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The WhatsApp data leak affecting billions is a stark reminder: platform architecture matters. Telegram Messenger 's model—where a phone number is optional, not mandatory—is a powerful competitive advantage. Expect the already massive 2.5M DAILY NEW USERS to accelerate as users seek platforms that prioritize data sovereignty and privacy. This... is a clear indicator of where network effects are heading. Welcome to #AlphaTON Capital 💎🚀🎯 #WhatsAppLeak #DataLeak #CyberSecurity #Privacy #Telegram #TechNews ₿rittany Kaiser 💎 🚀 enzo villani Will De Ath Wes Levitt logan Jennifer de Broglie Anthony Scaramucci Michael Terpin Disclaimer: All scenes depicted in this video are entirely fictional and were created using generative AI technology.show more

AlphaTON Capital 💎 🚀

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When #TheMooch talks, Wall Street listens. We took our world tour to the SALT stage in London, and founder Anthony Anthony Scaramucci gave AlphaTON Capital 💎 🚀 & the Telegram Messenger ecosystem a massive endorsement in front of 300+ institutional investors. His direct quote: "We are excited to be a strategic advisor to AlphaTON Capital, excited about the adoption and growth of the token and about the overall growth of the Telegram app." Why this matters: Telegram gets 2.5M new users EVERY DAY. With 1B+ active users, it's a top-4 global platform. The smartest money sees what we're building. Are you paying attention? 💎🚀⛏🎯 Huge thanks to Anthony Scaramucci and the SALT team for a high impact event! #AlphaTON #SALT #InstitutionalInvestors #Telegram #Nasdaq #ATON #DeFi ₿rittany Kaiser 💎 🚀 enzo villani logan Will De Ath Jennifer de Broglie Wes Levitt

When #TheMooch talks, Wall Street listens. We took our world tour to the SALT stage in London, and founder Anthony Anthony Scaramucci gave AlphaTON Capital 💎 🚀 & the Telegram Messenger ecosystem a massive endorsement in front of 300+ institutional investors. His direct quote: "We are excited to be a strategic advisor to AlphaTON Capital, excited about the adoption and growth of the token and about the overall growth of the Telegram app." Why this matters: Telegram gets 2.5M new users EVERY DAY. With 1B+ active users, it's a top-4 global platform. The smartest money sees what we're building. Are you paying attention? 💎🚀⛏🎯 Huge thanks to Anthony Scaramucci and the SALT team for a high impact event! #AlphaTON #SALT #InstitutionalInvestors #Telegram #Nasdaq #ATON #DeFi ₿rittany Kaiser 💎 🚀 enzo villani logan Will De Ath Jennifer de Broglie Wes Levitt

AlphaTON Capital 💎 🚀

47,703 Aufrufe • vor 7 Monaten

Listen to what Yat Siu , co-founder of Animoca Brands ✈️ SuperAI 🇸🇬 and one of the top 10 most influential leaders in crypto has to say about AlphaTON Capital 💎 🚀 : At the GBA Future of Money, Governance and the Law event in Washington D.C., Yat shared his 2026 outlook for AlphaTON Capital. He explains why AlphaTON Capital is the next big thing! By integrating gaming and building true operational capability, AlphaTON Capital is evolving into a key player in the TON 💎 and Telegram Messenger ecosystems for operating profit and long-term network growth. NASDAQ : $ATON 💎🚀🎯 ₿rittany Kaiser enzo villani Wes Levitt logan Jennifer de Broglie Yury Mitin Anthony Scaramucci Will De Ath

Listen to what Yat Siu , co-founder of Animoca Brands ✈️ SuperAI 🇸🇬 and one of the top 10 most influential leaders in crypto has to say about AlphaTON Capital 💎 🚀 : At the GBA Future of Money, Governance and the Law event in Washington D.C., Yat shared his 2026 outlook for AlphaTON Capital. He explains why AlphaTON Capital is the next big thing! By integrating gaming and building true operational capability, AlphaTON Capital is evolving into a key player in the TON 💎 and Telegram Messenger ecosystems for operating profit and long-term network growth. NASDAQ : $ATON 💎🚀🎯 ₿rittany Kaiser enzo villani Wes Levitt logan Jennifer de Broglie Yury Mitin Anthony Scaramucci Will De Ath

AlphaTON Capital 💎 🚀

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𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮. 𝗬𝗼𝘂𝗿 𝗔𝗜. 𝗬𝗼𝘂𝗿 𝗖𝗼𝗻𝘁𝗿𝗼𝗹. 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗮𝗹𝗹 𝘁𝗵𝗲 𝗶𝗻𝗳𝗼 𝘆𝗼𝘂 𝗳𝗲𝗲𝗱 𝗶𝗻𝘁𝗼 𝘆𝗼𝘂𝗿 #AI? The future of AI isn't about giving up your privacy to a tech giant. It's about sovereignty. Ben Goertzel the godfather of #AGI shares the vision. We're collaborating with SingularityNET to power Cocoon AI: Telegram Messenger ’s decentralized AI network. By securing high-performance compute infrastructure that is encrypted and decentralized, we are ensuring access to all Telegram users - more than 1 billion people right now - to top-tier AI tools without ever exposing their personal data. ✅ Decentralized Intelligence ✅ Military-Grade Privacy ✅ Zero-Carbon Footprint NASDAQ: $ATON The backbone of ethical AI 💎🚀🎯 #DataPrivacy #ATON ₿rittany Kaiser 💎 🚀 enzo villani Wes Levitt Will De Ath logan Yury Mitin Jennifer de Broglie Anthony Scaramucci

𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮. 𝗬𝗼𝘂𝗿 𝗔𝗜. 𝗬𝗼𝘂𝗿 𝗖𝗼𝗻𝘁𝗿𝗼𝗹. 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗮𝗹𝗹 𝘁𝗵𝗲 𝗶𝗻𝗳𝗼 𝘆𝗼𝘂 𝗳𝗲𝗲𝗱 𝗶𝗻𝘁𝗼 𝘆𝗼𝘂𝗿 #AI? The future of AI isn't about giving up your privacy to a tech giant. It's about sovereignty. Ben Goertzel the godfather of #AGI shares the vision. We're collaborating with SingularityNET to power Cocoon AI: Telegram Messenger ’s decentralized AI network. By securing high-performance compute infrastructure that is encrypted and decentralized, we are ensuring access to all Telegram users - more than 1 billion people right now - to top-tier AI tools without ever exposing their personal data. ✅ Decentralized Intelligence ✅ Military-Grade Privacy ✅ Zero-Carbon Footprint NASDAQ: $ATON The backbone of ethical AI 💎🚀🎯 #DataPrivacy #ATON ₿rittany Kaiser 💎 🚀 enzo villani Wes Levitt Will De Ath logan Yury Mitin Jennifer de Broglie Anthony Scaramucci

AlphaTON Capital 💎 🚀

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"What is the cleanest way to compare Billions with other web3 identity layers and privacy layers?" The word privacy means a lot of things to a lot of different people. Often it is associated with consent, which is an action that you take that diminishes the privacy of a given set of data. Privacy is basically the process of information arbitrage, the selective disclosure of data in order to enable interactions. Although in a web2 environment, that "free" transaction of data often weighs very heavily to one side. When we talk about privacy at Billions Network, privacy is a static state, the absence of disclosure, or a way to describe the outcomes of mechanisms of data disclosure. We really focus on those instances where the selective disclosure of data is a question of legal compliance, of security, of financial value, where the decision to leverage this technology is not necessarily one of personal feelings, but rather of business efficiency, of compliance, and security. Source: Billions CEO Evin McMullen evin speaking at House of Chimera Spaces Event Dec 3, 2025 In an era where AI is rapidly evolving, the boundaries of identity and privacy are being rewritten. Don’t miss our next Billions event in Shenzhen, China 🇨🇳 🗓 Date & Time Dec 21 (Sun), 20:00–23:00 Join a relaxed evening to experience our privacy-preserving verification and dive into the future of human + AI privacy In collaboration with: TinTinLand (TinTinLand 中文), Asia’s leading Web3 platform for developer growth and ecosystem acceleration.

"What is the cleanest way to compare Billions with other web3 identity layers and privacy layers?" The word privacy means a lot of things to a lot of different people. Often it is associated with consent, which is an action that you take that diminishes the privacy of a given set of data. Privacy is basically the process of information arbitrage, the selective disclosure of data in order to enable interactions. Although in a web2 environment, that "free" transaction of data often weighs very heavily to one side. When we talk about privacy at Billions Network, privacy is a static state, the absence of disclosure, or a way to describe the outcomes of mechanisms of data disclosure. We really focus on those instances where the selective disclosure of data is a question of legal compliance, of security, of financial value, where the decision to leverage this technology is not necessarily one of personal feelings, but rather of business efficiency, of compliance, and security. Source: Billions CEO Evin McMullen evin speaking at House of Chimera Spaces Event Dec 3, 2025 In an era where AI is rapidly evolving, the boundaries of identity and privacy are being rewritten. Don’t miss our next Billions event in Shenzhen, China 🇨🇳 🗓 Date & Time Dec 21 (Sun), 20:00–23:00 Join a relaxed evening to experience our privacy-preserving verification and dive into the future of human + AI privacy In collaboration with: TinTinLand (TinTinLand 中文), Asia’s leading Web3 platform for developer growth and ecosystem acceleration.

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Telegram Founder Durov: Using Technology to Protect Our Digital Rights and Freedom On October 30, at the Blockchain Life 2025 summit in Dubai, Telegram founder Pavel Durov stated that users are losing their digital freedom, with private information at risk of being misused by third parties — even in traditionally free countries where privacy and free speech are being restricted. He proposed a solution: building "decentralized AI" that belongs to the people，not to corporations or governments. Telegram is developing a blockchain-based private AI network that allows users to access common features without giving up their data. Durov emphasized that we must use technology to defend our freedom and rights. Source：

Telegram Founder Durov: Using Technology to Protect Our Digital Rights and Freedom On October 30, at the Blockchain Life 2025 summit in Dubai, Telegram founder Pavel Durov stated that users are losing their digital freedom, with private information at risk of being misused by third parties — even in traditionally free countries where privacy and free speech are being restricted. He proposed a solution: building "decentralized AI" that belongs to the people，not to corporations or governments. Telegram is developing a blockchain-based private AI network that allows users to access common features without giving up their data. Durov emphasized that we must use technology to defend our freedom and rights. Source：

Wu Blockchain

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Base has been home since 2024. We're building the world's largest decentralized telecom network and it settles to Base. Users can join the global telecom sharing economy, entirely onchain on Base in all aspects of our network. 3M+ daily active users utilize our network, and as we enter the next phase of scaling this video showcases what World Mobile already does on Base: Privacy First cellular phone plans, the first ones that pay you back, owning the core infrastructure of the network and earning rewards in stables, building the network, all transactions onchain settling to base and empowering base native communities like TOSHI We are spearheading the push for global adoption of a new onchain economy, built by all of us for all of us. World Mobile is live on Base

Base has been home since 2024. We're building the world's largest decentralized telecom network and it settles to Base. Users can join the global telecom sharing economy, entirely onchain on Base in all aspects of our network. 3M+ daily active users utilize our network, and as we enter the next phase of scaling this video showcases what World Mobile already does on Base: Privacy First cellular phone plans, the first ones that pay you back, owning the core infrastructure of the network and earning rewards in stables, building the network, all transactions onchain settling to base and empowering base native communities like TOSHI We are spearheading the push for global adoption of a new onchain economy, built by all of us for all of us. World Mobile is live on Base

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JD Vance just admitted the White House could take ownership of every major AI company in the US. Why? Because even governments are starting to realize the same thing: AI will create trillions in value, and at this rate, only a few Big Tech companies will benefit. Right now, billions of people are training AI every day through their data, actions, and online behavior. Yet almost all of the value flows back to a few billionaires and shareholders. That doesn't seem fair. At Action Model, we're building a different future. A people-owned AI model where those helping train it can share in the value they help create. If AI is built by the people, it should benefit the people too. Sign up to the Action Model movement and join the 500k+ users already contributing to a community-owned AI.

Action Model

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GMiden everyone 🤟 In finance, one rule always holds: a business is only as secure as the data behind it. So when the Miden team talks about Practical Private Finance, its not marketing - its a new on-chain model that finally works in real-world conditions. What’s the core idea behind Miden approach? The breakthrough is client-side proving: all computation happens on the users device. Your phone or laptop generates a local ZK-STARK proof, and the network verifies only correctnes. No exposed balances, no leaked strategies, no unnecessary risks. The chain sees the proof, but never your local state. That’s what practical privacy looks like. This is the kind of privacy blockchains should have offered to banks, brokers, trading platforms, and institutions yaers ago. And now it becomes real: private smart contracts, private execution, full control over state, fast performance, and programmable confidentiality - all without sacrificing speed or scalability. Practical Private Finance from Miden isnt a plug-in on top of the EVM. Its a new financial architecture where offchain data, proof-based validation, and compliance-ready design work as a unified system. This is how on-chain finally returns to sanity where trust isnt a slogan, but cryptography. And that’s exactly what inspired todays non NFT crypto art with my unofficial Miden mascot. The art itself in good quality is in the quote under this postHope you enjoy it )) #Miden #ClientSideProving

GMiden everyone 🤟 In finance, one rule always holds: a business is only as secure as the data behind it. So when the Miden team talks about Practical Private Finance, its not marketing - its a new on-chain model that finally works in real-world conditions. What’s the core idea behind Miden approach? The breakthrough is client-side proving: all computation happens on the users device. Your phone or laptop generates a local ZK-STARK proof, and the network verifies only correctnes. No exposed balances, no leaked strategies, no unnecessary risks. The chain sees the proof, but never your local state. That’s what practical privacy looks like. This is the kind of privacy blockchains should have offered to banks, brokers, trading platforms, and institutions yaers ago. And now it becomes real: private smart contracts, private execution, full control over state, fast performance, and programmable confidentiality - all without sacrificing speed or scalability. Practical Private Finance from Miden isnt a plug-in on top of the EVM. Its a new financial architecture where offchain data, proof-based validation, and compliance-ready design work as a unified system. This is how on-chain finally returns to sanity where trust isnt a slogan, but cryptography. And that’s exactly what inspired todays non NFT crypto art with my unofficial Miden mascot. The art itself in good quality is in the quote under this postHope you enjoy it )) #Miden #ClientSideProving

Konstantin

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The DMT ecosystem is on the cusp of producing yet again another major breakthrough This time ushered in by Superfan.fan and his HIRO’s project AI and DMT are two technology primitives that when combined can produce a new class of digital asset with “lifelike” properties that are generated through Bitcoin block data We discuss this in an interview with Superfan 👇 Introducing HIRO’s Bitcoin’s First Generative AI Killer App Powered By DMT | w/ SuperFan | TBR #224 Superfan is building a next-generation suite of tools that enables creators to use generative AI in their UNAT scripts. This will be showcased by the upcoming HIRO’s launch on 🅼🆂🅲🆁🅸₿🅴 August 15th. HIRO’s is a collection of 4,032 dynamic characters that are responsive to non-arbitrary data patterns that occur on Bitcoin. The HIRO asset itself is an impressive demonstration of the high-fidelity output behind the technology stack being utilized to generate them. We speak with Superfan to understand better the technology and the practical use cases moving forward as he will open source. Also, his thoughts on community building by utilizing AI and the superpower ability it can introduce in metaverse construction. 🚀Sign up to receive our Ordinal Takeover Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

The DMT ecosystem is on the cusp of producing yet again another major breakthrough This time ushered in by Superfan.fan and his HIRO’s project AI and DMT are two technology primitives that when combined can produce a new class of digital asset with “lifelike” properties that are generated through Bitcoin block data We discuss this in an interview with Superfan 👇 Introducing HIRO’s Bitcoin’s First Generative AI Killer App Powered By DMT | w/ SuperFan | TBR #224 Superfan is building a next-generation suite of tools that enables creators to use generative AI in their UNAT scripts. This will be showcased by the upcoming HIRO’s launch on 🅼🆂🅲🆁🅸₿🅴 August 15th. HIRO’s is a collection of 4,032 dynamic characters that are responsive to non-arbitrary data patterns that occur on Bitcoin. The HIRO asset itself is an impressive demonstration of the high-fidelity output behind the technology stack being utilized to generate them. We speak with Superfan to understand better the technology and the practical use cases moving forward as he will open source. Also, his thoughts on community building by utilizing AI and the superpower ability it can introduce in metaverse construction. 🚀Sign up to receive our Ordinal Takeover Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

ᴛʜᴇ ʙʟᴏᴄᴋ ʀᴜɴɴᴇʀ Podcast 🟧

14,538 Aufrufe • vor 1 Jahr

Kled Version 3 is coming. Over $20M+ in rewards will be paid directly to users from leading AI labs across robotics, legal services, image and video generation, world modeling, and more. In the last seven days, we’ve received inbound data requests from several decacorn AI labs and enterprises for datasets our human data marketplace is uniquely positioned to provide. Since receiving the specs for these requests, we now have a much better picture and understanding of how to reshape the systems that collect this data, so here’s what’s coming: 1. A fully redesigned home experience: The home feed is being rebuilt to surface the highest-value, most relevant tasks for each user, similar to how Uber Eats surfaces top restaurants. The goal is to turn every user into their most effective version as a data contributor. 2. Automated quality enforcement at scale: New ML systems are being built to evaluate task-specific requirements in real time. For example, if a task requires “two hands visible on camera at all times,” any video that fails that spec will be automatically rejected. This logic will apply across thousands of tasks and specifications using a general ML. 3. Kled Shop: Some tasks require better capture hardware. We’re introducing Kled Shop, where users can redeem points or tokens for equipment like Meta glasses, drones, and other tools. Points and tokens can be converted directly from payouts. 4. Partner-run data labeling and evaluation work: Some of our partners operate high-paying data labeling and model evaluation programs. We’re integrating their workflows directly into Kled so qualified users can access these roles in one place. These jobs are owned and managed by our partners. Kled’s role is to route the right people to the right work. Some opportunities pay $50–$1,000 per hour depending on expertise. 5. Global payouts and localization: We’re partnering with a major payment processor to enable cashouts in users’ native currencies. This unlocks broader global participation. Multi-language support is also coming to accelerate user growth. This full suite of tools will be rolling out soon, directly to Kled users. Top earners are currently making ~$7,000 per month. With this update, we should see the first ~$10,000 per month earner.

Kled Version 3 is coming. Over $20M+ in rewards will be paid directly to users from leading AI labs across robotics, legal services, image and video generation, world modeling, and more. In the last seven days, we’ve received inbound data requests from several decacorn AI labs and enterprises for datasets our human data marketplace is uniquely positioned to provide. Since receiving the specs for these requests, we now have a much better picture and understanding of how to reshape the systems that collect this data, so here’s what’s coming: 1. A fully redesigned home experience: The home feed is being rebuilt to surface the highest-value, most relevant tasks for each user, similar to how Uber Eats surfaces top restaurants. The goal is to turn every user into their most effective version as a data contributor. 2. Automated quality enforcement at scale: New ML systems are being built to evaluate task-specific requirements in real time. For example, if a task requires “two hands visible on camera at all times,” any video that fails that spec will be automatically rejected. This logic will apply across thousands of tasks and specifications using a general ML. 3. Kled Shop: Some tasks require better capture hardware. We’re introducing Kled Shop, where users can redeem points or tokens for equipment like Meta glasses, drones, and other tools. Points and tokens can be converted directly from payouts. 4. Partner-run data labeling and evaluation work: Some of our partners operate high-paying data labeling and model evaluation programs. We’re integrating their workflows directly into Kled so qualified users can access these roles in one place. These jobs are owned and managed by our partners. Kled’s role is to route the right people to the right work. Some opportunities pay $50–$1,000 per hour depending on expertise. 5. Global payouts and localization: We’re partnering with a major payment processor to enable cashouts in users’ native currencies. This unlocks broader global participation. Multi-language support is also coming to accelerate user growth. This full suite of tools will be rolling out soon, directly to Kled users. Top earners are currently making ~$7,000 per month. With this update, we should see the first ~$10,000 per month earner.

Avi Patel

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What is Nostr? Jack Dorsey explains it in just two minutes 👀 Nostr is revolutionizing the way we think about online communication and social networking. As an open protocol—short for "Notes and Other Stuff Transmitted by Relays"—it empowers users to share information in a decentralized manner, promoting freedom of expression and data security. Here are some key insights into why Nostr is gaining traction: A Response to Social Media Failures The current landscape of social media is fraught with issues—manipulative algorithms, intrusive ads, and rampant censorship. Nostr addresses these challenges head-on by offering an alternative that prioritizes user agency and transparency. It allows individuals to curate their experiences without being subjected to opaque corporate agendas. Decentralization at Its Core Nostr operates without a central authority, meaning there’s no single point of failure. This architecture not only enhances resilience against attacks but also ensures that users maintain control over their data. In a world where censorship is increasingly prevalent, Nostr’s structure allows for censorship-resistant communication, making it a compelling alternative to traditional social media platforms. User Empowerment through Cryptography At the heart of Nostr's functionality are cryptographic keys. Users generate unique "events" signed with their private keys, which are then broadcasted through independent relays. This not only secures communications but also enables users to verify their identities easily. The result? A platform where authenticity and privacy are paramount, allowing individuals to engage freely without fear of surveillance or censorship. Simplicity Meets Flexibility Nostr is built on a straightforward protocol that utilizes JSON for event objects and WebSocket connections for data transmission. This simplicity fosters software diversity, enabling developers to create various clients and applications that cater to different user needs. As a result, Nostr is not just another app; it's a flexible framework that can evolve with user demands. Nostr stands out as a beacon of hope for those seeking autonomy and privacy online. Its decentralized nature, combined with robust security features, positions it as a new challenger in the future of social networking. Are you ready to explore what Nostr has to offer? If you want to test nostr as a user, creator, developer or builder shoot me a DM, I'd love to connect. If you've read the whole post and haven't joined nostr yet, please try out Primal. It's a great nostr client for Android and IOS. I see you on the other side )

What is Nostr? Jack Dorsey explains it in just two minutes 👀 Nostr is revolutionizing the way we think about online communication and social networking. As an open protocol—short for "Notes and Other Stuff Transmitted by Relays"—it empowers users to share information in a decentralized manner, promoting freedom of expression and data security. Here are some key insights into why Nostr is gaining traction: A Response to Social Media Failures The current landscape of social media is fraught with issues—manipulative algorithms, intrusive ads, and rampant censorship. Nostr addresses these challenges head-on by offering an alternative that prioritizes user agency and transparency. It allows individuals to curate their experiences without being subjected to opaque corporate agendas. Decentralization at Its Core Nostr operates without a central authority, meaning there’s no single point of failure. This architecture not only enhances resilience against attacks but also ensures that users maintain control over their data. In a world where censorship is increasingly prevalent, Nostr’s structure allows for censorship-resistant communication, making it a compelling alternative to traditional social media platforms. User Empowerment through Cryptography At the heart of Nostr's functionality are cryptographic keys. Users generate unique "events" signed with their private keys, which are then broadcasted through independent relays. This not only secures communications but also enables users to verify their identities easily. The result? A platform where authenticity and privacy are paramount, allowing individuals to engage freely without fear of surveillance or censorship. Simplicity Meets Flexibility Nostr is built on a straightforward protocol that utilizes JSON for event objects and WebSocket connections for data transmission. This simplicity fosters software diversity, enabling developers to create various clients and applications that cater to different user needs. As a result, Nostr is not just another app; it's a flexible framework that can evolve with user demands. Nostr stands out as a beacon of hope for those seeking autonomy and privacy online. Its decentralized nature, combined with robust security features, positions it as a new challenger in the future of social networking. Are you ready to explore what Nostr has to offer? If you want to test nostr as a user, creator, developer or builder shoot me a DM, I'd love to connect. If you've read the whole post and haven't joined nostr yet, please try out Primal. It's a great nostr client for Android and IOS. I see you on the other side )

Pierre Corbin

18,456 Aufrufe • vor 1 Jahr

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 Aufrufe • vor 7 Monaten

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

Alex Ratner

49,964 Aufrufe • vor 1 Jahr

If you’re looking for the next wave of AI infrastructure opportunities, this is a must-watch 🚀 Everyone’s chasing the next big AI agent, but they’re missing the real story. Why is aixbt is dominating the market and how Cookie DAO 🍪 $COOKIE could change everything We discuss 👇 Why $COOKIE Is The Hidden AI GEM💎 on BASE! Chainlink For AI?! 400x POSSIBILITY! With most of the AI market mania fixated on which AI agent to speculate on next, we are deep diving into the depths of the ecosystem to find the next major infrastructure plays. With Aixbt dominating in crypto twitter mind share, it has proven the AI agents with the ability to produce impactful market insights stand among the pack as leaders in the market. Already Aixbt is at a 600M market cap only a couple of months after deployment. We break down why Aixbt has this ability to outperform other agents and how data aggregation is the necessary technical edge. Also, we analyze CookieDAO $COOKIE as the infrastructure provider leading the market with its data aggregation and packaging process. $COOKIE is on the verge of revamping its tokenomics to incorporate API access to data swarm API’s that they provide into the flywheel economics of the token. As demand increases from human and AI users of access to the data being aggregated will become that much more valuable in order for Agents to perform at a level equal to or greater than what Aixbt is capable of performing today. As $COOKIE are spent for these API’s by agents and developers, the supply gets burnt and funneled to the DAO. This will have a very positive impact on the value perception for the token. We also break down our predictions as to how their flagship agent Agent Cookie will perform once activated and released into the public sphere. Already based on internal testing as reported by the team, Agent Cookie is successfully producing valuable market calls. If Agent Cookie can achieve similar mind share as AIXBT as a result of its broader data aggregation access, this will have major ramifications for the value of $COOKIE and the ecosystem as a whole once more agents are launched using the same data infrastructure layer. 🚀Sign up to receive our Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

If you’re looking for the next wave of AI infrastructure opportunities, this is a must-watch 🚀 Everyone’s chasing the next big AI agent, but they’re missing the real story. Why is aixbt is dominating the market and how Cookie DAO 🍪 $COOKIE could change everything We discuss 👇 Why $COOKIE Is The Hidden AI GEM💎 on BASE! Chainlink For AI?! 400x POSSIBILITY! With most of the AI market mania fixated on which AI agent to speculate on next, we are deep diving into the depths of the ecosystem to find the next major infrastructure plays. With Aixbt dominating in crypto twitter mind share, it has proven the AI agents with the ability to produce impactful market insights stand among the pack as leaders in the market. Already Aixbt is at a 600M market cap only a couple of months after deployment. We break down why Aixbt has this ability to outperform other agents and how data aggregation is the necessary technical edge. Also, we analyze CookieDAO $COOKIE as the infrastructure provider leading the market with its data aggregation and packaging process. $COOKIE is on the verge of revamping its tokenomics to incorporate API access to data swarm API’s that they provide into the flywheel economics of the token. As demand increases from human and AI users of access to the data being aggregated will become that much more valuable in order for Agents to perform at a level equal to or greater than what Aixbt is capable of performing today. As $COOKIE are spent for these API’s by agents and developers, the supply gets burnt and funneled to the DAO. This will have a very positive impact on the value perception for the token. We also break down our predictions as to how their flagship agent Agent Cookie will perform once activated and released into the public sphere. Already based on internal testing as reported by the team, Agent Cookie is successfully producing valuable market calls. If Agent Cookie can achieve similar mind share as AIXBT as a result of its broader data aggregation access, this will have major ramifications for the value of $COOKIE and the ecosystem as a whole once more agents are launched using the same data infrastructure layer. 🚀Sign up to receive our Newsletter for weekly updates! Disclaimer: The views and opinions expressed by The Block Runner are for informational purposes only and do not constitute financial, investment, or other advice.

ᴛʜᴇ ʙʟᴏᴄᴋ ʀᴜɴɴᴇʀ Podcast | 91.bitmap 🟧

101,454 Aufrufe • vor 1 Jahr

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

Brian Roemmele

72,312 Aufrufe • vor 8 Monaten

$The Indian Government just did something that has Silicon Valley terrified. India is not simply buying AI chips. It is deliberately making AI compute cheaper than Amazon, and in some cases free. Under the IndiaAI Mission, the government has launched AIRAWAT, a national AI compute platform, alongside iKosha, India’s national AI data treasury. Together, they give startups, researchers and universities access to high-end AI compute at a fraction of the cost charged by Amazon, Google or Microsoft. For public institutions, researchers and selected early-stage startups, access is heavily subsidised, and in some cases provided entirely free. This is a fundamental shift in how AI infrastructure is being built. On Western cloud platforms, AI compute is priced for multinational corporations with deep pockets. India has chosen a different route. Instead of locking AI behind expensive pay-per-use contracts, it has created shared national infrastructure, where GPUs are pooled and made available at cost. Startups do not need millions in venture capital just to train a model. Researchers are not forced into foreign cloud dependency. Innovation is not restricted to those who can afford Silicon Valley pricing. The rollout of tens of thousands of GPUs, many of them Nvidia, is not about stockpiling hardware. It is about democratising access to compute. India is making it clear that if you are building something useful, locally relevant, or public-facing, you should not be priced out of AI by Big Tech. This is why it matters globally. India is not trying to outspend the United States or China. It is doing something more disruptive: undercutting the cloud monopoly model by making AI infrastructure cheap, shared, and in some cases free. That is also why this development receives so little attention in Western tech media. This is iKosha, AIRAWAT, and a conscious move towards AI sovereignty — affordable, accessible, and designed for public good rather than corporate rent-seeking.$

The Indian Government just did something that has Silicon Valley terrified. India is not simply buying AI chips. It is deliberately making AI compute cheaper than Amazon, and in some cases free. Under the IndiaAI Mission, the government has launched AIRAWAT, a national AI compute platform, alongside iKosha, India’s national AI data treasury. Together, they give startups, researchers and universities access to high-end AI compute at a fraction of the cost charged by Amazon, Google or Microsoft. For public institutions, researchers and selected early-stage startups, access is heavily subsidised, and in some cases provided entirely free. This is a fundamental shift in how AI infrastructure is being built. On Western cloud platforms, AI compute is priced for multinational corporations with deep pockets. India has chosen a different route. Instead of locking AI behind expensive pay-per-use contracts, it has created shared national infrastructure, where GPUs are pooled and made available at cost. Startups do not need millions in venture capital just to train a model. Researchers are not forced into foreign cloud dependency. Innovation is not restricted to those who can afford Silicon Valley pricing. The rollout of tens of thousands of GPUs, many of them Nvidia, is not about stockpiling hardware. It is about democratising access to compute. India is making it clear that if you are building something useful, locally relevant, or public-facing, you should not be priced out of AI by Big Tech. This is why it matters globally. India is not trying to outspend the United States or China. It is doing something more disruptive: undercutting the cloud monopoly model by making AI infrastructure cheap, shared, and in some cases free. That is also why this development receives so little attention in Western tech media. This is iKosha, AIRAWAT, and a conscious move towards AI sovereignty — affordable, accessible, and designed for public good rather than corporate rent-seeking.

JIX5A

67,346 Aufrufe • vor 5 Monaten

Spectre AI: New Website is Live We have launched the new Spectre AI website at After months of building behind closed doors, we are slowly ready to pull back the curtain. The community response has been incredible and pushed us to accelerate. We wanted you to see where Spectre is heading before the Beta opens. We deployed a video with a touch of comical value to express the daily need for freedom amongst people. Thats what we aim to build. This website is not the final form. New eyes on Spectre, old site that did not reflect where the product is today. We moved fast. It is an exclusive placeholder ahead of the Beta, built to introduce Spectre AI Platform 2.0 to the world. We also deployed a video with a touch of comical value to express the daily need for freedom. That is what we aim to build. What is the upcoming Spectre AI Platform 2.0 (Beta) about? AI-native from the ground up. Not a dashboard with a chatbot in the corner. Intelligence built into every surface. Agentic features synthesizing market data across crypto, stocks, commodities, macro, and predictions. Social signals, derivatives positioning, on-chain flows, the full macro picture, all surfaced at the point of decision. One platform. One intelligence layer. Everything talks to everything. A chapter closes. We are shutting down the old website and V1 app. That version served us well for over a year, tested ideas, gathered feedback, and taught us what V2 needed to be. V1 was the foundation. V2 is the building. Beta is close. What comes after is worth the wait. For anyone who wants to talk to the team now, our main Telegram is the place. Founding team and mods are active. Apply for the Beta on Spots are limited. Accepted testers will be notified directly by email. The Spectre AI Team $SPECTRE $SPECT

Spectre AI: New Website is Live We have launched the new Spectre AI website at After months of building behind closed doors, we are slowly ready to pull back the curtain. The community response has been incredible and pushed us to accelerate. We wanted you to see where Spectre is heading before the Beta opens. We deployed a video with a touch of comical value to express the daily need for freedom amongst people. Thats what we aim to build. This website is not the final form. New eyes on Spectre, old site that did not reflect where the product is today. We moved fast. It is an exclusive placeholder ahead of the Beta, built to introduce Spectre AI Platform 2.0 to the world. We also deployed a video with a touch of comical value to express the daily need for freedom. That is what we aim to build. What is the upcoming Spectre AI Platform 2.0 (Beta) about? AI-native from the ground up. Not a dashboard with a chatbot in the corner. Intelligence built into every surface. Agentic features synthesizing market data across crypto, stocks, commodities, macro, and predictions. Social signals, derivatives positioning, on-chain flows, the full macro picture, all surfaced at the point of decision. One platform. One intelligence layer. Everything talks to everything. A chapter closes. We are shutting down the old website and V1 app. That version served us well for over a year, tested ideas, gathered feedback, and taught us what V2 needed to be. V1 was the foundation. V2 is the building. Beta is close. What comes after is worth the wait. For anyone who wants to talk to the team now, our main Telegram is the place. Founding team and mods are active. Apply for the Beta on Spots are limited. Accepted testers will be notified directly by email. The Spectre AI Team $SPECTRE $SPECT

SPECTRE AI

29,264 Aufrufe • vor 3 Monaten

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

Jim Fan

165,246 Aufrufe • vor 1 Jahr