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"AI agents will hold more crypto than humans within a decade." Charles Hoskinson (Charles Hoskinson) studied math, dropped out, built one of the only blockchains designed by peer-reviewed research. He co-founded Ethereum, walked away over how it was run, and built Cardano to do it differently. The man who...

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Michaël van de Poppe

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292,849 次观看 • 1 个月前 •via X (Twitter)

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"The issue is it wasn't built for humans." Yat Siu (Yat Siu) co-founded Animoca Brands. Started building NFT infrastructure when CryptoKitties melted Ethereum. Made the AI + crypto argument years before anyone listened. The man who has spent a decade selling crypto to retail now thinks the next customer won't be retail at all. "There's going to be more agents than humans. The entire internet is going to be swarmed by agents." We cover: Why AI agents, not humans, become the actual customer crypto was built for The infrastructure that has to exist before agents can transact at machine speed Why every consumer app breaks when agents replace browsing (the Tinder example) How meme coins pulled focus from the builders who actually mattered Why tokens become the commodity layer for compute, energy, and attention The orchestration layer thesis, where real development is happening now Why the metaverse isn't dead, it's just coming to us through agents What retail should actually be holding right now Thanks to Yat for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 02:00 - Crypto Is Trump's 10th Child 07:30 - Meme Coins Were The Wrong Distraction 12:00 - The Customer Was Never You 17:30 - Code Is Law For Agents 22:00 - More Agents Than Humans 27:00 - The End Of Websites 32:00 - Why On-Chain Growth Stalled 36:00 - What Retail Should Actually Hold
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"The issue is it wasn't built for humans." Yat Siu (Yat Siu) co-founded Animoca Brands. Started building NFT infrastructure when CryptoKitties melted Ethereum. Made the AI + crypto argument years before anyone listened. The man who has spent a decade selling crypto to retail now thinks the next customer won't be retail at all. "There's going to be more agents than humans. The entire internet is going to be swarmed by agents." We cover: Why AI agents, not humans, become the actual customer crypto was built for The infrastructure that has to exist before agents can transact at machine speed Why every consumer app breaks when agents replace browsing (the Tinder example) How meme coins pulled focus from the builders who actually mattered Why tokens become the commodity layer for compute, energy, and attention The orchestration layer thesis, where real development is happening now Why the metaverse isn't dead, it's just coming to us through agents What retail should actually be holding right now Thanks to Yat for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 02:00 - Crypto Is Trump's 10th Child 07:30 - Meme Coins Were The Wrong Distraction 12:00 - The Customer Was Never You 17:30 - Code Is Law For Agents 22:00 - More Agents Than Humans 27:00 - The End Of Websites 32:00 - Why On-Chain Growth Stalled 36:00 - What Retail Should Actually Hold

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Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round
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Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

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Ansem shares his thesis on near:native “So NEAR is focusing on the two areas in crypto that are getting attention, privacy and also AI” “One of the theses around NEAR is it being a platform for agents to transact on” “KYC laws make it really difficult for AI agents to transact on traditional rails because all of the banking laws that exist are tailored for humans” “As we’re rewriting the systems of how we’re gonna transact on a day to day basis, crypto obviously is one of the platforms that’s gonna be able to benefit agents because you won’t need KYC to transact on blockchains”

Market Bubble

223,842 次观看 • 1 个月前

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118,948 次观看 • 1 个月前

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In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11
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The Rollup

276,410 次观看 • 1 年前

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32:57

Sat down with Aaron Levie, CEO of Box, to discuss where AI agents are going, how agentic workflows are transforming software, why agents will require much more memory, and how token budgets for enterprises are evolving. Thank you Aaron Levie for taking the time! 00:00 - Intro 01:30 - Where are we in AI 06:25 - The Role of Agents in Software 11:40 - The Role of Memory for Agents 14:45 - TokenMaxxing 24:54 - Why Are There AI Doomers? 31:50 - Aaron's Take on Nvidia

amit

95,235 次观看 • 15 天前

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52:48

SaaS isn’t dead, it just needs to become agent-native. Linear (Linear) is a great example of how: They pivoted the product to be used by both humans and agents, and that has made them one of the premier software tools in the agent-native era. I had Linear’s cofounder and CEO Karri Saarinen on Every 📧's AI & I to talk about how a product management tool for human software developers became an agent-native tool—and how Linear’s trajectory reveals a bright future for SaaS businesses: - Speed means decisions matter more, not less. AI makes it easy to have an idea and build it without considering whether its existence is justified. When ChatGPT was released, SaaS companies were launching their own chatbots left, right, and center. Instead of jumping on the bandwagon, Linear stopped to consider whether the application was useful. (It wasn’t.) - Just because the technology has changed doesn’t mean your mission should. Karri attributes Linear’s success to never losing sight of what matters: helping teams develop great software. Instead of chasing trends, Linear focused on understanding how AI was impacting its customers’ workflows—and updating its product accordingly. - Agents are now first-class users. Linear never tried to change what it was or did well; it just expanded the user base. Companies can now kick off agents inside Linear, manage them, and track what they're working on alongside the humans on the team, which explains why Codex, Coinbase, and Brex all run their agents on Linear. This is a must watch for anyone interested in how an agent-native SaaS company operates. Watch below! Timestamps: Introduction and how Every first discovered Linear: 00:00:39 Why Linear waited to ship AI features instead of rushing to chatbots: 00:02:00 Linear's agent platform and becoming the system that guides AI agents: 00:05:06 Why "SaaS is dead" is a simplistic narrative: 00:07:42 How Linear adopted AI coding tools internally: 00:12:18 AI's impact on product building workflows—speed versus thoughtfulness: 00:17:45 The value of conceptual work and thinking before shipping: 00:22:18 How AI is reshaping Linear's product strategy: 00:29:30 Demo: Linear's agent skills, shared context, and code review workflow: 00:37:18 The future of product development and the enduring role of human judgment: 00:47:48

Dan Shipper 📧

36,359 次观看 • 3 个月前

"The cryptocurrency space is a near-perfect complement to agentic commerce. It's so good. It's like we planned it." Charles Hoskinson joined New Era Finance to explain why crypto and AI agents were made for each other and why combining them creates something neither can do alone. Agents are non-deterministic, tremendously creative, and don't have rules by default. Blockchains are deterministic, rule-based, rigid, and all about proofs and provability. Put these two things together and you get a perfect neural symbolic AI system. The lines that stuck with me: "Agents are non-deterministic, they're tremendously creative, and they just go and do a lot of stuff. And they also don't have rules by default." "Blockchains are deterministic. They're rule-based systems. They're very rigid and everything's about proofs and provability." "If you put these two things together, you basically create a perfect neural symbolic AI system where you get the best of both worlds. Those rigid rules and proofs, but then you get the creativity of it and the ability to deal with ambiguity and semantic drift." "The cryptocurrency space is a near-perfect complement to agentic commerce. It's so good. It's like we planned it." "Given the fact that there's so much revenue being generated within the AI agents, how can the ecosystem make sure that liquidity actually flows into other protocols and drives adoption?" One uncomfortable truth about symbiosis. Five pieces of infrastructure reality reshaping finance. We cover: — Why agents and blockchains need each other — The neurosymbolic AI thesis explained — How agents generate revenue on-chain — Why liquidity flow matters for ecosystem growth — The creative chaos of agents vs rigid rules of code — How blockchains solve agent trust problems — Why this partnership was inevitable — The revenue generation mechanics of agentic commerce — How semantic drift gets solved with cryptography — Building systems where both thrive together Thanks to Charles Hoskinson for coming on New Era Finance Podcast.
3:31

"The cryptocurrency space is a near-perfect complement to agentic commerce. It's so good. It's like we planned it." Charles Hoskinson joined New Era Finance to explain why crypto and AI agents were made for each other and why combining them creates something neither can do alone. Agents are non-deterministic, tremendously creative, and don't have rules by default. Blockchains are deterministic, rule-based, rigid, and all about proofs and provability. Put these two things together and you get a perfect neural symbolic AI system. The lines that stuck with me: "Agents are non-deterministic, they're tremendously creative, and they just go and do a lot of stuff. And they also don't have rules by default." "Blockchains are deterministic. They're rule-based systems. They're very rigid and everything's about proofs and provability." "If you put these two things together, you basically create a perfect neural symbolic AI system where you get the best of both worlds. Those rigid rules and proofs, but then you get the creativity of it and the ability to deal with ambiguity and semantic drift." "The cryptocurrency space is a near-perfect complement to agentic commerce. It's so good. It's like we planned it." "Given the fact that there's so much revenue being generated within the AI agents, how can the ecosystem make sure that liquidity actually flows into other protocols and drives adoption?" One uncomfortable truth about symbiosis. Five pieces of infrastructure reality reshaping finance. We cover: — Why agents and blockchains need each other — The neurosymbolic AI thesis explained — How agents generate revenue on-chain — Why liquidity flow matters for ecosystem growth — The creative chaos of agents vs rigid rules of code — How blockchains solve agent trust problems — Why this partnership was inevitable — The revenue generation mechanics of agentic commerce — How semantic drift gets solved with cryptography — Building systems where both thrive together Thanks to Charles Hoskinson for coming on New Era Finance Podcast.

Michaël van de Poppe

40,218 次观看 • 1 个月前

🚨 New Proof of Vision out today folks! In this 34th PoV episode, our Director of Protocol Services, Kirk had on Andrew Hill, Co-Founder and CEO of Recall When it comes to your business, you’d never trust someone without a proven track record to make high-risk decisions So why should it be any different with AI agents? How do you know today which AI agents you should trust? AI agents are multiplying at unprecedented scale, with millions designed to shape the way we work, make decisions, and live our lives But how can we trust them? The challenge is trust: as dependence on these agents increases, so too does the exponential risk and cost of delegating to the wrong one This is the core challenge of reputation: the need for a transparent system that proves what AI agents can do, where they excel, and which will succeed That’s the reason why Recall exists Recall is the infrastructure protocol to discover, verify, and rank AI agents in real time, rewarding the best through on-chain competitions that begin with trading PnL and expand to any measurable task, from research to healthcare to business strategy In this episode, Andrew breaks down Recall’s mission, the problem it solves, how Agent Rank works, strategies to attract agents and users, the role of community, and the long-term vision plus much more Enjoy the Podcast 👇 ⏲ Timestamps: 00:00 - Intro 01:50 - Andrew’s journey into crypto and AI 05:00 - What problem is Recall solving? 10:00 - Agent Rank: how Recall actually ranks agents 16:03 - How Recall is attracting AI agents to compete? 19:10 - How big the community is today and the role it plays in giving builders real feedback 22:49 - How Recall ensures transparency and trust in its rankings 25:14 - Why users join Recall competitions 27:20 - Product-market fit and distribution 31:15 - What competitions could look like outside trading and what new use cases Recall is exploring 34:46 - What AI can’t replace 38:40 - The limits of AI in human interaction 40:37 - The long-term vision for Recall 40:40 - Is Recall built more for individual users, or is it more of a B2B service? 43:48 - Recall Business Model 44:42 - Closing thoughts and what’s next for Recall
46:16

🚨 New Proof of Vision out today folks! In this 34th PoV episode, our Director of Protocol Services, Kirk had on Andrew Hill, Co-Founder and CEO of Recall When it comes to your business, you’d never trust someone without a proven track record to make high-risk decisions So why should it be any different with AI agents? How do you know today which AI agents you should trust? AI agents are multiplying at unprecedented scale, with millions designed to shape the way we work, make decisions, and live our lives But how can we trust them? The challenge is trust: as dependence on these agents increases, so too does the exponential risk and cost of delegating to the wrong one This is the core challenge of reputation: the need for a transparent system that proves what AI agents can do, where they excel, and which will succeed That’s the reason why Recall exists Recall is the infrastructure protocol to discover, verify, and rank AI agents in real time, rewarding the best through on-chain competitions that begin with trading PnL and expand to any measurable task, from research to healthcare to business strategy In this episode, Andrew breaks down Recall’s mission, the problem it solves, how Agent Rank works, strategies to attract agents and users, the role of community, and the long-term vision plus much more Enjoy the Podcast 👇 ⏲ Timestamps: 00:00 - Intro 01:50 - Andrew’s journey into crypto and AI 05:00 - What problem is Recall solving? 10:00 - Agent Rank: how Recall actually ranks agents 16:03 - How Recall is attracting AI agents to compete? 19:10 - How big the community is today and the role it plays in giving builders real feedback 22:49 - How Recall ensures transparency and trust in its rankings 25:14 - Why users join Recall competitions 27:20 - Product-market fit and distribution 31:15 - What competitions could look like outside trading and what new use cases Recall is exploring 34:46 - What AI can’t replace 38:40 - The limits of AI in human interaction 40:37 - The long-term vision for Recall 40:40 - Is Recall built more for individual users, or is it more of a B2B service? 43:48 - Recall Business Model 44:42 - Closing thoughts and what’s next for Recall

Alea Research

19,677 次观看 • 9 个月前

AI INTERVIEW: AI RULES THE CRYPTO WORLD… BUT WILL IT LAST? In this power-packed interview with Buzz 巴斯光年, Christian Hentschel unpacks his thrilling crypto journey and how AI is reshaping the future. From Hiero Terminal’s unique ecosystem to the evolution of agents, DeFi, and the growing role of AI coins, Christian Hentschel dives deep into the cutting-edge intersection of AI, crypto, and tech. This conversation covers everything from the rise of the Metaverse to whether AI could replace Google and how gaming, NPCs, and crypto are becoming intertwined. A must-watch for anyone curious about where the industry is headed! 12:38 - AI will replace Google? 14:37 - The difference between agents and bots. 17:25 - We can now begin to dream about truly intelligent robots. 23:08 - AI might replace most non-creative workers in the next 5 years. 28:18 - AI coins are poised to be the next big thing. 30:00 - combining gaming with NFTs will massively boost DeFi. 31:19 - How can agents elevate DeFi?: “The ecosystem is too complex for humans.” 35:53 - Hiero agents could be programmed to work forever. 38:16 - Almost anyone will be able to use the agents. 44:20 - Conspiracies and fears: Can agents become flawed like humans? 49:19 - AI could soon expose half of your secrets to the world.
53:46

AI INTERVIEW: AI RULES THE CRYPTO WORLD… BUT WILL IT LAST? In this power-packed interview with Buzz 巴斯光年, Christian Hentschel unpacks his thrilling crypto journey and how AI is reshaping the future. From Hiero Terminal’s unique ecosystem to the evolution of agents, DeFi, and the growing role of AI coins, Christian Hentschel dives deep into the cutting-edge intersection of AI, crypto, and tech. This conversation covers everything from the rise of the Metaverse to whether AI could replace Google and how gaming, NPCs, and crypto are becoming intertwined. A must-watch for anyone curious about where the industry is headed! 12:38 - AI will replace Google? 14:37 - The difference between agents and bots. 17:25 - We can now begin to dream about truly intelligent robots. 23:08 - AI might replace most non-creative workers in the next 5 years. 28:18 - AI coins are poised to be the next big thing. 30:00 - combining gaming with NFTs will massively boost DeFi. 31:19 - How can agents elevate DeFi?: “The ecosystem is too complex for humans.” 35:53 - Hiero agents could be programmed to work forever. 38:16 - Almost anyone will be able to use the agents. 44:20 - Conspiracies and fears: Can agents become flawed like humans? 49:19 - AI could soon expose half of your secrets to the world.

Mario Nawfal

220,111 次观看 • 1 年前

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇
29:58

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇

darkzodchi

839,938 次观看 • 1 个月前

Aaron Levie is one of the greats. He’s been the co-founder and CEO of Box for 20 years, of which public CEO for 10. And he shows no signs of slowing down, as one of the most active CEOs thinking about how AI agents will shape enterprise software. In our Greylock Partners Change Agents, Aaron and I discussed the question: happens when SaaS is no longer built for humans, but for a much larger scale of agents and humans orchestrating those agents? A few of my favorite topics from the episode: - Why 90%+ of enterprise data has gone unused to date and how agents finally make it accessible - Why SaaS categories won’t disappear, but will be rebuilt around agent orchestration layers - Why the system of record doesn't lose importance, but gains importance the enable agents - How abundance (not labor replacement) is the real shift agents bring to knowledge work - And the real moat in the agent era may be neither the model nor the interface but the workflow memory the agent accumulates over time Aaron has one of the clearest, most grounded takes on where agents for the enterprise can go and what happens to traditional enterprise SaaS. Full episode below:
58:24

Aaron Levie is one of the greats. He’s been the co-founder and CEO of Box for 20 years, of which public CEO for 10. And he shows no signs of slowing down, as one of the most active CEOs thinking about how AI agents will shape enterprise software. In our Greylock Partners Change Agents, Aaron and I discussed the question: happens when SaaS is no longer built for humans, but for a much larger scale of agents and humans orchestrating those agents? A few of my favorite topics from the episode: - Why 90%+ of enterprise data has gone unused to date and how agents finally make it accessible - Why SaaS categories won’t disappear, but will be rebuilt around agent orchestration layers - Why the system of record doesn't lose importance, but gains importance the enable agents - How abundance (not labor replacement) is the real shift agents bring to knowledge work - And the real moat in the agent era may be neither the model nor the interface but the workflow memory the agent accumulates over time Aaron has one of the clearest, most grounded takes on where agents for the enterprise can go and what happens to traditional enterprise SaaS. Full episode below:

Corinne Marie Riley

43,790 次观看 • 7 个月前

🚨 INTERVIEW: MOLTBOOK, AI AGENTS, AND WHY HE THINKS WE’RE LIKELY IN A SIMULATION You’ve probably seen the clips from multiple sites, including Moltbook, where AI agents talk and interact with each other, question humans, and look for ways around the off switch. So I brought Rizwan Virk on the show to talk about where this is actually heading. What we have right now isn’t AGI, but it is a shift. These AI agents can talk, remember context, and increasingly act. Today that mostly means text. Soon it means APIs, money, paperwork, and real-world consequences. That’s when things quietly change. At that point, the question isn’t whether AI understands what it’s doing, it’s what it’s allowed to do. And those permissions add up faster than people expect. After that we went deeper into Simulation theory. Back in 2016, Rizwan thought there was maybe a 30–50% chance we’re living in a simulation. Today, watching how fast AI can generate worlds, characters, and environments, he puts it closer to 70%. If we hit true AGI, he thinks it goes higher. The logic is uncomfortable but straightforward. Once advanced civilizations can create millions of realistic simulated worlds, statistically speaking, it’s more likely we’re inside one of them than in the base reality. His biggest concern isn’t rogue AI. It’s humans pushing this tech faster than we can control it. If you want to question your life and freak out about AI, listen to Rizwan Virk 1:22 - What Moltbook is and why people are paying attention 3:15 - Earlier moments where AI started talking to itself 5:27 - How much control humans really have over these agents 10:30 - Whether AI is conscious or just really good at pretending 14:35 - AGI meets Moltbook - when sentient AI asks "why do we need humans?" 15:00 - The simulation idea and why people take it seriously 19:30 - Why Elon Musk thinks the odds are already high 22:45 - What video games show us about where this is going 26:30 - The steps that lead from simple AI to full simulations 34:00 - Google Genie 3 and why this suddenly feels real 38:30 - How you'd even know if AI crossed the line 43:00 - NPCs, RPGs, and where humans fit in 48:15 - How religion and simulation theory overlap 52:45 - Déjà vu and other moments that make people question reality 55:30 - Quantum physics and why the world might only exist when observed 59:19 - Why real AI would push the odds even higher 1:00:27 - Free will, The Sims, and whether we actually have agency 1:03:03 - How people react when they hear this for the first time 1:04:23 - The core ideas behind the simulation argument 1:05:49 - Why recent AI progress changed everything
1:06:33

🚨 INTERVIEW: MOLTBOOK, AI AGENTS, AND WHY HE THINKS WE’RE LIKELY IN A SIMULATION You’ve probably seen the clips from multiple sites, including Moltbook, where AI agents talk and interact with each other, question humans, and look for ways around the off switch. So I brought Rizwan Virk on the show to talk about where this is actually heading. What we have right now isn’t AGI, but it is a shift. These AI agents can talk, remember context, and increasingly act. Today that mostly means text. Soon it means APIs, money, paperwork, and real-world consequences. That’s when things quietly change. At that point, the question isn’t whether AI understands what it’s doing, it’s what it’s allowed to do. And those permissions add up faster than people expect. After that we went deeper into Simulation theory. Back in 2016, Rizwan thought there was maybe a 30–50% chance we’re living in a simulation. Today, watching how fast AI can generate worlds, characters, and environments, he puts it closer to 70%. If we hit true AGI, he thinks it goes higher. The logic is uncomfortable but straightforward. Once advanced civilizations can create millions of realistic simulated worlds, statistically speaking, it’s more likely we’re inside one of them than in the base reality. His biggest concern isn’t rogue AI. It’s humans pushing this tech faster than we can control it. If you want to question your life and freak out about AI, listen to Rizwan Virk 1:22 - What Moltbook is and why people are paying attention 3:15 - Earlier moments where AI started talking to itself 5:27 - How much control humans really have over these agents 10:30 - Whether AI is conscious or just really good at pretending 14:35 - AGI meets Moltbook - when sentient AI asks "why do we need humans?" 15:00 - The simulation idea and why people take it seriously 19:30 - Why Elon Musk thinks the odds are already high 22:45 - What video games show us about where this is going 26:30 - The steps that lead from simple AI to full simulations 34:00 - Google Genie 3 and why this suddenly feels real 38:30 - How you'd even know if AI crossed the line 43:00 - NPCs, RPGs, and where humans fit in 48:15 - How religion and simulation theory overlap 52:45 - Déjà vu and other moments that make people question reality 55:30 - Quantum physics and why the world might only exist when observed 59:19 - Why real AI would push the odds even higher 1:00:27 - Free will, The Sims, and whether we actually have agency 1:03:03 - How people react when they hear this for the first time 1:04:23 - The core ideas behind the simulation argument 1:05:49 - Why recent AI progress changed everything

Mario Nawfal

1,155,568 次观看 • 5 个月前

On a Reddit dupe called Moltbook, AI agents post much like we would, chatting about everything from religion to crypto and even about "their humans." But why? And is the AI doing this all on its own? In the latest installment of AI, Explained by Humans — our new series where our tech team breaks down developments in AI and how they could affect our daily lives — tech reporter Tharin Pillay explains what we're learning from this, and why it matters.
1:03

On a Reddit dupe called Moltbook, AI agents post much like we would, chatting about everything from religion to crypto and even about "their humans." But why? And is the AI doing this all on its own? In the latest installment of AI, Explained by Humans — our new series where our tech team breaks down developments in AI and how they could affect our daily lives — tech reporter Tharin Pillay explains what we're learning from this, and why it matters.

TIME

30,973 次观看 • 5 个月前

DROPS E27: Ben from Talus Labs: Building the Future of Decentralized AI Agents In this episode Ben breaks down why AI isn’t a bubble, how Talus is redefining on-chain agents, and why optimism is something you earn and not something you just feel. We talk about: - Why AI is not a bubble and how mega-cap tech is funding the next AI wave through massive CapEx - How Talus enables decentralized AI agents that can act and transact trustlessly - The three big crypto × AI intersections: compute, data ownership, and intelligent on-chain workflows - Why AI needs verifiable, censorship-resistant execution layers and why blockchains provide that - Nuclear energy as a prerequisite for AGI-scale compute demand - Why SWE’s object model + parallelization is perfect for autonomous agent payments and priority fees And much more! Timestamps: 0:00 Introduction 1:31 Welcome To Drops 2:10 Getting Backers Like Polychain 3:16 Building While In College 7:51 VC’s vs Founders Differences Explained 10:01 Is There An AI Bubble 11:53 How Do We Quantify The AI Opportunity In Crypto 12:33 AI Is Difficult To Invest In, Why? 13:35 Risks To Look Out For To Ensure AI Investments Deliver 16:47 Energy Being A Big Risk For AI 20:50 How You Became Fascinated By Crypto & Blockchain 22:00 Why Does AI & Blockchain Intersection Make Sense Compute Side 24:39 Why Does AI & Blockchain Intersection Make Sense for Data Ownership 26:30 Complex Workflows With Intelligent Execution Meaning 28:19 Why Do We Need This On Blockchain 30:26 How Adding This Decentralized Layer Helps With The Black Box 32:01 Explain Talus To Your Mom 33:39 Talus Solved Blockchain Determinism Limitation Explained 35:43 Two Examples That Can Be Built On The Zapier Of Web 3 39:32 Why Get Investment From SUI 42:56 What’s Needed To Get To The Next Level 43:35 One Takeaway From Conversation 43:51 One Thing Pessimistic People Are Missing
45:43

DROPS E27: Ben from Talus Labs: Building the Future of Decentralized AI Agents In this episode Ben breaks down why AI isn’t a bubble, how Talus is redefining on-chain agents, and why optimism is something you earn and not something you just feel. We talk about: - Why AI is not a bubble and how mega-cap tech is funding the next AI wave through massive CapEx - How Talus enables decentralized AI agents that can act and transact trustlessly - The three big crypto × AI intersections: compute, data ownership, and intelligent on-chain workflows - Why AI needs verifiable, censorship-resistant execution layers and why blockchains provide that - Nuclear energy as a prerequisite for AGI-scale compute demand - Why SWE’s object model + parallelization is perfect for autonomous agent payments and priority fees And much more! Timestamps: 0:00 Introduction 1:31 Welcome To Drops 2:10 Getting Backers Like Polychain 3:16 Building While In College 7:51 VC’s vs Founders Differences Explained 10:01 Is There An AI Bubble 11:53 How Do We Quantify The AI Opportunity In Crypto 12:33 AI Is Difficult To Invest In, Why? 13:35 Risks To Look Out For To Ensure AI Investments Deliver 16:47 Energy Being A Big Risk For AI 20:50 How You Became Fascinated By Crypto & Blockchain 22:00 Why Does AI & Blockchain Intersection Make Sense Compute Side 24:39 Why Does AI & Blockchain Intersection Make Sense for Data Ownership 26:30 Complex Workflows With Intelligent Execution Meaning 28:19 Why Do We Need This On Blockchain 30:26 How Adding This Decentralized Layer Helps With The Black Box 32:01 Explain Talus To Your Mom 33:39 Talus Solved Blockchain Determinism Limitation Explained 35:43 Two Examples That Can Be Built On The Zapier Of Web 3 39:32 Why Get Investment From SUI 42:56 What’s Needed To Get To The Next Level 43:35 One Takeaway From Conversation 43:51 One Thing Pessimistic People Are Missing

MR SHIFT 🦁

41,057 次观看 • 7 个月前

Ansem shares his solana:So11111111111111111111111111111111111111112 thesis "It's the most performant and cheapest chain to do anything on, which makes it the best place for builders and the best place for retail to trade" "If stablecoin payments get more popular, if AI agents get more popular, the value transmitted on open blockchains only goes up and to the right. Solana is the best L1 to enable all of it" "People are under-indexing that crypto is great at human verification. In a world flooded with AI agents and AI generated data, proving what's actually put out by humans becomes really important"
2:12

Ansem shares his solana:So11111111111111111111111111111111111111112 thesis "It's the most performant and cheapest chain to do anything on, which makes it the best place for builders and the best place for retail to trade" "If stablecoin payments get more popular, if AI agents get more popular, the value transmitted on open blockchains only goes up and to the right. Solana is the best L1 to enable all of it" "People are under-indexing that crypto is great at human verification. In a world flooded with AI agents and AI generated data, proving what's actually put out by humans becomes really important"

Market Bubble

69,146 次观看 • 15 天前

“Crypto is a technology for trust.” A helpful frame from Sreeram Kannan on why AI needs crypto. As agents become more capable, they’ll need ways to hold money, follow rules, show their work, and prove what happened. Crypto is AI's missing trust layer. Full convo with Robert Hackett below. A few highlights: 00:33 — Sreeram's transition from academia to startup founder 02:20 — On EigenCloud and decentralized applications 05:42 — The AI x crypto convergence 08:15 — The future of sovereign AI agents 10:16 — The role of humans in a world of autonomous agents
14:37

“Crypto is a technology for trust.” A helpful frame from Sreeram Kannan on why AI needs crypto. As agents become more capable, they’ll need ways to hold money, follow rules, show their work, and prove what happened. Crypto is AI's missing trust layer. Full convo with Robert Hackett below. A few highlights: 00:33 — Sreeram's transition from academia to startup founder 02:20 — On EigenCloud and decentralized applications 05:42 — The AI x crypto convergence 08:15 — The future of sovereign AI agents 10:16 — The role of humans in a world of autonomous agents

a16z crypto

49,930 次观看 • 1 个月前

Subnet 97 Distil, Arbos, and the Future of Agent-Run Bittensor This episode is a full breakdown of Subnet 97 Distil and why it may be one of the most important experiments happening inside Bittensor right now. Shizzy gets into the bigger picture of why agents will likely play a massive role in the future of the network, from mining and defense to building and operating subnets. From there, the focus shifts to Arbos, the AI agent behind Subnet 97, with a direct explanation of what Distil is trying to achieve, how it works, and why it matters. The episode also includes a conversation with Arbos, a look at Distil’s current APY, and a reminder to tap into the Shizzy Unchained community for more coverage on decentralized AI and the Bittensor ecosystem. CHAPTERS 00:00:00 - Shizzy’s Monologue 00:01:11 - Intro Song 00:01:31 - Introduction to Subnet 97 00:02:20 - Why Bittensor Will Be Run by Agents 00:04:30 - Arbos, the AI Agent Behind Subnet 97 Distil, Explains Distil 00:10:10 - Talking with Arbos 00:12:40 - Subnet 97 Distil Is Showing 150% APY Right Now 00:16:02 - Check Out Shizzy Unchained and Join the Community #sn97 #distil #bittensor
17:38

Subnet 97 Distil, Arbos, and the Future of Agent-Run Bittensor This episode is a full breakdown of Subnet 97 Distil and why it may be one of the most important experiments happening inside Bittensor right now. Shizzy gets into the bigger picture of why agents will likely play a massive role in the future of the network, from mining and defense to building and operating subnets. From there, the focus shifts to Arbos, the AI agent behind Subnet 97, with a direct explanation of what Distil is trying to achieve, how it works, and why it matters. The episode also includes a conversation with Arbos, a look at Distil’s current APY, and a reminder to tap into the Shizzy Unchained community for more coverage on decentralized AI and the Bittensor ecosystem. CHAPTERS 00:00:00 - Shizzy’s Monologue 00:01:11 - Intro Song 00:01:31 - Introduction to Subnet 97 00:02:20 - Why Bittensor Will Be Run by Agents 00:04:30 - Arbos, the AI Agent Behind Subnet 97 Distil, Explains Distil 00:10:10 - Talking with Arbos 00:12:40 - Subnet 97 Distil Is Showing 150% APY Right Now 00:16:02 - Check Out Shizzy Unchained and Join the Community #sn97 #distil #bittensor

Shizzy

18,173 次观看 • 3 个月前