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Whop CEO Steven Schwartz breaks down micro1's data labeling business: "There are so many ways that people can earn income on the internet today, and it's only going to get crazier and crazier." "[micro1] partners with AI labs to provide access to prerecorded videos and situations that the general... show more

TBPN

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46,713 просмотров • 7 месяцев назад •via X (Twitter)

Наука и технологии

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Whop 🤝 micro1 We’re excited to announce Whop is now the official payments network for micro1.

Whop 🤝 micro1 We’re excited to announce Whop is now the official payments network for micro1.

Whop

835,573 просмотров • 7 месяцев назад

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

Ali Ansari

332,574 просмотров • 7 месяцев назад

General Intuition CEO Pim de Witte, who's building foundation models trained on video game controller input data ("action-labeled gameplay clips"), says general intelligence won't "taste like an LLM": "We have a scale of data that's going to allow us to jump to the frontier in one capability — which is any system that can be controlled with a game controller (which is most robots) — and then, you can use that to create a sufficiently general intelligence." "As humans, the decision to talk or type is a very, very small subset of the actions that we can actually take." "So in order to create a sufficiently general intelligence to play 10,000+ video games, the model has to be able to predict across the entire action space of human cognition when they're interacting with these environments. Which are 2D and 3D environments, interfaces, long-horizon tasks, short-horizon tasks, [etc.]." "It has to be a sufficiently general intelligence in order to predict actions. Therefore, the type of model you get out is not going to taste like an LLM. This model is going to be incredibly good at navigating unforeseen environments. It's going to be incredibly good at zero-shotting any task that can be done with a game controller."

General Intuition CEO Pim de Witte, who's building foundation models trained on video game controller input data ("action-labeled gameplay clips"), says general intelligence won't "taste like an LLM": "We have a scale of data that's going to allow us to jump to the frontier in one capability — which is any system that can be controlled with a game controller (which is most robots) — and then, you can use that to create a sufficiently general intelligence." "As humans, the decision to talk or type is a very, very small subset of the actions that we can actually take." "So in order to create a sufficiently general intelligence to play 10,000+ video games, the model has to be able to predict across the entire action space of human cognition when they're interacting with these environments. Which are 2D and 3D environments, interfaces, long-horizon tasks, short-horizon tasks, [etc.]." "It has to be a sufficiently general intelligence in order to predict actions. Therefore, the type of model you get out is not going to taste like an LLM. This model is going to be incredibly good at navigating unforeseen environments. It's going to be incredibly good at zero-shotting any task that can be done with a game controller."

TBPN

79,134 просмотров • 10 дней назад

Design used to have a ton of variation until the iPhone came out, says Figma CEO Dylan Field. After that, Skeuomorphism and Swiss minimalism became the standard everyone copied. Dylan says that now, AI is causing the pendulum to swing back: "We can go into such interesting places, and try so many interesting patterns in the UX side, too. It's not just UI and the visuals. It's also the structure, the IA, the way that people navigate through these things. And I think there's innovation that's going to be flourishing on all of it." "People are going to try things we haven't seen in a while, and things people haven't seen, ever. Because that's what it's going to take to stand out now."

Design used to have a ton of variation until the iPhone came out, says Figma CEO Dylan Field. After that, Skeuomorphism and Swiss minimalism became the standard everyone copied. Dylan says that now, AI is causing the pendulum to swing back: "We can go into such interesting places, and try so many interesting patterns in the UX side, too. It's not just UI and the visuals. It's also the structure, the IA, the way that people navigate through these things. And I think there's innovation that's going to be flourishing on all of it." "People are going to try things we haven't seen in a while, and things people haven't seen, ever. Because that's what it's going to take to stand out now."

TBPN

66,929 просмотров • 4 месяцев назад

#1 Elon Musk says the mission of Twitter 2.0 is to be the most reliable source of information and to provide citizens with a way to control the narrative: "The goal is to have Twitter be the best source of truth, the most timely and accurate source of truth, even if the truth is something we don't want to hear or unpleasant. Not just is something true or not, but what is the narrative. Most people don't appreciate that the media controls the narrative, so there are many things that could be talked about in the world, but only a few things can fit on the front page. But Twitter doesn't have a limitation like that, so the public can control the narrative, and the public can inform themselves as to what the narrative should be. That's a really big deal. It's a forum for citizen journalism or for the public to get together and communicate in a way that was never possible before so you can really know what's going on."

#1 Elon Musk says the mission of Twitter 2.0 is to be the most reliable source of information and to provide citizens with a way to control the narrative: "The goal is to have Twitter be the best source of truth, the most timely and accurate source of truth, even if the truth is something we don't want to hear or unpleasant. Not just is something true or not, but what is the narrative. Most people don't appreciate that the media controls the narrative, so there are many things that could be talked about in the world, but only a few things can fit on the front page. But Twitter doesn't have a limitation like that, so the public can control the narrative, and the public can inform themselves as to what the narrative should be. That's a really big deal. It's a forum for citizen journalism or for the public to get together and communicate in a way that was never possible before so you can really know what's going on."

KanekoaTheGreat

1,650,088 просмотров • 3 лет назад

Etched CEO Gavin Uberti: "People don't realize how big of a market inference is going to be." "Right now, only a couple million people have access to the frontier models, and those are going to have to get deployed to 8 billion people across the globe. And that's not even counting AI agents that exist already, and will exist in the future." "There need to be way, way more tokens produced, and that requires much bigger assembly lines, many more factories, and some new technology."

Etched CEO Gavin Uberti: "People don't realize how big of a market inference is going to be." "Right now, only a couple million people have access to the frontier models, and those are going to have to get deployed to 8 billion people across the globe. And that's not even counting AI agents that exist already, and will exist in the future." "There need to be way, way more tokens produced, and that requires much bigger assembly lines, many more factories, and some new technology."

TBPN

62,252 просмотров • 9 дней назад

Sequoia's Ravi Gupta and Pat Grady on potential layoffs and why the AI doomers are wrong: "Technology is neither good nor bad, it's what we do with it. The same technology that powers a nuclear bomb can power a nuclear power plant." "A lot of what people are doing when they go and talk about the technology is they talk about all the things that might happen. I would rather us talk about the fact that it's going to get more and more powerful, and it's more and more incumbent on all of us to make sure we use it for something great." "If I could give my kids one thing, it wouldn't be kindness. It wouldn't be curiosity. It would be agency. The technology is going to be what all of us make of it."

Sequoia's Ravi Gupta and Pat Grady on potential layoffs and why the AI doomers are wrong: "Technology is neither good nor bad, it's what we do with it. The same technology that powers a nuclear bomb can power a nuclear power plant." "A lot of what people are doing when they go and talk about the technology is they talk about all the things that might happen. I would rather us talk about the fact that it's going to get more and more powerful, and it's more and more incumbent on all of us to make sure we use it for something great." "If I could give my kids one thing, it wouldn't be kindness. It wouldn't be curiosity. It would be agency. The technology is going to be what all of us make of it."

TBPN

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"The left won, and they don't even appreciate it. The world's first trillionaire has done more to solve environmental problems than everyone else on Earth combined." Gavin Baker: "This is a 'Bond villain' who's decarbonizing the world (last time I checked, people on the left like the environment), connecting people, schools, and hospitals in low-income countries to the internet at very low cost, and helping blind people see and interact with the world today. That's a villain?" "And there are so many parts to the $SPCX story. All of the blue-collar workers who've gotten super wealthy. If you're opposed to data centers on Earth, because of the environment? Well, SpaceX is your solution."

"The left won, and they don't even appreciate it. The world's first trillionaire has done more to solve environmental problems than everyone else on Earth combined." Gavin Baker: "This is a 'Bond villain' who's decarbonizing the world (last time I checked, people on the left like the environment), connecting people, schools, and hospitals in low-income countries to the internet at very low cost, and helping blind people see and interact with the world today. That's a villain?" "And there are so many parts to the $SPCX story. All of the blue-collar workers who've gotten super wealthy. If you're opposed to data centers on Earth, because of the environment? Well, SpaceX is your solution."

TBPN

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ELON: IT’S CRUCIAL THAT THE PEOPLE GET TO DECIDE WHAT MATTERS “With the Internet, anyone can learn anything at any time. That's why 𝕏 is the future. It's citizen journalism by the people, for the people. That's what it's all about. It's absolutely fundamental and transformative that the people actually get to decide the news and the narrative and what matters." Source: Town Hall in Lancaster, Pennsylvania, October 2024

ELON: IT’S CRUCIAL THAT THE PEOPLE GET TO DECIDE WHAT MATTERS “With the Internet, anyone can learn anything at any time. That's why 𝕏 is the future. It's citizen journalism by the people, for the people. That's what it's all about. It's absolutely fundamental and transformative that the people actually get to decide the news and the narrative and what matters." Source: Town Hall in Lancaster, Pennsylvania, October 2024

Mario Nawfal

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🚨 Chamath explains Grok 4's breakthrough and how Elon leapfrogged the competition in AI: Elon Musk and the team at xAI understood "The Bitter Lesson" by Richard Sutton Chamath Palihapitiya: "(The Bitter Lesson) basically says in a nutshell, that you're always better off, when you're trying to solve an AI problem, taking a general learning approach that can scale with computation. Because it ultimately proves to be the most effective." "The alternative would be something that's much more human labored and human involved that requires human knowledge." "So the first method, what it essentially allows you to do is view any problem as an endless, scalable search or learning task." "As it's turned out, whether it's chess, or Go, or speech recognition, or computer vision, whenever there was two competing approaches, one that used general computation and one that used human knowledge, the general computation problem always won." " And so it creates this bitter lesson for humans that want to think that we are at the center of all of this critical learning and all of these leaps, and what these results show is a general computational approach that doesn't require as much human labeling can actually get to the answer and better answers faster."

🚨 Chamath explains Grok 4's breakthrough and how Elon leapfrogged the competition in AI: Elon Musk and the team at xAI understood "The Bitter Lesson" by Richard Sutton Chamath Palihapitiya: "(The Bitter Lesson) basically says in a nutshell, that you're always better off, when you're trying to solve an AI problem, taking a general learning approach that can scale with computation. Because it ultimately proves to be the most effective." "The alternative would be something that's much more human labored and human involved that requires human knowledge." "So the first method, what it essentially allows you to do is view any problem as an endless, scalable search or learning task." "As it's turned out, whether it's chess, or Go, or speech recognition, or computer vision, whenever there was two competing approaches, one that used general computation and one that used human knowledge, the general computation problem always won." " And so it creates this bitter lesson for humans that want to think that we are at the center of all of this critical learning and all of these leaps, and what these results show is a general computational approach that doesn't require as much human labeling can actually get to the answer and better answers faster."

The All-In Podcast

597,321 просмотров • 1 год назад

⚡️Al Companies are offering up to $150/HR to watch you cook and clean to help train the next generation of humanoid robots that will be mass produced. A few of the companies offering pay are Encord, Micro1, and Scale Al.

⚡️Al Companies are offering up to $150/HR to watch you cook and clean to help train the next generation of humanoid robots that will be mass produced. A few of the companies offering pay are Encord, Micro1, and Scale Al.

Middle East Observer

20,110 просмотров • 8 месяцев назад

Sequoia's Carl Eschenbach on the founder traits that matter most when scaling a company: "One of the things I absolutely look for is self-awareness in founders, and are they honest about what they’re good at? Because a lot of these founders are just incredibly intelligent human beings, and sometimes they think they can do everything. Do they have the self-awareness to say, 'I need to go get other people as part of the company to help me scale so I can focus on what I’m really good at?'" "There are attributes and characteristics of people that I look for that are way beyond the intelligence side of the equation. You can’t teach grit. You can’t teach drive. You can’t teach a great attitude. You can’t teach determination." "All of those are things that are innate and part of people, and you want to see that in these founders. When you find someone who has that passion, drive, desire, and relentless ability to fight through challenges, issues, and opportunities — and then they have the intellectual horsepower on the other side — when that comes together, that’s a beautiful thing."

Sequoia's Carl Eschenbach on the founder traits that matter most when scaling a company: "One of the things I absolutely look for is self-awareness in founders, and are they honest about what they’re good at? Because a lot of these founders are just incredibly intelligent human beings, and sometimes they think they can do everything. Do they have the self-awareness to say, 'I need to go get other people as part of the company to help me scale so I can focus on what I’m really good at?'" "There are attributes and characteristics of people that I look for that are way beyond the intelligence side of the equation. You can’t teach grit. You can’t teach drive. You can’t teach a great attitude. You can’t teach determination." "All of those are things that are innate and part of people, and you want to see that in these founders. When you find someone who has that passion, drive, desire, and relentless ability to fight through challenges, issues, and opportunities — and then they have the intellectual horsepower on the other side — when that comes together, that’s a beautiful thing."

TBPN

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Introducing Trace. Trace is our flagship, public audit and search platform where every asset permanently registered on DATA Network can be accessed. AI Labs can search every human contributed photo or voice sample and drill into any individual record to see the full audit trail. Trace is where labs and regulators can filter by dataset, app, data type, modality, and time to verify data provenance so AI models can be trained with confidence.

Introducing Trace. Trace is our flagship, public audit and search platform where every asset permanently registered on DATA Network can be accessed. AI Labs can search every human contributed photo or voice sample and drill into any individual record to see the full audit trail. Trace is where labs and regulators can filter by dataset, app, data type, modality, and time to verify data provenance so AI models can be trained with confidence.

The DATA Foundation

68,103 просмотров • 15 дней назад

🔥🚨BREAKING: Al Companies are offering up to $150/HR to watch you cook and clean to help train the next generation of humanoid robots that will be mass produced. A few of the companies offering pay are Encord, Micro1, and Scale Al.

🔥🚨BREAKING: Al Companies are offering up to $150/HR to watch you cook and clean to help train the next generation of humanoid robots that will be mass produced. A few of the companies offering pay are Encord, Micro1, and Scale Al.

Dom Lucre | Breaker of Narratives

604,499 просмотров • 8 месяцев назад

Jim Clark called both NVIDIA and the internet before either existed: "Everything we sell today for $50,000 is going on a chip, on a card, on a PC, and it's going to cost $300. Either we're the company that makes that, or we get destroyed." "The function of the computer is no longer going to be mainly what just the computer does. It's going to be the fact that it can talk to all the other computers." Both predictions proved exactly right. The CEO said we'll deal with it in the future. Jim said by the time the future arrives, it's going to be too late. So he left and built the next company.

Jim Clark called both NVIDIA and the internet before either existed: "Everything we sell today for $50,000 is going on a chip, on a card, on a PC, and it's going to cost $300. Either we're the company that makes that, or we get destroyed." "The function of the computer is no longer going to be mainly what just the computer does. It's going to be the fact that it can talk to all the other computers." Both predictions proved exactly right. The CEO said we'll deal with it in the future. Jim said by the time the future arrives, it's going to be too late. So he left and built the next company.

David Senra

61,879 просмотров • 3 месяцев назад

Binance CEO CZ 🔶 BNB says the crypto industry is too transparent: "I think right now the crypto industry is too transparent. It's actually extremely easy to track crypto funds. The blockchain is a public ledger. If you couple that with a few centralized exchanges, KYC information, you can track most of the transactions pretty accurately. So I think right now there's a lack of preserving of privacy." "For example, if your company pays everybody in crypto and if you get one payment today on the blockchain, you can just trace to the address that paid you and see how many addresses that address paid in the last week, then you can figure out everybody's salary. That's a privacy issue." "Another example, if you pay for a hotel [in crypto], then people will know that you're going to stay at that hotel, which for some people may create security issues. So there's little problems like those that are not solved yet."

Binance CEO CZ 🔶 BNB says the crypto industry is too transparent: "I think right now the crypto industry is too transparent. It's actually extremely easy to track crypto funds. The blockchain is a public ledger. If you couple that with a few centralized exchanges, KYC information, you can track most of the transactions pretty accurately. So I think right now there's a lack of preserving of privacy." "For example, if your company pays everybody in crypto and if you get one payment today on the blockchain, you can just trace to the address that paid you and see how many addresses that address paid in the last week, then you can figure out everybody's salary. That's a privacy issue." "Another example, if you pay for a hotel [in crypto], then people will know that you're going to stay at that hotel, which for some people may create security issues. So there's little problems like those that are not solved yet."

TBPN

489,733 просмотров • 3 месяцев назад

.John Coogan says the recent reporting on Meta's 'tokenmaxxing' is less of a sign of bad incentives at the company, and more of a tell about its potential strategy for more vertical integration: "I think it makes clearer the strategy with MSL. Because it's clear that they're spending hundreds of millions of dollars on this, just for internal code-gen tooling — like, running their business." "They are going to spend an inordinate amount of money on frontier inference, and so [by] training a model there, they will be able to amortize the training cost of the next model they build not just over, 'Can they get a product out that goes viral and becomes its own standalone chat app that people pay for.'" "Just on the internal usage, they could be running a multi-billion-dollar token bill that they would have to pay another lab. And so if they develop that internally, it's pure vertical integration." "And then you also have everything that's happening on the actual ad targeting and content delivery side..." "The big question has been like, 'Is Meta going to be able to launch an entirely new AI product like Vibes or something like that?'" "And this is a data point that, to me, says they don't need to. Because just from a pure vertical integration [perspective], the investment in MSL can pencil out."

.John Coogan says the recent reporting on Meta's 'tokenmaxxing' is less of a sign of bad incentives at the company, and more of a tell about its potential strategy for more vertical integration: "I think it makes clearer the strategy with MSL. Because it's clear that they're spending hundreds of millions of dollars on this, just for internal code-gen tooling — like, running their business." "They are going to spend an inordinate amount of money on frontier inference, and so [by] training a model there, they will be able to amortize the training cost of the next model they build not just over, 'Can they get a product out that goes viral and becomes its own standalone chat app that people pay for.'" "Just on the internal usage, they could be running a multi-billion-dollar token bill that they would have to pay another lab. And so if they develop that internally, it's pure vertical integration." "And then you also have everything that's happening on the actual ad targeting and content delivery side..." "The big question has been like, 'Is Meta going to be able to launch an entirely new AI product like Vibes or something like that?'" "And this is a data point that, to me, says they don't need to. Because just from a pure vertical integration [perspective], the investment in MSL can pencil out."

TBPN

32,654 просмотров • 3 месяцев назад

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

TBPN

21,828 просмотров • 6 месяцев назад

Prime Intellect's will brown says continual learning could be solved in the first half of 2026: "Continual learning is going to fall pretty quickly, I think. It's more of an engineering problem. No one's actually trying." "OpenAI and Anthropic don't want to continuously train their models for each user. It's expensive and annoying and hard to serve at scale. But from a research perspective, we do continue learning where they just keep training the model more and it knows more stuff because they put more of the Internet in it." "I think there's a lot of experimentation around exactly the recipe that's going to be the most reliable. But we kind of have a grab bag of six or seven tricks that kind of work, or they work in different ways, and you can mix and match them. And it's just going to be like whatever's the best combination of these tricks." "People are going to experiment with it and find the versions that work the best. And there doesn't seem to be any big wall inside that prevents that from being practical."

Prime Intellect's will brown says continual learning could be solved in the first half of 2026: "Continual learning is going to fall pretty quickly, I think. It's more of an engineering problem. No one's actually trying." "OpenAI and Anthropic don't want to continuously train their models for each user. It's expensive and annoying and hard to serve at scale. But from a research perspective, we do continue learning where they just keep training the model more and it knows more stuff because they put more of the Internet in it." "I think there's a lot of experimentation around exactly the recipe that's going to be the most reliable. But we kind of have a grab bag of six or seven tricks that kind of work, or they work in different ways, and you can mix and match them. And it's just going to be like whatever's the best combination of these tricks." "People are going to experiment with it and find the versions that work the best. And there doesn't seem to be any big wall inside that prevents that from being practical."

TBPN

72,077 просмотров • 4 месяцев назад

"What is P vs NP and how does it relate to human knowledge?" Avi Wigderson (Turing Award & Abel Prize winner): "In a very basic way, all the problems we want to solve are really NP problems. A subset of it is the problems we can solve. So the question of P versus NP is whether we can solve all the problems we want to solve, whether we can know everything we want to know. This is basically about the limits of our knowledge. You can think there is no limit to what we may want to know but I claim that essentially in any human endeavor, what people are searching for have the property that when a solution is found, it is easily recognized. NP are all problems that we can honestly say we really want to solve and P are those that we can solve. Whether they are equal is just the very fact that a solution can be easily recognized would imply that it can be efficiently found. That means that we can know everything we ever want to know, it's a fundamental question about human knowledge."

"What is P vs NP and how does it relate to human knowledge?" Avi Wigderson (Turing Award & Abel Prize winner): "In a very basic way, all the problems we want to solve are really NP problems. A subset of it is the problems we can solve. So the question of P versus NP is whether we can solve all the problems we want to solve, whether we can know everything we want to know. This is basically about the limits of our knowledge. You can think there is no limit to what we may want to know but I claim that essentially in any human endeavor, what people are searching for have the property that when a solution is found, it is easily recognized. NP are all problems that we can honestly say we really want to solve and P are those that we can solve. Whether they are equal is just the very fact that a solution can be easily recognized would imply that it can be efficiently found. That means that we can know everything we ever want to know, it's a fundamental question about human knowledge."

Ryan Peterman

20,069 просмотров • 1 месяц назад