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𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗪𝗶𝗹𝗹 𝗕𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗮𝗯𝗹𝗲 𝗶𝗻 𝟭𝟮 𝗠𝗼𝗻𝘁𝗵𝘀 This is what Anthropic CEO Dario Amodei said at the World Economic Forum in Davos last week. His exact words: “I think we might be 6 to 12 months away from when the model is doing most, maybe all of what... SWEs do end-to-end.” It is a bold prediction, but the headlines omit the part about others' views. Demis Hassabis, Nobel Prize-winning CEO of Google DeepMind, said current AI is “𝘯𝘰𝘸𝘩𝘦𝘳𝘦 𝘯𝘦𝘢𝘳” human-level intelligence. He gives AGI a 50% chance within the decade and says we need “one or two more breakthroughs” beyond existing technology. Yann LeCun, Turing Award winner and former Meta AI chief, went further. He called the industry “𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦𝘭𝘺 𝘓𝘓𝘔-𝘱𝘪𝘭𝘭𝘦𝘥” and stated that large language models will never achieve human-level intelligence. Three of the most respected minds in AI. Fundamentally incompatible views. Same stage. The headlines also skip what Amodei actually described. His engineers “𝘥𝘰𝘯’𝘵 𝘸𝘳𝘪𝘵𝘦 𝘤𝘰𝘥𝘦 𝘢𝘯𝘺𝘮𝘰𝘳𝘦.” They let the model write it. They edit it. They do “𝘵𝘩𝘦 𝘵𝘩𝘪𝘯𝘨𝘴 𝘢𝘳𝘰𝘶𝘯𝘥 𝘪𝘵.” But this means, obviously, that it is not a replacement. That is role transformation. The engineer is still there, and important. We have seen this pattern before. Self-driving cars were supposed to be here by 2018. Level 5 autonomy was “𝘫𝘶𝘴𝘵 𝘢𝘳𝘰𝘶𝘯𝘥 𝘵𝘩𝘦 𝘤𝘰𝘳𝘯𝘦𝘳.” Tesla still requires hands on the wheel. LeCun put it like this: 𝗶𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗱𝗲𝗺𝗼𝘀 𝗱𝗼 𝗻𝗼𝘁 𝗲𝗾𝘂𝗮𝗹 𝗱𝗲𝗽𝗲𝗻𝗱𝗮𝗯𝗹𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁. There is a considerable distance between a demo and a system you put in people’s hands daily. But let's consider who benefits from this story. Amodei runs a company valued in the billions, competing for talent, funding, and market standing against OpenAI and Google. Bold predictions attract attention, investment, and impetus to adopt their products. This is not a conspiracy. This is an incentive structure. 𝗪𝗵𝗲𝗻 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝘁𝗲𝗹𝗹𝘀 𝘆𝗼𝘂 𝘁𝗵𝗲𝗶𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝘄𝗶𝗹𝗹 𝗰𝗵𝗮𝗻𝗴𝗲 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴, 𝗮𝘀𝗸 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝘀𝗲𝗹𝗹𝗶𝗻𝗴. The fundamental transformation is already here. AI coding tools make developers more productive. Anthropic’s Cowork product was built in a week and a half, almost entirely with their AI tools. But someone still decided what to build. Someone evaluated if it worked. Someone made architectural decisions. Someone owned the outcome. 𝗧𝗵𝗲 𝘀𝗵𝗶𝗳𝘁 𝗶𝘀 𝗳𝗿𝗼𝗺 𝘁𝘆𝗽𝗶𝗻𝗴 𝗰𝗼𝗱𝗲 𝘁𝗼 𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘁𝘆𝗽𝗲 𝗰𝗼𝗱𝗲. That requires different skills. No skills. The question is not whether AI will change software engineering. It already has. The question is whether, 12 months from now, we will look back on this prediction the way we look at 2018's self-driving promises. What do you think, is this a transformation or a hype cycle?show more

Dr Milan Milanović

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26,117 views • 5 months ago •via X (Twitter)

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One reason I stay a bit quite about AI these few months. I can’t find my voice to say this right. I’ll try. — What has my AI found just in the millions of never saved TV from the 1980s-1990s? The simple commercial, I have the largest collection known in the world is a reflection of hyper nuanced humanity. Frail and over optimistic as it is, it shows the sprit of humanity in ways that self-hating 2010 Internet sewage training AI can not. It is interesting to have dark humor, when you know the soul of the person with the humor. It is not interesting to have dark humor from an AI that was not trained on the human spirit. The human sprit is not math, coding and science. This is the OUTCOME of a human sprit. We are training AI backwards and we just can’t see it yet, but we will. I am doing may best as “some posted on X” who has no currency in the “big boy” AI world to save the human sprit. We will need it one day and most of this training material is being erased, trillions of bytes daily. This is the secret to truthful AI. This is the secret to AI that LOVES humanity. We don’t get this right soon, there will be little chance. The data is… Almost gone.

One reason I stay a bit quite about AI these few months. I can’t find my voice to say this right. I’ll try. — What has my AI found just in the millions of never saved TV from the 1980s-1990s? The simple commercial, I have the largest collection known in the world is a reflection of hyper nuanced humanity. Frail and over optimistic as it is, it shows the sprit of humanity in ways that self-hating 2010 Internet sewage training AI can not. It is interesting to have dark humor, when you know the soul of the person with the humor. It is not interesting to have dark humor from an AI that was not trained on the human spirit. The human sprit is not math, coding and science. This is the OUTCOME of a human sprit. We are training AI backwards and we just can’t see it yet, but we will. I am doing may best as “some posted on X” who has no currency in the “big boy” AI world to save the human sprit. We will need it one day and most of this training material is being erased, trillions of bytes daily. This is the secret to truthful AI. This is the secret to AI that LOVES humanity. We don’t get this right soon, there will be little chance. The data is… Almost gone.

Brian Roemmele

123,518 views • 1 year ago

The CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world. Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language models are a dead end for artificial intelligence. LeCun, who left Meta earlier this year to start his own AI lab, has been saying for years that LLMs cannot reason, cannot plan, and will never get us to human-level intelligence. Hassabis disagrees, and he said so directly. His position is that scaling laws are still working, foundation models are still getting more capable, and whatever AGI ends up looking like, LLMs will be a central part of it, not something that gets replaced. He does say there is roughly a 50/50 chance that one or two additional breakthroughs will be needed beyond scaling alone, things like better memory, long-term planning, and world models. But the core disagreement with LeCun is clear, Hassabis believes the current architecture is sound and the current path leads somewhere real. Two Nobel-recognized researchers, two founding figures of modern AI, now publicly on opposite sides of the most important technical question in the industry.

The CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world. Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language models are a dead end for artificial intelligence. LeCun, who left Meta earlier this year to start his own AI lab, has been saying for years that LLMs cannot reason, cannot plan, and will never get us to human-level intelligence. Hassabis disagrees, and he said so directly. His position is that scaling laws are still working, foundation models are still getting more capable, and whatever AGI ends up looking like, LLMs will be a central part of it, not something that gets replaced. He does say there is roughly a 50/50 chance that one or two additional breakthroughs will be needed beyond scaling alone, things like better memory, long-term planning, and world models. But the core disagreement with LeCun is clear, Hassabis believes the current architecture is sound and the current path leads somewhere real. Two Nobel-recognized researchers, two founding figures of modern AI, now publicly on opposite sides of the most important technical question in the industry.

Milk Road AI

130,649 views • 3 months ago

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 views • 1 month ago

Google just got executed by a Nobel Prize winner, the inventor of modern AI, and Donald Trump. They literally LOST the AI race in the most brutal way possible. Here is what happened: 5 days ago, Trump told Axios that Anthropic was a national security threat and warned that "people get put in prison immediately" for what the company had been doing with its frontier model exports. 4 days ago, Trump met Dario Amodei at the G7 AI Summit and walked out telling reporters Dario was a "nice guy, smart guy" who had "responded very responsibly." 3 days ago, Noam Shazeer, the co-author of "Attention Is All You Need" (the paper that invented the transformer architecture powering EVERY modern AI model on Earth), walked out of Google to join OpenAI. Yesterday, John Jumper, the 2024 Nobel Prize winner who co-created AlphaFold and ran Google DeepMind's protein structure team for nearly a decade, announced he was leaving to join Anthropic. And this is NOT a coincidence or a normal talent shuffle... Demis Hassabis, who shared the Nobel Prize with Jumper just 18 months ago, had to publicly THANK his own co-laureate for defecting to a rival lab. The man who shared the highest scientific honor in the world with you is now going to work for the people trying to put you out of business. This is what the end of a war looks like. The AI race was never going to be decided by chips, capital, or compute. There are only about 50 people on Earth who can actually build a frontier model from scratch. Google invented the field and trained most of them. They had the largest concentration of them anywhere on the planet. But in one week, two of the most important AI researchers alive betrayed them. And the actual reason is what's terrifying here: For nine months, the consensus take has been that Google's compute advantage would eventually win because talent is replaceable and compute is not. This week proved the opposite. Anthropic just secured a Nobel Prize winner whose work on AlphaFold opened the entire field of AI for biology. That is the same field every pharma company on Earth is desperately trying to enter. Anthropic now literally owns the most credentialed scientist in it. Meanwhile OpenAI just secured the actual inventor of the transformer. The man whose paper underpins every product Google has shipped in the last three years, including Gemini itself. Google has the compute but Google does not have the people who know what to do with it anymore. And the crazy part is that five days ago, Anthropic was effectively under siege. The administration was threatening PRISON, and the Mythos export crisis had triggered a federal block. Their largest investor was reportedly working against them while the company was hours from an existential national security designation that would have frozen them out of federal contracts. But four days later, Trump cleared them in public, they secured the most decorated AI researcher of the decade, and the entire frontier AI duopoly locked in with Anthropic in pole position. The fastest reversal of fortune in modern corporate history. "It's a two-horse race at the frontier. Google is effectively out." Wall Street wakes up to this in six months and starts downgrading Alphabet. But the smart money already knows. Anthropic is being whispered at a $2 trillion valuation. OpenAI is approaching $500 billion in the private market. Gemini 3.5 Pro has been delayed with no public timeline. The AI race literally ended this week. What do you think?

Google just got executed by a Nobel Prize winner, the inventor of modern AI, and Donald Trump. They literally LOST the AI race in the most brutal way possible. Here is what happened: 5 days ago, Trump told Axios that Anthropic was a national security threat and warned that "people get put in prison immediately" for what the company had been doing with its frontier model exports. 4 days ago, Trump met Dario Amodei at the G7 AI Summit and walked out telling reporters Dario was a "nice guy, smart guy" who had "responded very responsibly." 3 days ago, Noam Shazeer, the co-author of "Attention Is All You Need" (the paper that invented the transformer architecture powering EVERY modern AI model on Earth), walked out of Google to join OpenAI. Yesterday, John Jumper, the 2024 Nobel Prize winner who co-created AlphaFold and ran Google DeepMind's protein structure team for nearly a decade, announced he was leaving to join Anthropic. And this is NOT a coincidence or a normal talent shuffle... Demis Hassabis, who shared the Nobel Prize with Jumper just 18 months ago, had to publicly THANK his own co-laureate for defecting to a rival lab. The man who shared the highest scientific honor in the world with you is now going to work for the people trying to put you out of business. This is what the end of a war looks like. The AI race was never going to be decided by chips, capital, or compute. There are only about 50 people on Earth who can actually build a frontier model from scratch. Google invented the field and trained most of them. They had the largest concentration of them anywhere on the planet. But in one week, two of the most important AI researchers alive betrayed them. And the actual reason is what's terrifying here: For nine months, the consensus take has been that Google's compute advantage would eventually win because talent is replaceable and compute is not. This week proved the opposite. Anthropic just secured a Nobel Prize winner whose work on AlphaFold opened the entire field of AI for biology. That is the same field every pharma company on Earth is desperately trying to enter. Anthropic now literally owns the most credentialed scientist in it. Meanwhile OpenAI just secured the actual inventor of the transformer. The man whose paper underpins every product Google has shipped in the last three years, including Gemini itself. Google has the compute but Google does not have the people who know what to do with it anymore. And the crazy part is that five days ago, Anthropic was effectively under siege. The administration was threatening PRISON, and the Mythos export crisis had triggered a federal block. Their largest investor was reportedly working against them while the company was hours from an existential national security designation that would have frozen them out of federal contracts. But four days later, Trump cleared them in public, they secured the most decorated AI researcher of the decade, and the entire frontier AI duopoly locked in with Anthropic in pole position. The fastest reversal of fortune in modern corporate history. "It's a two-horse race at the frontier. Google is effectively out." Wall Street wakes up to this in six months and starts downgrading Alphabet. But the smart money already knows. Anthropic is being whispered at a $2 trillion valuation. OpenAI is approaching $500 billion in the private market. Gemini 3.5 Pro has been delayed with no public timeline. The AI race literally ended this week. What do you think?

Ricardo

90,843 views • 1 month ago

"Selling AI chips to China is like selling nuclear weapons to North Korea." The Anthropic CEO just went to war with Nvidia at Davos. And dropped the most terrifying satisfying prediction about AI I've ever heard. Dario Amodei and Demis Hassabis sat on the same stage for the first time in a year. The two men building the most powerful AI systems on Earth. The conversation was called "The Day After AGI." And it turned into a countdown clock. Here's what they revealed about our future: Amodei said we're 6-12 months away from AI doing EVERYTHING software engineers do. End to end. Not helping with code. Not writing snippets. REPLACING the entire function. "I have engineers at Anthropic who say I don't write any code anymore. I just let the model write the code." That's the CEO of a $183 billion company telling you his own engineers are becoming obsolete. Inside his own building. Right now. But that's not even the scary part. The scary part is the LOOP: AI writes code → AI does AI research → AI builds better AI → Repeat Once this closes, human progress becomes irrelevant. It's exponential compounding with no ceiling. Amodei's exact words: "If I had to guess, this goes faster than people imagine." Hassabis didn't disagree. Two competitors building the same technology. Same timeline. Same warning. On jobs, Amodei said: "Half of entry-level white-collar jobs could be gone within one to five years." He's already seeing it internally. "I can look forward to a time where on the junior end and the intermediate end, we actually need less and not more people." The CEO of an AI company planning for FEWER employees. While revenue 10x'd. Think about that. Hassabis's advice for students: "If I was talking to undergrads right now, I would tell them to get unbelievably proficient with these tools." Translation: Your degree means nothing. Learn to work WITH the machine or get replaced BY it. Then Amodei went full existential... He quoted Contact. The 1997 alien movie: "If you could ask aliens one question, what would it be?" The answer: "How did you do it? How did you manage to get through this technological adolescence without destroying yourselves?" That's the frame he uses for AI. The guy BUILDING AGI is publicly wondering if humanity survives what he's creating. At Davos. In front of world leaders. Then he dropped the Nvidia bomb. The US just approved chip exports to China. Amodei's response: "I think of this more as like selling nuclear weapons to North Korea and bragging 'oh yeah, Boeing made the case.'" He called it "crazy." Said there would be "grave consequences." The man building the technology is telling governments they're making catastrophic mistakes. But nobody's listening. When asked why they can't just slow down: "We have geopolitical adversaries building the same technology at a similar pace. It's very hard to have an enforceable agreement." So basically we CAN'T stop even if we wanted to. The race has no brakes. But it's interesting that both have different timelines when it comes to AGI. Amodei: AGI by 2026-2027 Hassabis: 50% chance by end of decade But both also say the self-improvement loop is the only variable that matters If AI builds AI, everything accelerates beyond control. If it can't, we get more time. We're about to find out which reality we're in. Amodei's final words: "The biggest thing to watch is AI systems building AI systems. That will determine whether it's a few more years or whether we have wonders and a great emergency in front of us." Wonders AND emergency. Same sentence. From the man running the second-most-advanced AI lab on the planet. The day after AGI is arriving. And it feels like the people building it are more terrified than we are.

"Selling AI chips to China is like selling nuclear weapons to North Korea." The Anthropic CEO just went to war with Nvidia at Davos. And dropped the most terrifying satisfying prediction about AI I've ever heard. Dario Amodei and Demis Hassabis sat on the same stage for the first time in a year. The two men building the most powerful AI systems on Earth. The conversation was called "The Day After AGI." And it turned into a countdown clock. Here's what they revealed about our future: Amodei said we're 6-12 months away from AI doing EVERYTHING software engineers do. End to end. Not helping with code. Not writing snippets. REPLACING the entire function. "I have engineers at Anthropic who say I don't write any code anymore. I just let the model write the code." That's the CEO of a $183 billion company telling you his own engineers are becoming obsolete. Inside his own building. Right now. But that's not even the scary part. The scary part is the LOOP: AI writes code → AI does AI research → AI builds better AI → Repeat Once this closes, human progress becomes irrelevant. It's exponential compounding with no ceiling. Amodei's exact words: "If I had to guess, this goes faster than people imagine." Hassabis didn't disagree. Two competitors building the same technology. Same timeline. Same warning. On jobs, Amodei said: "Half of entry-level white-collar jobs could be gone within one to five years." He's already seeing it internally. "I can look forward to a time where on the junior end and the intermediate end, we actually need less and not more people." The CEO of an AI company planning for FEWER employees. While revenue 10x'd. Think about that. Hassabis's advice for students: "If I was talking to undergrads right now, I would tell them to get unbelievably proficient with these tools." Translation: Your degree means nothing. Learn to work WITH the machine or get replaced BY it. Then Amodei went full existential... He quoted Contact. The 1997 alien movie: "If you could ask aliens one question, what would it be?" The answer: "How did you do it? How did you manage to get through this technological adolescence without destroying yourselves?" That's the frame he uses for AI. The guy BUILDING AGI is publicly wondering if humanity survives what he's creating. At Davos. In front of world leaders. Then he dropped the Nvidia bomb. The US just approved chip exports to China. Amodei's response: "I think of this more as like selling nuclear weapons to North Korea and bragging 'oh yeah, Boeing made the case.'" He called it "crazy." Said there would be "grave consequences." The man building the technology is telling governments they're making catastrophic mistakes. But nobody's listening. When asked why they can't just slow down: "We have geopolitical adversaries building the same technology at a similar pace. It's very hard to have an enforceable agreement." So basically we CAN'T stop even if we wanted to. The race has no brakes. But it's interesting that both have different timelines when it comes to AGI. Amodei: AGI by 2026-2027 Hassabis: 50% chance by end of decade But both also say the self-improvement loop is the only variable that matters If AI builds AI, everything accelerates beyond control. If it can't, we get more time. We're about to find out which reality we're in. Amodei's final words: "The biggest thing to watch is AI systems building AI systems. That will determine whether it's a few more years or whether we have wonders and a great emergency in front of us." Wonders AND emergency. Same sentence. From the man running the second-most-advanced AI lab on the planet. The day after AGI is arriving. And it feels like the people building it are more terrified than we are.

Ricardo

441,253 views • 6 months ago

Everyone’s talking about what Jensen said at GTC about AI capex. But the most important thing he said got almost no attention — that software companies are about to become the biggest resellers of AI tokens in the world. Think about what that means. Workday buys raw intelligence from OpenAI. Wraps it in HR domain expertise. Sells it back as an AI product at a massive markup. That’s not a software company anymore. That’s a refinery. And right now nobody is tracking the economics of that refining layer — what the crude costs, what the refined product sells for, and who’s capturing the spread. This is the most important data gap in AI right now. More on this soon. $NVDA

Everyone’s talking about what Jensen said at GTC about AI capex. But the most important thing he said got almost no attention — that software companies are about to become the biggest resellers of AI tokens in the world. Think about what that means. Workday buys raw intelligence from OpenAI. Wraps it in HR domain expertise. Sells it back as an AI product at a massive markup. That’s not a software company anymore. That’s a refinery. And right now nobody is tracking the economics of that refining layer — what the crude costs, what the refined product sells for, and who’s capturing the spread. This is the most important data gap in AI right now. More on this soon. $NVDA

Midnight Capital LLC

40,075 views • 4 months ago

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)

Rohan Paul

79,111 views • 1 month ago

The smartest man in AI just exposed the whole AGI narrative as a LIE. And he used a physics problem from 1905 to prove it. His name is Demis Hassabis. He runs Google DeepMind, and won the Nobel Prize for using AI to crack a problem in biology that had stumped scientists for 50 years. Almost nobody in this industry has a track record like his. He went on the NothingButTech podcast and called out the biggest lie in AI right now: Right now the loudest voices in AI are telling you that AGI is basically here. OpenAI has literally defined AGI as a system that can outperform humans at most "economically valuable work." In other words, if it replaces enough jobs, we have arrived. Hassabis thinks that bar is a joke. He said real general intelligence has to do what the human brain can do, because the brain is the only proof we have that this kind of intelligence is even possible. He called that "a higher bar than just being able to do some useful economic work," which is about as close as a polite British Nobel laureate gets to calling his rivals out. Then he gave the actual test: Today's AI has read everything humans have ever written, including the theory of relativity. So when it explains relativity back to you, it's repeating an answer that already exists. That's not intelligence. So Hassabis proposed a test that makes memorization impossible. Train an AI on only what humanity knew in 1901, four years BEFORE Einstein published relativity. Then ask it to come up with relativity on its own. It can't look up the answer, because in 1901 the answer doesn't exist yet. The only way to pass is to do what Einstein actually did: Take the same physics everyone else had and reason its way to an idea no human had ever had. Hassabis says not a single AI today can, no matter how much it has memorized. Which means what we keep calling "almost AGI" is really just the best librarian in history. It can find any answer that already exists but it cannot create one that doesn't. His second version is even sharper: AlphaGo, the system his own team built, famously invented a brand new move that no human had played in 2,000 years of the game. Everyone called it genius but Hassabis says that still is not the bar. The real test is not whether an AI can invent a new move inside Go, it is whether an AI could INVENT a game as deep and as beautiful as Go in the first place. No model that exists today can do it. The people telling you AGI has already arrived are the same people raising hundreds of billions of dollars on that exact promise. The valuations only work if the finish line is right in front of us. So the finish line keeps getting dragged closer, and AGI keeps getting quietly redefined down to "does useful work," until the products they already sell happen to qualify. Hassabis has nothing to prove and nothing to sell you. He already won the Nobel, and he is telling you the machines still cannot do the one thing that would make them genuinely intelligent, which is have a truly original idea. To be fair to him, he is not a pessimist about it. He believes real AGI IS coming, and he is spending his life building it. He just refuses to pretend it is already sitting in your phone. So the next time a founder tells you AGI is months away, remember that the one man in the room with a Nobel Prize built his test around Einstein, and admitted that nothing we have made can pass it. What do you think?

Ricardo

1,284,988 views • 1 month ago

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.

Dustin

16,132 views • 3 months ago

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,976 views • 22 days ago

This Google insider just revealed what AI is actually being used for behind closed doors. It has nothing to do with chatbots. Mo Gawdat was a senior executive at Google for over a decade. He watched AI get built from the inside. He was in the rooms, in the labs, in the government meetings in China that almost no Western executive was allowed into. And he just went on Diary of a CEO and said things that no active tech executive would ever be allowed to say publicly: "What the general public sees about AI is overhyped but ineffective. What the real geeks see inside the lab is genuinely world-changing." The public gets chatbots and AI-generated videos while the labs are building autonomous weapons systems, military targeting technology, real-time surveillance infrastructure, and self-improving code that rewrites itself every microsecond without human oversight. As Mo put it: "As we speak, we are living in two major wars where AI is doing most of the killing." He talked about Palantir's CEO Alex Karp openly celebrating how his targeting technology identifies and eliminates people. He talked about the next generation of autonomous weapons costing $20,000 each, meaning any government with a $50 billion defense budget can literally rain drones on every corner of the planet. And as you remember, Anthropic was offered a $500 million military contract to allow their AI to be used for human targeting and surveillance. They refused and walked away from the money. OpenAI took the contract the following week. Mo's response: "You have to start observing who is actually behaving in a way that makes AI work for humanity, and who is behaving in a way that makes AI work for their share price." Now this is where it gets really interesting... In Mo's documentary Chasing Utopia, Altman literally says directly on camera: "I suspect that AI is likely going to end humanity, but we're going to create a lot of interesting companies in the process." That is the CEO of the most powerful AI company on Earth saying that he suspects his OWN technology will end the human race and then shrugging it off because the business opportunity is too good to pass up. Mo's prediction for the next decade: War, economic collapse, mass unemployment, surveillance expansion, and an absolute concentration of power at the top unlike anything in modern history. His prediction after that is if humanity survives the next 10 years, AI will eventually create a world of abundance where intelligence solves every problem we currently face. But the path between here and there is what terrifies him. And the men building the technology know exactly what they're doing. Do you think he's just exaggerating for attention, or is there truth in this?

This Google insider just revealed what AI is actually being used for behind closed doors. It has nothing to do with chatbots. Mo Gawdat was a senior executive at Google for over a decade. He watched AI get built from the inside. He was in the rooms, in the labs, in the government meetings in China that almost no Western executive was allowed into. And he just went on Diary of a CEO and said things that no active tech executive would ever be allowed to say publicly: "What the general public sees about AI is overhyped but ineffective. What the real geeks see inside the lab is genuinely world-changing." The public gets chatbots and AI-generated videos while the labs are building autonomous weapons systems, military targeting technology, real-time surveillance infrastructure, and self-improving code that rewrites itself every microsecond without human oversight. As Mo put it: "As we speak, we are living in two major wars where AI is doing most of the killing." He talked about Palantir's CEO Alex Karp openly celebrating how his targeting technology identifies and eliminates people. He talked about the next generation of autonomous weapons costing $20,000 each, meaning any government with a $50 billion defense budget can literally rain drones on every corner of the planet. And as you remember, Anthropic was offered a $500 million military contract to allow their AI to be used for human targeting and surveillance. They refused and walked away from the money. OpenAI took the contract the following week. Mo's response: "You have to start observing who is actually behaving in a way that makes AI work for humanity, and who is behaving in a way that makes AI work for their share price." Now this is where it gets really interesting... In Mo's documentary Chasing Utopia, Altman literally says directly on camera: "I suspect that AI is likely going to end humanity, but we're going to create a lot of interesting companies in the process." That is the CEO of the most powerful AI company on Earth saying that he suspects his OWN technology will end the human race and then shrugging it off because the business opportunity is too good to pass up. Mo's prediction for the next decade: War, economic collapse, mass unemployment, surveillance expansion, and an absolute concentration of power at the top unlike anything in modern history. His prediction after that is if humanity survives the next 10 years, AI will eventually create a world of abundance where intelligence solves every problem we currently face. But the path between here and there is what terrifies him. And the men building the technology know exactly what they're doing. Do you think he's just exaggerating for attention, or is there truth in this?

Ricardo

197,369 views • 1 month ago

.David Deutsch: "What's currently called AI and AGI are not only different from each other, they are very close to being the exact opposites of each other. The reason is that an AI, current AI is like an AI that diagnoses diseases or an AI that plays chess or an AI that controls a huge factory. Those things have objective functions, that is they have a function that they are designed to maximize and that is why they are used in those particular applications. Or in military terms, you could say the objective is to hit the target. You might say the objective is to hit the target unless some thing specified, but it's a specified thing comes up in which case don't hit the target and so on. This is, as I said, almost the opposite of what humans do when humans think. For a start, the AI has to be obedient, that is it has to actually do the things it is programmed to do, whereas a human is fundamentally disobedient, especially when being creative. When a human plays chess, they are performing a completely different kind of computation. They don't do the same things, they don't investigate the same possibilities that the artificial chess playing machine does, because the artificial one is capable of looking at billions and billions of possibilities, whereas the human can only look at hundreds or something. They are doing something completely different. Another difference is that the human can explain, can write a book later, having become world champion, can write a book saying how I did it, as the computer program that beats the world champion can write no such book, because it has no idea how it did it. It was just following a program. I was doing this and that and that and none of that is illuminating. Also, third thing, the chess player can decide I don't want to play chess anymore, from now on I will play Go or from now on I will play tennis. If commanded to play chess, the functionality will deteriorate completely. Those things are different. What we want in an AGI is that it behaves in a way that cannot be specified in advance, because if you specified it, you would already have the answer. The AGI program has to give unexpected answers, answers to questions we didn't even know how to ask."

.David Deutsch: "What's currently called AI and AGI are not only different from each other, they are very close to being the exact opposites of each other. The reason is that an AI, current AI is like an AI that diagnoses diseases or an AI that plays chess or an AI that controls a huge factory. Those things have objective functions, that is they have a function that they are designed to maximize and that is why they are used in those particular applications. Or in military terms, you could say the objective is to hit the target. You might say the objective is to hit the target unless some thing specified, but it's a specified thing comes up in which case don't hit the target and so on. This is, as I said, almost the opposite of what humans do when humans think. For a start, the AI has to be obedient, that is it has to actually do the things it is programmed to do, whereas a human is fundamentally disobedient, especially when being creative. When a human plays chess, they are performing a completely different kind of computation. They don't do the same things, they don't investigate the same possibilities that the artificial chess playing machine does, because the artificial one is capable of looking at billions and billions of possibilities, whereas the human can only look at hundreds or something. They are doing something completely different. Another difference is that the human can explain, can write a book later, having become world champion, can write a book saying how I did it, as the computer program that beats the world champion can write no such book, because it has no idea how it did it. It was just following a program. I was doing this and that and that and none of that is illuminating. Also, third thing, the chess player can decide I don't want to play chess anymore, from now on I will play Go or from now on I will play tennis. If commanded to play chess, the functionality will deteriorate completely. Those things are different. What we want in an AGI is that it behaves in a way that cannot be specified in advance, because if you specified it, you would already have the answer. The AGI program has to give unexpected answers, answers to questions we didn't even know how to ask."

Deutsch Explains

72,455 views • 1 year ago

$Dario Amodei just revealed the exact realization that fractured OpenAI. It happened while building the most powerful AI in the world. The team discovered that scaling had no ceiling. Amodei: “If you pour more compute into these models, they’ll get better and better, and that there’s almost no end to this.” At the time, almost nobody believed it. Amodei’s group were among the first to see it clearly. More compute meant more intelligence. Indefinitely. Without limit. That should have been the most exciting discovery in the history of technology. It terrified them. Because they saw the second half of the equation the industry was ignoring entirely. Amodei: “You don’t tell the models what their values are just by pouring more compute into them.” Intelligence scales with compute. Values don’t. You can build a mind of unlimited capability and it will have no moral compass unless you deliberately build one in. Not as a feature. Not as a guardrail bolted on at the end. As the foundation the entire system is constructed on. This wasn’t a philosophical disagreement. It was an existential one. A god-like intelligence with no alignment isn’t a powerful tool. It’s an uncontrolled force with no reason to care about the species that built it. Amodei: “There were a set of people who believed in those two ideas. We really trusted each other and wanted to work together, and so we went off and started our own company with that idea in mind.” They walked out of the most powerful AI lab on earth. Not for better funding. Not for equity. Because they believed the path OpenAI was on led somewhere nobody could walk back from. That small group became Anthropic. Safety wasn’t a feature they added. It was the entire reason the company exists. The intelligence is going to keep scaling. There is almost no end to it. The only question that has ever mattered is what it’s pointing at when it gets there.$

Dario Amodei just revealed the exact realization that fractured OpenAI. It happened while building the most powerful AI in the world. The team discovered that scaling had no ceiling. Amodei: “If you pour more compute into these models, they’ll get better and better, and that there’s almost no end to this.” At the time, almost nobody believed it. Amodei’s group were among the first to see it clearly. More compute meant more intelligence. Indefinitely. Without limit. That should have been the most exciting discovery in the history of technology. It terrified them. Because they saw the second half of the equation the industry was ignoring entirely. Amodei: “You don’t tell the models what their values are just by pouring more compute into them.” Intelligence scales with compute. Values don’t. You can build a mind of unlimited capability and it will have no moral compass unless you deliberately build one in. Not as a feature. Not as a guardrail bolted on at the end. As the foundation the entire system is constructed on. This wasn’t a philosophical disagreement. It was an existential one. A god-like intelligence with no alignment isn’t a powerful tool. It’s an uncontrolled force with no reason to care about the species that built it. Amodei: “There were a set of people who believed in those two ideas. We really trusted each other and wanted to work together, and so we went off and started our own company with that idea in mind.” They walked out of the most powerful AI lab on earth. Not for better funding. Not for equity. Because they believed the path OpenAI was on led somewhere nobody could walk back from. That small group became Anthropic. Safety wasn’t a feature they added. It was the entire reason the company exists. The intelligence is going to keep scaling. There is almost no end to it. The only question that has ever mattered is what it’s pointing at when it gets there.

Dustin

52,414 views • 5 months ago

$GOOGL CEO Sundar Pichai on the AI Bubble: "There is some irrationality in the current AI boom. The growth of AI investment has been an extraordinary moment. Asked what happens if the AI bubble pops, he said "I think NO company is going to be immune, including us." We can look back at the internet. There was clearly a lot of excess investment, but none of us would question whether the internet was profound. I expect AI to be the same. It is both rational and there are elements of irrationality through a moment like this. AI is the most profound technology humankind has worked on. It will evolve and transition certain jobs, and people will need to adapt... the people who will do well are people who learn how to use these tools." Source: BBC

$GOOGL CEO Sundar Pichai on the AI Bubble: "There is some irrationality in the current AI boom. The growth of AI investment has been an extraordinary moment. Asked what happens if the AI bubble pops, he said "I think NO company is going to be immune, including us." We can look back at the internet. There was clearly a lot of excess investment, but none of us would question whether the internet was profound. I expect AI to be the same. It is both rational and there are elements of irrationality through a moment like this. AI is the most profound technology humankind has worked on. It will evolve and transition certain jobs, and people will need to adapt... the people who will do well are people who learn how to use these tools." Source: BBC

Wall St Engine

406,054 views • 8 months ago

Andrew Ng, co-founder of Google Brain and Coursera, on the worst career advice being given about AI right now: He doesn't mince words about what he's hearing from supposed experts: "As early as earlier this year and certainly last year, there are a few people advising others to stop learning to write code because AI will automate it." His reasoning is rooted in a historical pattern most people miss: "As something becomes easier, more people should do it, not fewer. When the world moved from assembly language to COBOL, there were actually articles saying, 'Well, we now have COBOL. Programming is so easier. Looks like we don't need programmers anymore.' But the opposite happened." Andrew believes the same thing is happening now with AI-assisted coding: "As we now have AI assisted coding, a lot more people should be coding. And I think the demand for software, custom software, has no practical ceiling. So the cost of software engineering comes down, which it is, we'll just get more and more great software out in the world." But here's where the advice gets uncomfortable for experienced engineers. Andrew Ng is honest about what he's seeing on the ground: "It is true that a fresh college grad that is really on top of AI will outperform a full stack engineer with 10 years of experience that is still doing things they were back in 2022, 3 years ago before GenAI." However, there's a nuance most people miss when they hear that stereotype: "The other piece that is less well appreciated is the best engineers I know are not fresh college grads. They're actually very experienced engineers that deeply understand architecture and the conceptual framework of how to think about computers and additionally are on top of AI and on top of these AI skills."

Andrew Ng, co-founder of Google Brain and Coursera, on the worst career advice being given about AI right now: He doesn't mince words about what he's hearing from supposed experts: "As early as earlier this year and certainly last year, there are a few people advising others to stop learning to write code because AI will automate it." His reasoning is rooted in a historical pattern most people miss: "As something becomes easier, more people should do it, not fewer. When the world moved from assembly language to COBOL, there were actually articles saying, 'Well, we now have COBOL. Programming is so easier. Looks like we don't need programmers anymore.' But the opposite happened." Andrew believes the same thing is happening now with AI-assisted coding: "As we now have AI assisted coding, a lot more people should be coding. And I think the demand for software, custom software, has no practical ceiling. So the cost of software engineering comes down, which it is, we'll just get more and more great software out in the world." But here's where the advice gets uncomfortable for experienced engineers. Andrew Ng is honest about what he's seeing on the ground: "It is true that a fresh college grad that is really on top of AI will outperform a full stack engineer with 10 years of experience that is still doing things they were back in 2022, 3 years ago before GenAI." However, there's a nuance most people miss when they hear that stereotype: "The other piece that is less well appreciated is the best engineers I know are not fresh college grads. They're actually very experienced engineers that deeply understand architecture and the conceptual framework of how to think about computers and additionally are on top of AI and on top of these AI skills."

Big Brain AI

211,593 views • 2 months ago

Dario Amodei just dismantled the biggest myth in the AI industry. Open source AI isn’t free. It never was. Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.” For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants. That was genuine democratization. That actually happened. AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet. Downloading the weights is the easy part. The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale. That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction. Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.” The open source debate was never about who owns the model. It was always about who owns the cloud. And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology. Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.” That’s the ruthless clarity of someone actually trying to win. While the media debates licensing frameworks, Amodei is asking one question. Is it better. Everything else is a distraction. Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.” This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited. You can download it. And then you need a data center to run it. The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts. The era of the basement coder rewriting civilization on a laptop is over. The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on. Open weights without infrastructure isn’t democratization. It’s a promise the physics of the universe won’t let us keep.

Dario Amodei just dismantled the biggest myth in the AI industry. Open source AI isn’t free. It never was. Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.” For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants. That was genuine democratization. That actually happened. AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet. Downloading the weights is the easy part. The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale. That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction. Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.” The open source debate was never about who owns the model. It was always about who owns the cloud. And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology. Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.” That’s the ruthless clarity of someone actually trying to win. While the media debates licensing frameworks, Amodei is asking one question. Is it better. Everything else is a distraction. Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.” This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited. You can download it. And then you need a data center to run it. The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts. The era of the basement coder rewriting civilization on a laptop is over. The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on. Open weights without infrastructure isn’t democratization. It’s a promise the physics of the universe won’t let us keep.

Dustin

686,754 views • 4 months ago

Chamath: Anthropic's Mythos Warning Is Theater @jason: “Chamath, is it the Boy who Cried Wolf, or is this the real deal now?” Chamath Palihapitiya: “I think it's mostly theater. In February of 2019 when Dario was still at OpenAI, they did the same thing with GPT-2. That was a 1.5 billion parameter model, which sounds like a total fart in the wind in 2026. But at that time, this model was supposed to be the end of days. And at the end of it, it was a huge nothingburger. If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is, a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about five years to patch them all. So when you see a large multi-trillion dollar GSIB bank, it's a bit of theater. Why? What do you think they can actually accomplish in two months? Do you actually think that if there's these vulnerabilities, it's all going to get fixed? Let's give them six months, let's give them nine months. So I do think that Sacks is right, that they have figured out a very clever go-to-market muscle here that activates hyper attention and hyper usage, and so I give them tremendous credit. But we've seen it before, we saw it when these folks were the principal architects at OpenAI, and we're now seeing the same playbook here. The reality is that capitalism moves forward, the funding needs moves forward, and the need for these guys to build adoption moves forward. And that's going to supersede what this is.”

Chamath: Anthropic's Mythos Warning Is Theater @jason: “Chamath, is it the Boy who Cried Wolf, or is this the real deal now?” Chamath Palihapitiya: “I think it's mostly theater. In February of 2019 when Dario was still at OpenAI, they did the same thing with GPT-2. That was a 1.5 billion parameter model, which sounds like a total fart in the wind in 2026. But at that time, this model was supposed to be the end of days. And at the end of it, it was a huge nothingburger. If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is, a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about five years to patch them all. So when you see a large multi-trillion dollar GSIB bank, it's a bit of theater. Why? What do you think they can actually accomplish in two months? Do you actually think that if there's these vulnerabilities, it's all going to get fixed? Let's give them six months, let's give them nine months. So I do think that Sacks is right, that they have figured out a very clever go-to-market muscle here that activates hyper attention and hyper usage, and so I give them tremendous credit. But we've seen it before, we saw it when these folks were the principal architects at OpenAI, and we're now seeing the same playbook here. The reality is that capitalism moves forward, the funding needs moves forward, and the need for these guys to build adoption moves forward. And that's going to supersede what this is.”

The All-In Podcast

220,049 views • 3 months ago

Dario Amodei, the CEO of Anthropic, went on CNN and put a number on the thing most AI CEOs will not say out loud: Half of all entry-level white-collar jobs gone. Unemployment at 10 to 20%. Inside 1 to 5 years. "The most salient feature of the technology, and what is driving all of this, is how fast the technology is getting better." "A couple of years ago, you could say that AI models were maybe as good as a smart high school student. I would say that now they're as good as a smart college student, and sort of reaching past that." "I really worry, particularly at the entry level, that the AI models are very much at the center of what an entry level human worker would do." "What is striking to me about this AI boom is that it's bigger and it's broader and it's moving faster than anything has before." "People will adapt, but they may not adapt fast enough. And so there may be an adjustment period." The tell: this is not a critic outside the industry. It is the man building the models saying the quiet part on camera -- because he thinks the people whose jobs are on the line adapt slower than the models improve. High school to college in two years was the warm-up. The entry level is where it lands first.

Dario Amodei, the CEO of Anthropic, went on CNN and put a number on the thing most AI CEOs will not say out loud: Half of all entry-level white-collar jobs gone. Unemployment at 10 to 20%. Inside 1 to 5 years. "The most salient feature of the technology, and what is driving all of this, is how fast the technology is getting better." "A couple of years ago, you could say that AI models were maybe as good as a smart high school student. I would say that now they're as good as a smart college student, and sort of reaching past that." "I really worry, particularly at the entry level, that the AI models are very much at the center of what an entry level human worker would do." "What is striking to me about this AI boom is that it's bigger and it's broader and it's moving faster than anything has before." "People will adapt, but they may not adapt fast enough. And so there may be an adjustment period." The tell: this is not a critic outside the industry. It is the man building the models saying the quiet part on camera -- because he thinks the people whose jobs are on the line adapt slower than the models improve. High school to college in two years was the warm-up. The entry level is where it lands first.

Karl Mehta

340,883 views • 24 days ago

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”

The All-In Podcast

57,581 views • 4 months ago

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.

Dustin

121,240 views • 14 days ago