Jonas Simanavicius von J.P. Morgan dazu kam, mit Synternet das Web3 zu revolutionieren

Cómo Jonas Simanavicius pasó de J.P. Morgan a revolucionar Web3 con Synternet

Comment Jonas Simanavicius est passé de J.P. Morgan à révolutionner le Web3 avec Synternet

जोनास सिमनाविसियस ने जे.पी. मॉर्गन से सिंटर्नेट के साथ वेब3 में क्रांति कैसे ला दी

ジョナス・シマナヴィチウスがJ.P.モルガンからSynternetに移り、Web3に革命を起こした経緯

Jonas Simanavicius가 J.P. Morgan에서 Synternet을 통해 Web3에 혁신을 가져온 방법

Como Jonas Simanavicius passou do J.P. Morgan para revolucionar a Web3 com a Synternet

Как Йонас Симанавичюс прошел путь от J.P. Morgan до революции в Web3 с помощью Synternet

Jonas Simanavicius, J.P. Morgan'dan Synternet ile Web3'te Devrim Yaratmaya Nasıl Geçti?

Jonas Simanavicius đã đi từ J.P. Morgan đến cách mạng hóa Web3 bằng Synternet như thế nào

Jonas Simanavicius 如何从摩根大通走出来，用 Synternet 革新 Web3

In this session of our "Behind the Startup" series, we sit down with Zad, the visionary founder of OpenCred, to explore the revolutionary concept of tokenizing trust in the Web3 environment. As a Stanford-certified expert in blockchain and cryptography, Zad discusses the inception of OpenCred, its unique approach to digital identity through eSFT tokens, and its ambitious mission to reshape social and economic interactions online. Ishan Pandey: Hi Zad, great to have you here for our "Innovators in Web3" series. Can you tell us about your background and what led you to create OpenCred? Zad: As a postgraduate in Blockchain Strategy and Stanford-certified cryptography expert, I have spent years conducting cutting-edge research in asset tokenization, DID, and cybersecurity. Trust is actually one of the most difficult things to measure and quantify, no matter “IRL” or online. Now with blockchain and tokens we finally have the tools to tackle this problem in a novel way. I founded OpenCred to bring tokenized trust to the Web3 industry, unleash the hidden potential that lies in social relationships, and eventually enable the establishment of a decentralized society. Ishan Pandey: Could you start by explaining what OpenCred is and what specific gap in the Web3 space it aims to fill? Zad: OpenCred is a decentralized Web3 credit protocol that applies a new token standard called “eSFT” to tokenize trust relationships into tangible and quantifiable economic assets. Our vision is to empower users to monetize their online activity while guaranteeing data privacy and ownership. By providing a blockchain-based solution for establishing and measuring trust relationships, OpenCred fills a crucial gap in the Web3 ecosystem: enabling trustworthy interactions and collaboration without relying on centralized intermediaries or KYC. Ishan Pandey: In the deck, you mention that OpenCred introduces a groundbreaking trust value (credit) quantification for Web3. Can you elaborate on how this works and why it's important? Zad: OpenCred aggregates both on-chain (e.g., DeFi TVL, smart contract interactions) and off-chain data (e.g., social media followers and interactions) to tokenize trust in the form of CRED tokens. This means users can increase their personal trust value by increasing their online activity and footprint. Each CRED is unique to the user and contains a number of fungible Score Tokens (ST) that determine the value of a user’s CRED. By thus providing a measurable and objective way to assess trustworthiness, OpenCred enables secure, traceable, and efficient trust-based interactions in various Web3 applications, such as social media, e-commerce, DeFi, and gaming. This groundbreaking mechanism is crucial for fostering a trustworthy environment in the digital space and enabling countless new use cases in many areas from B2B to B2C to C2B to C2C. Ishan Pandey: The CRED token seems to be a key component of the OpenCred ecosystem. Can you explain its dual nature as a semi-fungible token and how it represents both identity and trustworthiness? And how does this design benefit users of your platform? Zad: CRED tokens are a groundbreaking innovation of OpenCred, creating a new token standard we call embedded semi-fungible token (eSFT) that combines both non-fungible (unique) and fungible (interchangeable) properties. The non-fungible part of the token represents a user's unique identity within the OpenCred protocol, ensuring that each user has a distinct and verifiable presence. On the other hand, the fungible part of the token quantifies the user's trustworthiness, which is determined by their interactions (on-chain & off-chain) and the amount of CRED tokens they receive from others. This design benefits users by empowering them to monetize their online activity and social relationships. Moreover, by tokenizing trust and making it quantifiable and tangible, we are creating a new kind of asset that simply has not existed before, thereby creating huge value. Ishan Pandey: How does sending CRED between users facilitate the building of a trustable and quantifiable social graph in Web3? Zad: When a user sends CRED tokens to another user, they are essentially establishing a trust relationship that is recorded on the blockchain. This transaction signifies that the sender trusts the recipient to a certain degree, based on their interactions, reputation, or other factors. As users continue to interact and send CRED tokens to each other, a dynamic, evolving on-chain social graph emerges. The social graph is quantifiable and traceable. This quantification of trust enables users to make informed decisions when interacting with others, as they can assess the trustworthiness of potential collaborators, partners, or service providers based on their position in the social graph. Ishan Pandey: With OpenCred positioning itself as a provider of "Trust as a Service," how do you ensure the reliability and security of the trust metrics generated by your protocol? Zad: There is a clear friction between incentivizing users on the one hand and ensuring the authenticity of trust relationships on the other hand. We are aware of this and will tackle this problem in multiple ways. First of all, we will connect the sending of CRED with some actions such as “follow”, “like”, etc., so that the transfer of CRED corresponds with the establishment of a meaningful trust relationship. Secondly, we will implement punishments for sybil attackers and other malicious behavior. Additionally, OpenCred implements a multi-layered governance model that involves community participation and decentralized decision-making. This approach helps to maintain the integrity and fairness of the trust metrics, as the community can collectively monitor and flag any suspicious activities or attempts to manipulate trust scores. To further enhance the reliability of trust metrics, OpenCred incorporates a reputation staking mechanism, where users are required to stake a portion of our governance tokens to participate in trust-building activities. OpenCred places a strong emphasis on user education and awareness. By providing clear guidelines, tutorials, and best practices for using the trust protocol. Ishan Pandey: How do you plan to drive adoption and grow the OpenCred ecosystem, particularly in terms of attracting both users and developers? Zad: OpenCred actively seeks partnerships and collaborations with established Web3 projects across various sectors, such as social media, e-commerce, gaming, and decentralized finance (DeFi). We currently have established partnerships with over 10 Web3 projects with close to 1 million daily active users ready to onboard our protocol once it is live. To attract developers, OpenCred will provide a range of tools, SDKs, and documentation to facilitate the integration of its trust protocol into various applications. The protocol will offer developer grants, hackathons, and bounty programs to incentivize the creation of innovative trust-based solutions. By fostering a vibrant developer community and providing the necessary resources and support, OpenCred aims to accelerate the development of a diverse range of dApps that leverage its trust infrastructure. OpenCred's tokenomics model is designed to incentivize user participation and ecosystem growth. The governance token serves as the primary means of interaction within the OpenCred ecosystem, used for establishing trust relationships, staking, and accessing trust-based services. The protocol will implement a reward system that incentivizes users to actively participate in trust-building activities, such as providing accurate trust assessments, staking tokens, and contributing to the network's security. These incentives will drive user adoption and encourage long-term engagement with the OpenCred ecosystem. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. In this session of our "Behind the Startup" series, we sit down with Zad, the visionary founder of OpenCred, to explore the revolutionary concept of tokenizing trust in the Web3 environment. As a Stanford-certified expert in blockchain and cryptography, Zad discusses the inception of OpenCred, its unique approach to digital identity through eSFT tokens, and its ambitious mission to reshape social and economic interactions online. Ishan Pandey: Hi Zad, great to have you here for our "Innovators in Web3" series. Can you tell us about your background and what led you to create OpenCred? Ishan Pandey: Zad: As a postgraduate in Blockchain Strategy and Stanford-certified cryptography expert, I have spent years conducting cutting-edge research in asset tokenization, DID, and cybersecurity. Trust is actually one of the most difficult things to measure and quantify, no matter “IRL” or online. Now with blockchain and tokens we finally have the tools to tackle this problem in a novel way. I founded OpenCred to bring tokenized trust to the Web3 industry, unleash the hidden potential that lies in social relationships, and eventually enable the establishment of a decentralized society. Zad: Ishan Pandey: Could you start by explaining what OpenCred is and what specific gap in the Web3 space it aims to fill? Ishan Pandey: Zad: OpenCred is a decentralized Web3 credit protocol that applies a new token standard called “eSFT” to tokenize trust relationships into tangible and quantifiable economic assets. Our vision is to empower users to monetize their online activity while guaranteeing data privacy and ownership. By providing a blockchain-based solution for establishing and measuring trust relationships, OpenCred fills a crucial gap in the Web3 ecosystem: enabling trustworthy interactions and collaboration without relying on centralized intermediaries or KYC. Zad: Ishan Pandey: In the deck, you mention that OpenCred introduces a groundbreaking trust value (credit) quantification for Web3. Can you elaborate on how this works and why it's important? Ishan Pandey: Zad: OpenCred aggregates both on-chain (e.g., DeFi TVL, smart contract interactions) and off-chain data (e.g., social media followers and interactions) to tokenize trust in the form of CRED tokens. This means users can increase their personal trust value by increasing their online activity and footprint. Each CRED is unique to the user and contains a number of fungible Score Tokens (ST) that determine the value of a user’s CRED. By thus providing a measurable and objective way to assess trustworthiness, OpenCred enables secure, traceable, and efficient trust-based interactions in various Web3 applications, such as social media, e-commerce, DeFi, and gaming. This groundbreaking mechanism is crucial for fostering a trustworthy environment in the digital space and enabling countless new use cases in many areas from B2B to B2C to C2B to C2C. Zad: Ishan Pandey: The CRED token seems to be a key component of the OpenCred ecosystem. Can you explain its dual nature as a semi-fungible token and how it represents both identity and trustworthiness? And how does this design benefit users of your platform? Ishan Pandey: Zad: CRED tokens are a groundbreaking innovation of OpenCred, creating a new token standard we call embedded semi-fungible token (eSFT) that combines both non-fungible (unique) and fungible (interchangeable) properties. The non-fungible part of the token represents a user's unique identity within the OpenCred protocol, ensuring that each user has a distinct and verifiable presence. On the other hand, the fungible part of the token quantifies the user's trustworthiness, which is determined by their interactions (on-chain & off-chain) and the amount of CRED tokens they receive from others. This design benefits users by empowering them to monetize their online activity and social relationships. Moreover, by tokenizing trust and making it quantifiable and tangible, we are creating a new kind of asset that simply has not existed before, thereby creating huge value. Zad: Ishan Pandey: How does sending CRED between users facilitate the building of a trustable and quantifiable social graph in Web3? Ishan Pandey: Zad: When a user sends CRED tokens to another user, they are essentially establishing a trust relationship that is recorded on the blockchain. This transaction signifies that the sender trusts the recipient to a certain degree, based on their interactions, reputation, or other factors. As users continue to interact and send CRED tokens to each other, a dynamic, evolving on-chain social graph emerges. The social graph is quantifiable and traceable. This quantification of trust enables users to make informed decisions when interacting with others, as they can assess the trustworthiness of potential collaborators, partners, or service providers based on their position in the social graph. Zad: Ishan Pandey: With OpenCred positioning itself as a provider of "Trust as a Service," how do you ensure the reliability and security of the trust metrics generated by your protocol? Ishan Pandey: Zad: There is a clear friction between incentivizing users on the one hand and ensuring the authenticity of trust relationships on the other hand. We are aware of this and will tackle this problem in multiple ways. First of all, we will connect the sending of CRED with some actions such as “follow”, “like”, etc., so that the transfer of CRED corresponds with the establishment of a meaningful trust relationship. Secondly, we will implement punishments for sybil attackers and other malicious behavior. Additionally, OpenCred implements a multi-layered governance model that involves community participation and decentralized decision-making. This approach helps to maintain the integrity and fairness of the trust metrics, as the community can collectively monitor and flag any suspicious activities or attempts to manipulate trust scores. To further enhance the reliability of trust metrics, OpenCred incorporates a reputation staking mechanism, where users are required to stake a portion of our governance tokens to participate in trust-building activities. OpenCred places a strong emphasis on user education and awareness. By providing clear guidelines, tutorials, and best practices for using the trust protocol. Zad: Ishan Pandey: How do you plan to drive adoption and grow the OpenCred ecosystem, particularly in terms of attracting both users and developers? Ishan Pandey: Zad: OpenCred actively seeks partnerships and collaborations with established Web3 projects across various sectors, such as social media, e-commerce, gaming, and decentralized finance (DeFi). We currently have established partnerships with over 10 Web3 projects with close to 1 million daily active users ready to onboard our protocol once it is live. To attract developers, OpenCred will provide a range of tools, SDKs, and documentation to facilitate the integration of its trust protocol into various applications. The protocol will offer developer grants, hackathons, and bounty programs to incentivize the creation of innovative trust-based solutions. Zad: By fostering a vibrant developer community and providing the necessary resources and support, OpenCred aims to accelerate the development of a diverse range of dApps that leverage its trust infrastructure. OpenCred's tokenomics model is designed to incentivize user participation and ecosystem growth. The governance token serves as the primary means of interaction within the OpenCred ecosystem, used for establishing trust relationships, staking, and accessing trust-based services. The protocol will implement a reward system that incentivizes users to actively participate in trust-building activities, such as providing accurate trust assessments, staking tokens, and contributing to the network's security. These incentives will drive user adoption and encourage long-term engagement with the OpenCred ecosystem. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

How OpenCred Makes Trust Tangible via Tokenization

কিভাবে ওপেনক্রেড অনলাইনে বিশ্বাস তৈরি করতে টোকেনাইজেশন ব্যবহার করে

Wie OpenCred Tokenisierung nutzt, um Online-Vertrauen aufzubauen

Cómo OpenCred utiliza la tokenización para generar confianza en línea

Comment OpenCred utilise la tokenisation pour renforcer la confiance en ligne

ओपनक्रेड ऑनलाइन विश्वास बनाने के लिए टोकनाइजेशन का उपयोग कैसे करता है

OpenCred がトークン化を利用してオンラインで信頼を築く方法

OpenCred가 토큰화를 사용하여 온라인 신뢰를 구축하는 방법

Como o OpenCred usa tokenização para construir confiança online

Как OpenCred использует токенизацию для укрепления доверия в Интернете

OpenCred Çevrimiçi Güven Oluşturmak İçin Tokenizasyonu Nasıl Kullanıyor?

Cách OpenCred sử dụng mã thông báo để xây dựng niềm tin trực tuyến

OpenCred 如何使用代币化在线建立信任

Summer 2023 was a tough time for Web3 projects. Our company was bordering on breaking even with no ETA in sight. While we were looking for new possibilities and business ideas, we worked hard on developing existing products and services. In a volatile space, we had to work in a trial and error mode, with every new project having the potential to make or break the market. When There Is No Market Quite recently, I had a short but meaningful conversation with an IT business devil. I came in with a direct approach right off the bat, stating that my company provides security services for the blockchain market. "There is no blockchain market," was his response. He even elaborated, claiming that there’s a mobile devices market and a real estate market but no "blockchain market." Bold statement, but it gave me some food for thought. The mobile development market cap was , the EV market cap was around , and the wearables market cap was . There is plenty of room to play. But what is the blockchain market? According to CoinMarketCap, the global crypto market cap was about . However, the blockchain services and products market was just . $206.85 billion in 2022 $388 billion in 2023 $71.91 billion in 2023 $1.69 trillion in January 2024 $11.4 billion in 2022 First of all, there’s a huge difference between the asset cap and services cap. Second, if your startup is aiming to take 0.01% of a $206 billion market, it is aiming at $20.6 million. But then, even 0.1% of an $11 billion market is $11 million. Consider: You’re trying to take a 10x market share but gaining half the revenue. At the end of the day, $11.4 billion doesn’t come close to a big corporation number, and here we were trying to claim the existence of a whole market. Despite working in it for years, I had no other choice but to agree with the initial claim of the IT business expert. There are companies, projects, and startups, but they haven’t yet made a market. Making A Market If the market doesn’t exist, why bother, right? There are several already successful functioning and developing markets. And if you think about it, entering them does become easier in time. It’s cheaper, too, thanks to various technological leaps and the options to start from scratch and develop an advanced product. But in the end, we always see the same image: margin drops down to zero profitability. That, however, doesn’t apply to some restricted markets that exist solely based on monopolies. Working in an officially nonexistent space has its advantages. Everything is brand new, and as a founder, you make the rules. There also is a lucky chance event that can happen to a market that doesn’t exist: It can appear. If you still have doubts, you can look back at history. Every revolution, be it industrial or technological, kickstarted the development of not one but several dedicated markets. A company might start with 3% of nothing and grow to 3% of everything in no time, surpassing huge corporations in other fields. It might be a long-lasting success or just a flash, but at the end of the day, that’s how many success stories began. How To Approach A Nonexistent Market Whether a market is new or well-developed, success is impossible unless you try to achieve it. But I’m going to take this segment to talk about chickens. It’s no secret that hens are the point of interest for poultry farms. Roosters, however, often become meat as soon as they reach a required weight. Yet, in many cases, it's only possible to tell the sex of a chicken around the fifth or sixth week of their life. Before that, hens and roosters look identical. This brings massive expenses that go into feeding and maintaining about 50% of the birds, which are virtually useless for the farm. Surprisingly, the issue could be solved: Factories and farms have trained people who can identify a chicken’s sex with and only a day after the chicken is hatched. The best can process 1,000 chickens per hour, and what’s most incredible is that it’s a teachable skill. There’s no theory to that, just intuition and practice: After every attempt, a professional confirms or denies the results, and this happens until the student achieves the required accuracy. 98% accuracy A startup in a new market is similar to a chicken. Most founders attempt to identify its potential after six to 12 months of existence, even after investing large sums in launching the project. But there is another way. Like those chicken sex experts, a founder has to practice and train their intuition so that they eventually will be able to determine the perspectives and potential success of their startup. There is no logic to this; the circumstances change every day, and hard data comes in too late. So the only real skill is your gut feeling—that’s what founders should be training and developing. This skill is the only important and viable advantage for any founder. Conclusion There are two ways to conquer a market. A startup can disrupt the existing field with an innovative product or hope for a multiplier in a market that doesn’t yet exist. Either way, success isn’t guaranteed. So, the blockchain market, whether it’s already created and developed or just exists in our imaginations, can still be a fruitful field. Follow me on . Check out my . LinkedIn website

What To Do As A Startup Without A Market

একটি বাজার ছাড়া একটি স্টার্টআপ হিসাবে কি করতে হবে

Was tun als Startup ohne Markt?

Qué hacer como startup sin mercado

Que faire en tant que startup sans marché

बिना बाज़ार के स्टार्टअप के रूप में क्या करें?

Elaborate

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Since 2021

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Elaborate

elaborate.com

11-50 employees

Since 2021

COMPANY RANKING

ELABORATE

EVERGREEN INDEX #408

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