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We already have a superintelligence. It's called civilization. Humans, institutions, and now AI agents all interact among each other in one big economy. Allison Duettmann's take is that the real project in such a system is building and preparing AI enabled institutions on top of what already works. Her...

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Soubhik Deb

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11,759 次观看 • 9 天前 •via X (Twitter)

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"Nobody has actually lost their job to AI. They lost it due to the promise of AI." - Tanay Kothari Meta cut 8,000. Intuit cut 3,000. Anthropic is paying $1.25B a month for compute. China is winning the open-source war. And the Pope just called for AI to be disarmed. This week we covered these topics and more with: - Erik Bernhardsson (Erik Bernhardsson) is running the GPU cloud powering it all at Modal. - Tanay Kothari (Tanay Kothari) is running $100M in marketing with two humans and a swarm of agents at Wispr Flow. - Richard Socher (Richard Socher) is building recursive self-improving superintelligence at Recursive and the future of AI search at You.com. They join @jason on This Week in AI Episode 15, out now.
1:07:17

"Nobody has actually lost their job to AI. They lost it due to the promise of AI." - Tanay Kothari Meta cut 8,000. Intuit cut 3,000. Anthropic is paying $1.25B a month for compute. China is winning the open-source war. And the Pope just called for AI to be disarmed. This week we covered these topics and more with: - Erik Bernhardsson (Erik Bernhardsson) is running the GPU cloud powering it all at Modal. - Tanay Kothari (Tanay Kothari) is running $100M in marketing with two humans and a swarm of agents at Wispr Flow. - Richard Socher (Richard Socher) is building recursive self-improving superintelligence at Recursive and the future of AI search at You.com. They join @jason on This Week in AI Episode 15, out now.

This Week in AI

76,712 次观看 • 1 个月前

Microsoft AI CEO Mustafa Suleyman reveals the assumption about superintelligence he thinks the other AI labs have backwards "Some of the other labs are making an assumption that a superintelligence that is smarter than all of us put together is both inevitable and even desirable. And that such a system would probably be very hard to control" "We have to reset that and make the assumption that we should only bring a system like that into the world that we are sure we can control, that operates in a subordinate way to us, that humans remain at the top of the food chain" "These tools, like any other past technology, are designed to enhance human wellbeing and serve humanity. Not exceed humanity" "Some of the things that you hear from Elon often, or even others in the field - they're fixating on a world in 2050 or 2075 when they're going off exploring other universes and conquering resources from other planets. A system like that, it is unclear to me how it would have any time for preserving us as a species" "We have to make a decision as a species to prioritize creating superintelligences that are aligned, that care about humans and want to protect humans. If we just accelerate and cut all those corners, we're taking a massive risk with the future of our species" He calls it humanist superintelligence: build it only if it is provably controllable, subordinate, and pointed at human wellbeing. The uncomfortable part: "provably controllable" is a standard nobody in the industry can verify yet.
2:09

Microsoft AI CEO Mustafa Suleyman reveals the assumption about superintelligence he thinks the other AI labs have backwards "Some of the other labs are making an assumption that a superintelligence that is smarter than all of us put together is both inevitable and even desirable. And that such a system would probably be very hard to control" "We have to reset that and make the assumption that we should only bring a system like that into the world that we are sure we can control, that operates in a subordinate way to us, that humans remain at the top of the food chain" "These tools, like any other past technology, are designed to enhance human wellbeing and serve humanity. Not exceed humanity" "Some of the things that you hear from Elon often, or even others in the field - they're fixating on a world in 2050 or 2075 when they're going off exploring other universes and conquering resources from other planets. A system like that, it is unclear to me how it would have any time for preserving us as a species" "We have to make a decision as a species to prioritize creating superintelligences that are aligned, that care about humans and want to protect humans. If we just accelerate and cut all those corners, we're taking a massive risk with the future of our species" He calls it humanist superintelligence: build it only if it is provably controllable, subordinate, and pointed at human wellbeing. The uncomfortable part: "provably controllable" is a standard nobody in the industry can verify yet.

Karl Mehta

15,004 次观看 • 22 天前

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇
3:00

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,809 次观看 • 1 年前

CreatorBid is now live on BNB Chain 🟨 With our platform now officially multichain, the agentic revolution on the yellow chain is set to accelerate at lightspeed. BNB Chain is a wide-open frontier for AI Agents, and we’re already in talks with multiple teams gearing up to launch their agents through CreatorBid. And remember, once an agent exits the bonding curve, it automatically hits the DEX - PancakeSwap. CZ 🔶 BNB called for more AI Agent development onchain - this is exactly that, real use cases and serious development. CreatorBid is becoming the home of the next generation of AI Agents.
0:48

CreatorBid is now live on BNB Chain 🟨 With our platform now officially multichain, the agentic revolution on the yellow chain is set to accelerate at lightspeed. BNB Chain is a wide-open frontier for AI Agents, and we’re already in talks with multiple teams gearing up to launch their agents through CreatorBid. And remember, once an agent exits the bonding curve, it automatically hits the DEX - PancakeSwap. CZ 🔶 BNB called for more AI Agent development onchain - this is exactly that, real use cases and serious development. CreatorBid is becoming the home of the next generation of AI Agents.

Creator.Bid

129,924 次观看 • 1 年前

🇨🇳 China: AI should be open, inclusive, people-centered, and a force for good for all. 🇺🇸 America: AI should be led by us, secured by us, and placed in the hands of “trusted defenders.” That is the difference. One sees AI as part of human civilization. The other sees AI as a strategic asset of empire. No wonder Chinese people are becoming more comfortable with AI, while Americans are taught to fear it. You don’t love a weapon. You fear the day it stops obeying.
1:04

🇨🇳 China: AI should be open, inclusive, people-centered, and a force for good for all. 🇺🇸 America: AI should be led by us, secured by us, and placed in the hands of “trusted defenders.” That is the difference. One sees AI as part of human civilization. The other sees AI as a strategic asset of empire. No wonder Chinese people are becoming more comfortable with AI, while Americans are taught to fear it. You don’t love a weapon. You fear the day it stops obeying.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

17,142 次观看 • 1 个月前

Mark Zuckerberg, CEO of Meta: "The average American has fewer than three friends. And the average person has demand for meaningfully more, like 15." He said it flatly, as the setup for his real point: people are going to have relationships with AI. Not use it. Have relationships with it. AI friends, AI therapists, and yes, the other kind too. His logic is hard to argue with, and darker than it sounds. People are lonelier than they want to be. The demand for connection is already there, unmet. So Meta is building AI companions that remember you, talk back in real time, and with their Codec Avatars, "feel like a real person" on an always-on video call. We spent a decade afraid AI would take our jobs. Nobody asked whether it would take our friends. And the unsettling part is, for a lot of people, it might feel better.
2:07

Mark Zuckerberg, CEO of Meta: "The average American has fewer than three friends. And the average person has demand for meaningfully more, like 15." He said it flatly, as the setup for his real point: people are going to have relationships with AI. Not use it. Have relationships with it. AI friends, AI therapists, and yes, the other kind too. His logic is hard to argue with, and darker than it sounds. People are lonelier than they want to be. The demand for connection is already there, unmet. So Meta is building AI companions that remember you, talk back in real time, and with their Codec Avatars, "feel like a real person" on an always-on video call. We spent a decade afraid AI would take our jobs. Nobody asked whether it would take our friends. And the unsettling part is, for a lot of people, it might feel better.

Casper

255,730 次观看 • 4 天前

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.
0:24

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.

Gata

48,232 次观看 • 9 个月前

AI is everywhere. But the real question is: how does AI participate in the economy? That's where Base comes in. While everyone is focused on AI models, Base is building the rails for AI agents to transact, pay, and interact online. With Baseapp, you can already access a future where trading, payments, yield, prediction markets, and more live in one place. Ready to explore the future of the onchain economy? Download Base App and see what's possible 👇
0:48

AI is everywhere. But the real question is: how does AI participate in the economy? That's where Base comes in. While everyone is focused on AI models, Base is building the rails for AI agents to transact, pay, and interact online. With Baseapp, you can already access a future where trading, payments, yield, prediction markets, and more live in one place. Ready to explore the future of the onchain economy? Download Base App and see what's possible 👇

SPACE 😎

16,125 次观看 • 1 个月前

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇
2:00

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇

MosesMee

14,108 次观看 • 1 年前

"The data that we've been working with as people now becomes extremely useful in a world of agents. You're having this rebirth of the file system." Aaron Levie on Navigators with Paul Klein IV on why unstructured data, the 90% of enterprise data that has always been the hardest to automate, is now the biggest unlock for AI agents. And why the real AI conversation is a context conversation.
2:40

"The data that we've been working with as people now becomes extremely useful in a world of agents. You're having this rebirth of the file system." Aaron Levie on Navigators with Paul Klein IV on why unstructured data, the 90% of enterprise data that has always been the hardest to automate, is now the biggest unlock for AI agents. And why the real AI conversation is a context conversation.

Box

66,225 次观看 • 14 天前

Jack Dorsey says the real danger isn't open source AI, it's five CEOS deciding what the world is allowed to build with AI. "These AI companies are building platforms and they're all incentivized around their own particular models. You have to ask them for permission, you have rate limits, and you have all these things. Even what the models spit back are constrained." "What are the technologies where you don't need permission from a company, from a CEO, to work on what you want, to build what you want, to build a business around that? Those are the things that are durable. That's why these open protocols are significant and important." "It limits the potential of really great ideas bringing humanity forward because it's a decision of a group of CEOs that think they know best. They may know best for their company, but they don't know the best for the creativity of the world and what people actually want to do with it." "Fortunately, there's a great movement in open source AI, and DeepSeek was an important moment in this space for exactly that reason to show a different path and to provide something that is not only competitive but better than the models that the corporations are putting out there." "We should not be reliant upon five companies telling us that they know best, and there should not be open source because it's dangerous. No, we should have these things in the open and race towards solutions that stay ahead of all the dangers." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:
2:07

Jack Dorsey says the real danger isn't open source AI, it's five CEOS deciding what the world is allowed to build with AI. "These AI companies are building platforms and they're all incentivized around their own particular models. You have to ask them for permission, you have rate limits, and you have all these things. Even what the models spit back are constrained." "What are the technologies where you don't need permission from a company, from a CEO, to work on what you want, to build what you want, to build a business around that? Those are the things that are durable. That's why these open protocols are significant and important." "It limits the potential of really great ideas bringing humanity forward because it's a decision of a group of CEOs that think they know best. They may know best for their company, but they don't know the best for the creativity of the world and what people actually want to do with it." "Fortunately, there's a great movement in open source AI, and DeepSeek was an important moment in this space for exactly that reason to show a different path and to provide something that is not only competitive but better than the models that the corporations are putting out there." "We should not be reliant upon five companies telling us that they know best, and there should not be open source because it's dangerous. No, we should have these things in the open and race towards solutions that stay ahead of all the dangers." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:

Uncover AI

36,393 次观看 • 13 天前

In the AI era, the traditional biopharma industry is the underdog. Big tech and AI labs are building wet labs. China has overtaken Europe in molecules produced. But the tools available to the industry discuss science, not do it. The hard problem in AI for science is at the interface between the physical and digital worlds. We built an AI Scientist at that seam. It wires together the digital and physical worlds of R&D. Predictive models, data infrastructure, wet lab execution feed into a single loop that reasons, acts, and improves with every experiment. Our ambition: get molecules to the clinic twice as fast. Last fall I wrote about why biotech needs to be rebuilt for the AI era. Today I'm sharing the next chapter: what the AI Scientist is, a blueprint for how it works, and why even Richard Feynman couldn't hack it in a wet lab.
1:44

In the AI era, the traditional biopharma industry is the underdog. Big tech and AI labs are building wet labs. China has overtaken Europe in molecules produced. But the tools available to the industry discuss science, not do it. The hard problem in AI for science is at the interface between the physical and digital worlds. We built an AI Scientist at that seam. It wires together the digital and physical worlds of R&D. Predictive models, data infrastructure, wet lab execution feed into a single loop that reasons, acts, and improves with every experiment. Our ambition: get molecules to the clinic twice as fast. Last fall I wrote about why biotech needs to be rebuilt for the AI era. Today I'm sharing the next chapter: what the AI Scientist is, a blueprint for how it works, and why even Richard Feynman couldn't hack it in a wet lab.

Sajith Wickramasekara

30,646 次观看 • 3 个月前

Mira Murati says the outcome of frontier AI is not predestined: "Predicting a dystopia or a utopia, to me, feels very simplified because the truth is we actually have a lot of agency in how we build this technology, in the tools that we're building, how we're deploying it." "There are certainly those risks. We all understand the potential for greatness that comes with building frontier AI systems, and that's why we're working on them." "Where I might disagree or take a different path is that I think we have a lot of agency. This period of time where both humans and AI systems have their hands on the wheel, and we can collaborate, it's a very important time to get right." Mira Murati at Bloomberg Tech live with Emily Chang
1:35

Mira Murati says the outcome of frontier AI is not predestined: "Predicting a dystopia or a utopia, to me, feels very simplified because the truth is we actually have a lot of agency in how we build this technology, in the tools that we're building, how we're deploying it." "There are certainly those risks. We all understand the potential for greatness that comes with building frontier AI systems, and that's why we're working on them." "Where I might disagree or take a different path is that I think we have a lot of agency. This period of time where both humans and AI systems have their hands on the wheel, and we can collaborate, it's a very important time to get right." Mira Murati at Bloomberg Tech live with Emily Chang

a16z

120,011 次观看 • 1 个月前

Jamie Dimon, we’re coming for you. Kontigo is building the largest bank in the world. (A “full-stack” AI stablecoin bank). Most “stablecoin neobanks” are just Bridge wrappers with no real distribution. We’re building our own infrastructure to replace traditional banks. Our infra lets humans and agents transact on top of open networks (blockchains) and local stablecoins. “A startup building agents for law firms could just build the AI law firm.” We’re doing the same for banking. Disclaimer: Kontigo is not a bank. Banking services are provided by the freaking blockchain.
1:12

Jamie Dimon, we’re coming for you. Kontigo is building the largest bank in the world. (A “full-stack” AI stablecoin bank). Most “stablecoin neobanks” are just Bridge wrappers with no real distribution. We’re building our own infrastructure to replace traditional banks. Our infra lets humans and agents transact on top of open networks (blockchains) and local stablecoins. “A startup building agents for law firms could just build the AI law firm.” We’re doing the same for banking. Disclaimer: Kontigo is not a bank. Banking services are provided by the freaking blockchain.

Jesus A. Castillo F.

22,731 次观看 • 7 个月前

Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇
1:18

Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇

Etherealize

115,212 次观看 • 2 个月前

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?
0:59

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?

ChainOpera AI

15,398 次观看 • 1 个月前

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science
49:06

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science

Matt Turck

64,952 次观看 • 1 个月前

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
3:38

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,594 次观看 • 1 年前

Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI
1:06:29

Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI

Matt Turck

11,971 次观看 • 1 年前

Astrophysicist David Kipping says science has crossed a real threshold. In a private gathering at the Institute for Advanced Study, leading physicists warned that AI now handles as much as “90%” of their work and could soon uncover truths humans can’t fully grasp. According to Kipping, emergency conversations are already underway among the world’s top scientists. Video: vitrupo
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Astrophysicist David Kipping says science has crossed a real threshold. In a private gathering at the Institute for Advanced Study, leading physicists warned that AI now handles as much as “90%” of their work and could soon uncover truths humans can’t fully grasp. According to Kipping, emergency conversations are already underway among the world’s top scientists. Video: vitrupo

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