Yann LeCun, Executive Chairman of AMI Labs, explains why LLMs are mostly retrieving human knowledge rather than thinking for themselves: LeCun starts with why so many people misread what these systems are doing: "I think there's a lot of confusion, really, because we tend to anthropomorphize systems that can reproduce certain human functions." When an AI writes fluent answers, we assume there's a mind behind them. LeCun's view is that most of what we're seeing is something more familiar: "LLMs, to some extent, except for a few domains, are mostly information retrieval systems. They can compress a lot of factual knowledge that has been previously produced by humans and can give easy access to it." The key words are "previously produced by humans." The knowledge in an LLM came from people. What the system adds is compression and easy access. That puts LLMs in a long historical line: "In a way, it's kind of a natural evolution of the printing press, the libraries, the Internet, and search engines. Right. It's just a more efficient way to access information." @ylecun is clear about their value: "LLMs are incredibly useful, there's no question about that. And they do amplify human intelligence, like computer technology going back to the 1940s." He also allows that in a few areas, such as generating code and some types of mathematics, the capabilities seem to go beyond retrieval. But he notes what those areas share: "It's still, to a large extent, domains where reasoning has to do with manipulating symbols." That's where the retrieval framing shows its limits. If these systems were truly thinking for themselves, you'd expect that ability to carry over into the physical world. It hasn't: "The problem is that why do we have systems that can pass the bar exam and win mathematics Olympiads, but we don't have domestic robots, we don't even have self driving cars." Then comes his sharpest comparison: "And we certainly do not have self driving cars that can teach themselves to drive in 20 hours of practice like any 17 year old. So we're missing something big still."

Dario Amodei is at the desk to assure that the future of humanity is safe from AI

Harvard cognitive scientist Steven Pinker (@sapinker) on AI's future path. "It will get better. It'll never be omniscient. It'll never be omnipotent. That's out of comic books out of religion. There are laws of physics. There are limits on information. There's no system that could learn the position and velocity of every particle in the universe. So as long as that is true, there's not going to be an AI system that can do anything or can know everything."

The claude folks should just own this 🤣

They’re building a pawn-shop economy: Where future purchasing power may come from what you can sell - or borrow against - in a permissioned market. Which assets will they still let you turn into cash? That’s liquidity now.

I'm back.

Minimum wage in 1963 in the US was $1.25 That was 5 silver quarters. Today the melt value of those 5 silver quarters is $57.90. Instead, US Federal minimum wage is $7.25 That's the whole ruse...that's the whole game. @wbmosler

Correct all whilst Warsh makes cost of borrowing higher. @themarketsniper @MakeGoldGreat

The AI fight IS the gun fight: “It’s too fast, too cheap, a criminal will get one — halt it, license it, BAN the “super” versions…” The truth: We didn’t ban the gun. We knew if good people refuse the tool, evil people will not. Now? We have the ultimate checkmate. Even AI “knows” it.

Oh sh!t... @andreijikh just went down the rabbit hole. Except it isn't 2028...🤫

4D-Chess

I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle. It starts with METR. Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models. He proposes METR for this purpose. But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock. Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio. And GVF is the overwhelming funder of the entire Anthropic Network ecosystem. This stock was worth $500 million early last year. It is worth more than $7.7 billion just ~16 months later. METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth. Because if Anthropic goes under, many of the organizations that fund METR go under as well. But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much. The "third-party evaluator" is not "third-party" at all. The evaluator is on Anthropic's payroll. If this were the end of it, that's bad. But that isn't all. The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom. The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others. They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's. All of these organizations are financially dependent on the same exploding $7 billion money pile. As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder. Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created. From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts. This itself is an objective fact. The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it. But the problem also goes in the other direction: If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die. Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen. Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly. They simply are not organizations independent of Anthropic. And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly. What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations. The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture. And that feedback loop is winning. That's what Jacob Coxon is. China is keeping messaging tight. That is why optimism for AI is so high in China. America has Anthropic: a massive company pushing anti-AI propaganda at a state level. Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences. Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully. It is the mirror of the same AI virus that it hypothesizes to consume America. Anthropic's business model, models itself after the very thing it claims to fear. Except Anthropic's ideology infects humans, not computers. Congress must investigate. Evidence and Github in next post. Then some supplementary figures.

Yes

The Ancients Knew Something We Don’t! It seems we’re the primitive ones😉 The Ancients all had advanced technology, We still do not know how they built these Megaliths also many otherw have been found across the planet. The didn't have digital computers nor printers either. Maybe they did, everyone can only speculate. youtube.com/@TheWhyFiles/vid…