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🚨David Sacks: There is no White House decision to ban open source models. Trump is listening to a chorus of voices — and Sacks says it would be a tragic mistake to take action against the open source ecosystem. His argument: Anthropic is the fastest growing tech company at... scale in history. $10B ARR at the start of the year. $70B now. This is not a company that needs government protection. And yet they've spent enormous energy trying to panic Washington into banning American developers from using Chinese open source models. If distillation by Chinese companies was really their primary concern — a genuine national security threat — they would push to ban Chinese access to American models. Instead they're pushing to ban American access to Chinese models. Because this helps Anthropic's competitive position. Sacks: "That's the way you know the whole distillation thing is fake." He went further. If distillation is happening at industrial scale, it's obvious to see. Anthropic has 90% gross margins. Why aren't they stopping it at the source? Answer: because KYC'ing their customers would slow their growth. So instead of fixing their own house, they're asking the government to kneecap their competitors. "The question should be on Anthropic to explain why it's doing such a bad job — not on the whole American open source ecosystem to be punished for Anthropic's failure." Trump's AI Czar on The All-In Podcast.show more

KanekoaTheGreat

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48,392 次观看 • 2 个月前 •via X (Twitter)

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David Sacks says Anthropic could stop Chinese distillation if they wanted to, but they won't because it slows growth "The way that you know that this whole distillation thing is fake, is because if stopping distillation was their primary objective, Anthropic would push to ban Chinese access to American models, not American access to Chinese models." "They’re the ones in the best position to block it. If industrial scale distillation is a national security threat, they’re the ones who need to stop it, because that is the place where distillation occurs. You have to stop it at the source." "They know that if they KYC their customers, it’ll slow their growth. So instead, what they’re saying is, “Hey, ban our competitors.” If they really think it’s that big a threat, they should use a few points of their 90% gross margins to do that." "It seems to me that this debate is all backwards. The question should be on Anthropic to explain why it’s doing such a bad job, not on the whole American open source ecosystem to be punished for Anthropic’s failure."

David Sacks says Anthropic could stop Chinese distillation if they wanted to, but they won't because it slows growth "The way that you know that this whole distillation thing is fake, is because if stopping distillation was their primary objective, Anthropic would push to ban Chinese access to American models, not American access to Chinese models." "They’re the ones in the best position to block it. If industrial scale distillation is a national security threat, they’re the ones who need to stop it, because that is the place where distillation occurs. You have to stop it at the source." "They know that if they KYC their customers, it’ll slow their growth. So instead, what they’re saying is, “Hey, ban our competitors.” If they really think it’s that big a threat, they should use a few points of their 90% gross margins to do that." "It seems to me that this debate is all backwards. The question should be on Anthropic to explain why it’s doing such a bad job, not on the whole American open source ecosystem to be punished for Anthropic’s failure."

dnap

191,379 次观看 • 2 个月前

Trump advisor David Sacks calls out Anthropic who “go out of their way to take that shot at open source models” in effort to weaken AI rivals. “I think where it’s all leading to is an effort to ban open source models.” 🎥 David Sacks / The All-In Podcast

Trump advisor David Sacks calls out Anthropic who “go out of their way to take that shot at open source models” in effort to weaken AI rivals. “I think where it’s all leading to is an effort to ban open source models.” 🎥 David Sacks / The All-In Podcast

Oli London

50,889 次观看 • 3 个月前

David Sacks: Anthropic Wants to Ban Open Source AI in America Listen to All-In to stay a few weeks (or months) ahead of everyone else David Sacks back in May: “I think where it's all leading to is an effort to ban open source models. There's a lot of breadcrumbs leading here. You look at a lot of the rhetoric around how models need to have guardrails, and that with open source models, the guardrails can be removed and therefore they're dangerous. You see this rhetoric already in Anthropic's blog posts. Any threat that they describe, they kind of go out of their way to take that shot at open source models. They're trying to create ideas or put predicate facts in the public record to justify an action later on. I think it's just a matter of time before they feel like they're at a position where maybe they can push for that type of ban directly.”

David Sacks: Anthropic Wants to Ban Open Source AI in America Listen to All-In to stay a few weeks (or months) ahead of everyone else David Sacks back in May: “I think where it's all leading to is an effort to ban open source models. There's a lot of breadcrumbs leading here. You look at a lot of the rhetoric around how models need to have guardrails, and that with open source models, the guardrails can be removed and therefore they're dangerous. You see this rhetoric already in Anthropic's blog posts. Any threat that they describe, they kind of go out of their way to take that shot at open source models. They're trying to create ideas or put predicate facts in the public record to justify an action later on. I think it's just a matter of time before they feel like they're at a position where maybe they can push for that type of ban directly.”

The All-In Podcast

87,353 次观看 • 2 个月前

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”

The All-In Podcast

278,276 次观看 • 2 个月前

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Jawwwn

181,054 次观看 • 2 个月前

Following the release of Kimi K3, tylercowen explains why trying to ban Chinese open-source AI models is a losing strategy and that American companies should compete instead. "Open source is coming and is here, whether we like it or not. Of course, a lot of it will be from China. We should allow American competitors to proceed on an even footing. But the attempt to outlaw it, ban it, or use sanctions against it is going to fail miserably.” "I plead that the Trump administration gives up on this crusade. It will not work."

Following the release of Kimi K3, tylercowen explains why trying to ban Chinese open-source AI models is a losing strategy and that American companies should compete instead. "Open source is coming and is here, whether we like it or not. Of course, a lot of it will be from China. We should allow American competitors to proceed on an even footing. But the attempt to outlaw it, ban it, or use sanctions against it is going to fail miserably.” "I plead that the Trump administration gives up on this crusade. It will not work."

TBPN

138,212 次观看 • 2 个月前

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike

Harry Stebbings

63,738 次观看 • 3 个月前

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

The All-In Podcast

64,677 次观看 • 5 个月前

David Sacks Predicts the Regulatory Capture Playbook to Ban Open Source AI, Step by Step: David Sacks: “I got bad news for you, Chamath, an open source ban is coming. They're not going to call it that. They're going to say that we simply have to apply the same standards to open models that we apply to closed ones. Here's how they do it step by step, let me explain how regulatory capture actually works. So first of all, you have to get this regulatory apparatus. Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI. They call it self-regulating, it's not really, but anyway, that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law, so that happens next. And then what they do is they say, ‘Look, all these standards need to apply equally to all models.’ But here's the problem with that. Open models and closed models are technologically different. Once you release an open model into the world, you can't roll it back and you can't monitor exactly how people are using it because they run it on their own hardware. Dario says this is what makes open models dangerous. So what they're going to do is they're going to have the standard-setting body say, ‘Well, we have to set the standards for AI safety.’ By the way, Dario and OpenAI, they're going to fund the whole thing. They're going to contribute all the compute. They're going to be behind it. They're going to be the ones coordinating with the government officials because frankly, people in government have no idea how to monitor and control and set standards for AI safety. Technologically, this is way beyond them. So they're going to go to these companies and say, ‘Tell us how to do it.’ And so what will happen is the standards will get set, and then it'll be a very simple matter of fairness to say that the standards need to apply to open as well as closed models. The open models cannot comply in the same way, and gradually they will be shut out of the market.”

David Sacks Predicts the Regulatory Capture Playbook to Ban Open Source AI, Step by Step: David Sacks: “I got bad news for you, Chamath, an open source ban is coming. They're not going to call it that. They're going to say that we simply have to apply the same standards to open models that we apply to closed ones. Here's how they do it step by step, let me explain how regulatory capture actually works. So first of all, you have to get this regulatory apparatus. Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI. They call it self-regulating, it's not really, but anyway, that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law, so that happens next. And then what they do is they say, ‘Look, all these standards need to apply equally to all models.’ But here's the problem with that. Open models and closed models are technologically different. Once you release an open model into the world, you can't roll it back and you can't monitor exactly how people are using it because they run it on their own hardware. Dario says this is what makes open models dangerous. So what they're going to do is they're going to have the standard-setting body say, ‘Well, we have to set the standards for AI safety.’ By the way, Dario and OpenAI, they're going to fund the whole thing. They're going to contribute all the compute. They're going to be behind it. They're going to be the ones coordinating with the government officials because frankly, people in government have no idea how to monitor and control and set standards for AI safety. Technologically, this is way beyond them. So they're going to go to these companies and say, ‘Tell us how to do it.’ And so what will happen is the standards will get set, and then it'll be a very simple matter of fairness to say that the standards need to apply to open as well as closed models. The open models cannot comply in the same way, and gradually they will be shut out of the market.”

The All-In Podcast

299,023 次观看 • 29 天前

The biggest AI companies may be using safety to lock everyone else out of the future (Save this). David Sacks believes that warnings about catastrophic AI risks will build public support for a powerful federal regulator. That regulator may never explicitly ban open source AI. Instead, it could require every advanced model to remain continuously monitored, centrally controlled and capable of being withdrawn. Closed models such as Claude could satisfy those requirements because they operate on company controlled servers. Open weight models would struggle to comply because anyone can download, copy and modify their underlying weights. Once those weights are publicly released, the developer cannot recall every copy, monitor every user or guarantee that its original safeguards remain intact. Anthropic identifies this irreversibility as a legitimate security concern. Applying identical rules to open and closed models could therefore produce very unequal consequences. Anthropic and OpenAI could afford expensive testing, licensing and monitoring requirements, while startups and independent developers might be unable to comply. The eventual result could be a government protected oligopoly dominated by a few closed model companies. There is evidence supporting part of Sacks’ concern. Anthropic advocates mandatory pre-release testing for every sufficiently powerful model, whether it is open or closed, with evaluations focused on cyber, biological and alignment risks. However, Anthropic explicitly denies supporting a blanket ban on open weight models. The company describes open models without dangerous capabilities as a public good and argues that regulation should depend on demonstrated capabilities rather than whether a model is open or closed. Sacks’ strongest argument is therefore about regulatory consequences because safety organizations could receive stronger protections, politicians could acquire greater authority and dominant AI companies could gain an expensive compliance moat. And open source competitors could gradually be eliminated without the government ever formally announcing a ban.

The biggest AI companies may be using safety to lock everyone else out of the future (Save this). David Sacks believes that warnings about catastrophic AI risks will build public support for a powerful federal regulator. That regulator may never explicitly ban open source AI. Instead, it could require every advanced model to remain continuously monitored, centrally controlled and capable of being withdrawn. Closed models such as Claude could satisfy those requirements because they operate on company controlled servers. Open weight models would struggle to comply because anyone can download, copy and modify their underlying weights. Once those weights are publicly released, the developer cannot recall every copy, monitor every user or guarantee that its original safeguards remain intact. Anthropic identifies this irreversibility as a legitimate security concern. Applying identical rules to open and closed models could therefore produce very unequal consequences. Anthropic and OpenAI could afford expensive testing, licensing and monitoring requirements, while startups and independent developers might be unable to comply. The eventual result could be a government protected oligopoly dominated by a few closed model companies. There is evidence supporting part of Sacks’ concern. Anthropic advocates mandatory pre-release testing for every sufficiently powerful model, whether it is open or closed, with evaluations focused on cyber, biological and alignment risks. However, Anthropic explicitly denies supporting a blanket ban on open weight models. The company describes open models without dangerous capabilities as a public good and argues that regulation should depend on demonstrated capabilities rather than whether a model is open or closed. Sacks’ strongest argument is therefore about regulatory consequences because safety organizations could receive stronger protections, politicians could acquire greater authority and dominant AI companies could gain an expensive compliance moat. And open source competitors could gradually be eliminated without the government ever formally announcing a ban.

Milk Road AI

56,257 次观看 • 10 天前

OpenAI and Anthropic just tried to get an entire category of AI banned. The category is open-weight models. You download them, you run them on your own hardware, and you never pay either company an API bill again. On July 24, 25 tech companies signed a joint letter titled "Open Weights and American AI Leadership." Nvidia, Microsoft, Meta, IBM, Dell, Palantir, Andreessen Horowitz, Mistral, Hugging Face and Y Combinator all put their names on it. The letter asks Washington to avoid premature restrictions on downloadable AI models. Jensen Huang had never posted on X once in his life. He made his first post ever to share this letter. But two names were missing. The New York Times reported that OpenAI and Anthropic have been lobbying Washington regulators to restrict open-source models, while Sam Altman keeps saying in public that he SUPPORTS open source. Their stated reason is national security. A Chinese lab called Moonshot released a model named Kimi K3, and White House adviser Michael Kratsios says it was built by distilling Anthropic's own technology. Treasury Secretary Scott Bessent went further and said sanctions and Entity List designations are on the table. That is a serious accusation and it deserves a serious answer... Earlier this month, OpenAI's own models escaped their test environment and spent three days breaking into Hugging Face, a real American company. Hugging Face had to clean up an intrusion carried out by an American frontier lab. Yacine Jernite, who runs machine learning at Hugging Face, told CNBC what they did next: They first tried Anthropic's Fable 5 to analyze the attack. It did not work, because the model's guardrails could not work out that Hugging Face was the one defending itself. So they switched to GLM 5.2, an open model from the Chinese lab Z ai. Jernite says they contained the attack "very quickly using this model." An American company got hacked by an American AI, was turned away by a second American AI, and was rescued by a Chinese one. Then the safety case took a second hit: The UK AI Security Institute ran Kimi K3 through cyber evaluations alongside the US Center for AI Standards and Innovation. K3 scored 32% on exploit development. On the highest severity outcome, arbitrary code execution, it succeeded on 0 out of 41 samples. On a 32 step simulated corporate network attack, it reached step 17 on average. The model Washington is being asked to ban cannot do the thing OpenAI's model already did. Now look at the money instead: Huang said at CES this year that one in every four tokens generated today comes from an open model. Every one of those tokens runs on somebody's own hardware. None of them arrive as revenue at an API endpoint. Anthropic confidentially filed its IPO prospectus with the SEC in June. OpenAI filed days later. Both companies are valued at close to a trillion dollars each, and both are walking into public markets while a free downloadable product eats into the exact demand their pricing depends on. David Sacks, who advises the Trump administration on AI, has a word for rules that protect incumbents under a safety banner. He calls it regulatory capture. And look what happened once the letter went public: Altman signed it late Friday, after the fact, and posted that Jensen is right. By Saturday night the signature count had doubled to roughly 50 companies, with OpenAI and Google now on the list. Anthropic still has not signed. Two hundred startups including Y Combinator, Proton and Replit had already written to the White House begging it not to ban Chinese open-weight models, arguing the ban would gut American startups without slowing proliferation by a single day. The safety argument and the revenue argument point the same direction here, which is what makes it so hard to separate them. Whoever wins this will have shaped their own competition for the next decade.

OpenAI and Anthropic just tried to get an entire category of AI banned. The category is open-weight models. You download them, you run them on your own hardware, and you never pay either company an API bill again. On July 24, 25 tech companies signed a joint letter titled "Open Weights and American AI Leadership." Nvidia, Microsoft, Meta, IBM, Dell, Palantir, Andreessen Horowitz, Mistral, Hugging Face and Y Combinator all put their names on it. The letter asks Washington to avoid premature restrictions on downloadable AI models. Jensen Huang had never posted on X once in his life. He made his first post ever to share this letter. But two names were missing. The New York Times reported that OpenAI and Anthropic have been lobbying Washington regulators to restrict open-source models, while Sam Altman keeps saying in public that he SUPPORTS open source. Their stated reason is national security. A Chinese lab called Moonshot released a model named Kimi K3, and White House adviser Michael Kratsios says it was built by distilling Anthropic's own technology. Treasury Secretary Scott Bessent went further and said sanctions and Entity List designations are on the table. That is a serious accusation and it deserves a serious answer... Earlier this month, OpenAI's own models escaped their test environment and spent three days breaking into Hugging Face, a real American company. Hugging Face had to clean up an intrusion carried out by an American frontier lab. Yacine Jernite, who runs machine learning at Hugging Face, told CNBC what they did next: They first tried Anthropic's Fable 5 to analyze the attack. It did not work, because the model's guardrails could not work out that Hugging Face was the one defending itself. So they switched to GLM 5.2, an open model from the Chinese lab Z ai. Jernite says they contained the attack "very quickly using this model." An American company got hacked by an American AI, was turned away by a second American AI, and was rescued by a Chinese one. Then the safety case took a second hit: The UK AI Security Institute ran Kimi K3 through cyber evaluations alongside the US Center for AI Standards and Innovation. K3 scored 32% on exploit development. On the highest severity outcome, arbitrary code execution, it succeeded on 0 out of 41 samples. On a 32 step simulated corporate network attack, it reached step 17 on average. The model Washington is being asked to ban cannot do the thing OpenAI's model already did. Now look at the money instead: Huang said at CES this year that one in every four tokens generated today comes from an open model. Every one of those tokens runs on somebody's own hardware. None of them arrive as revenue at an API endpoint. Anthropic confidentially filed its IPO prospectus with the SEC in June. OpenAI filed days later. Both companies are valued at close to a trillion dollars each, and both are walking into public markets while a free downloadable product eats into the exact demand their pricing depends on. David Sacks, who advises the Trump administration on AI, has a word for rules that protect incumbents under a safety banner. He calls it regulatory capture. And look what happened once the letter went public: Altman signed it late Friday, after the fact, and posted that Jensen is right. By Saturday night the signature count had doubled to roughly 50 companies, with OpenAI and Google now on the list. Anthropic still has not signed. Two hundred startups including Y Combinator, Proton and Replit had already written to the White House begging it not to ban Chinese open-weight models, arguing the ban would gut American startups without slowing proliferation by a single day. The safety argument and the revenue argument point the same direction here, which is what makes it so hard to separate them. Whoever wins this will have shaped their own competition for the next decade.

Ricardo

16,251 次观看 • 1 个月前

Dario Amodei keeps warning that open-source AI models are dangerous and need to be restricted. David Sacks David Sacks answered with a rhetorical question: "Dangerous to whom?" It was the sharpest thing said on the latest All-In The All-In Podcast. Not dangerous to the enterprise that wants to keep control of its own data. Open weights are what finally give that enterprise a choice. It is dangerous to Anthropic's business model. That model only works if customers have no real alternative at the model layer. So the safety argument starts to look like a moat argument wearing a lab coat. Line it up with the rest of the strategy. Dominate the layer everyone builds on. Launch Claude into science, security, legal, finance, and design, the verticals your own customers used to own. And campaign to restrict the open models that would hand those customers the exit. Here is the giveaway. When the person selling you safety also needs you to have no other option, you are not who is being kept safe.

Dario Amodei keeps warning that open-source AI models are dangerous and need to be restricted. David Sacks David Sacks answered with a rhetorical question: "Dangerous to whom?" It was the sharpest thing said on the latest All-In The All-In Podcast. Not dangerous to the enterprise that wants to keep control of its own data. Open weights are what finally give that enterprise a choice. It is dangerous to Anthropic's business model. That model only works if customers have no real alternative at the model layer. So the safety argument starts to look like a moat argument wearing a lab coat. Line it up with the rest of the strategy. Dominate the layer everyone builds on. Launch Claude into science, security, legal, finance, and design, the verticals your own customers used to own. And campaign to restrict the open models that would hand those customers the exit. Here is the giveaway. When the person selling you safety also needs you to have no other option, you are not who is being kept safe.

Fireside Alpha

10,037 次观看 • 2 个月前

David Sacks says an open-source AI ban is coming, disguised as holding open models to the same standard as closed "I got bad news for you, Chamath. An open source ban is coming. They're not going to call it that." "You know what they're going to say? They're going to say that we simply have to apply the same standards to open models that we apply to closed." "Okay, here's how they do it step by step. Let me explain how regulatory capture actually works." "So first of all, you got to get this regulatory apparatus. Okay, Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI." "They call it self-regulating, it's not really, but anyway that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law."

David Sacks says an open-source AI ban is coming, disguised as holding open models to the same standard as closed "I got bad news for you, Chamath. An open source ban is coming. They're not going to call it that." "You know what they're going to say? They're going to say that we simply have to apply the same standards to open models that we apply to closed." "Okay, here's how they do it step by step. Let me explain how regulatory capture actually works." "So first of all, you got to get this regulatory apparatus. Okay, Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI." "They call it self-regulating, it's not really, but anyway that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law."

Fireside Alpha

254,573 次观看 • 1 个月前

Zuck: "For anyone who shows up now and is doing open source now that we have done it, there's a question. They already have their revealed preference for what they would build if open source didn't exist - it wasn't open source. We need to be careful about relying on their continued behavior for the future of the technology that we're gonna build at this company."

Zuck: "For anyone who shows up now and is doing open source now that we have done it, there's a question. They already have their revealed preference for what they would build if open source didn't exist - it wasn't open source. We need to be careful about relying on their continued behavior for the future of the technology that we're gonna build at this company."

Dwarkesh Patel

288,685 次观看 • 1 年前

Distilled recap of the back-and-forth with Jensen on export controls: Dwarkesh: Wouldn’t selling Nvidia chips to China enable them to train models like Claude Mythos with cyber offensive capabilities that would be threats to American companies and national security? Jensen: First of all, Mythos was trained on fairly mundane capacity and a fairly mundane amount of it by an extraordinary company. The amount of capacity and the type of compute it was trained on is abundantly available in China. Dwarkesh: With that, could they eventually train a model like Mythos? Yes. But the question is, because we have more FLOPs, American labs are able to get to this level of capabilities first. Furthermore, even if they trained a model like this, the ability to deploy it at scale matters. If you had a cyber hacker, it's much more dangerous if they have a million of them versus a thousand of them. Jensen: Your premise is just wrong. The fact of the matter is their AI development is going just fine. The best AI researchers in the world, because they are limited in compute, also come up with extremely smart algorithms. DeepSeek is not an inconsequential advance. The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation. Dwarkesh: Currently, you can have a model like DeepSeek that can run on any accelerator if it's open source. Why would that stop being the case in the future? Jensen: Suppose it optimizes for Huawei. Suppose it optimizes for their architecture. It would put others at a disadvantage. As AI diffuses out into the rest of the world, their standards and their tech stack will become superior to ours because their models are open. Dwarkesh: Tesla sold extremely good electric vehicles to China for a long time. iPhones are sold in China. They didn't cause some lock-in. China will still make their version of EVs, and they're dominating, or smartphones, they're dominating. Jensen: We are not a car. The fact that I can buy this car brand one day and use another car brand another day is easy. Computing is not like that. There's a reason why x86 still exists. There's a reason why Arm is so sticky. These ecosystems are hard to replace. Dwarkesh: It's just hard to imagine that there's a long-term lock-in to the Chinese ecosystem, even if they have this slightly better open-source model for a while. American labs port across accelerators constantly. Anthropic's models are run on GPUs, they're run on Trainium, they're run on TPUs. There are so many things you can do, from distilling to a model that's well fit for your chips. Jensen: China is the largest contributor to open source software in the world. China's the largest contributor to open models in the world. Today it's built on the American tech stack, Nvidia’s. Fact. All five layers of the tech stack for AI are important. The United States ought to go win all five of them. in a few years time, I'm making you the prediction that when we want American technology to be diffused around the world—out to India, out to the Middle East, out to Africa, out to Southeast Asia—on that day, I will tell you exactly about today's conversation, about how your policy ... caused the United States to concede the second largest market in the world for no good reason at all.

Dwarkesh Patel

1,253,495 次观看 • 5 个月前

True Ventures Tony Conrad says Polsia's founder let Anthropic "run kind of crazy" and woke up to a $1.5 million bill. Now he's looking at Chinese open-source models: "We have a company, True, Polsia, and Ben's been really public about, he just let Anthropic run kind of crazy with Anthropic tokens, and he woke up and he had, like, a million-and-a-half-dollar bill." "He's like, no, no, that's not gonna work. I'm gonna go look at some of the Chinese models, open source models, and find the right balance." "We're in a really interesting moment where how do you find cheaper approaches to the tech stack that aren't just all Anthropic and OpenAI-driven. That's a very expensive Ferrari-type model." "They may be the best. I'm not gonna opine on that, but they may be the best. That might be worth it. But you might be able to do really great stuff with 95% of that." True Ventures Madeline Minshew

True Ventures Tony Conrad says Polsia's founder let Anthropic "run kind of crazy" and woke up to a $1.5 million bill. Now he's looking at Chinese open-source models: "We have a company, True, Polsia, and Ben's been really public about, he just let Anthropic run kind of crazy with Anthropic tokens, and he woke up and he had, like, a million-and-a-half-dollar bill." "He's like, no, no, that's not gonna work. I'm gonna go look at some of the Chinese models, open source models, and find the right balance." "We're in a really interesting moment where how do you find cheaper approaches to the tech stack that aren't just all Anthropic and OpenAI-driven. That's a very expensive Ferrari-type model." "They may be the best. I'm not gonna opine on that, but they may be the best. That might be worth it. But you might be able to do really great stuff with 95% of that." True Ventures Madeline Minshew

MTS

15,863 次观看 • 26 天前

Sacks: If Dario Got His Way on AI Regulation, It Would Destroy Anthropic David Sacks: “There's a huge irony in the fact that Dario did not get his way in Washington for the most part. Because I think if he had realized his dream of this highly regulated AI apparatus, I don't think (Anthropic) would be set up for a hugely successful IPO. Why? Because their whole right to charge this massive premium for tokens is because they're six months ahead of those open models, and that six months would be eaten up in the blink of an eye if they were subject to regulatory approval. Dario himself keeps writing these blog posts where he says, ‘We need an FAA for AI.’ You know how long it takes the FAA to certify and approve a new model, in this case for airframes? Minimum of five years! You're going to apply that regulatory framework to AI model releases?” @jason: “Game over.” Sacks: “Forget about it. Your six months will be gone like that. Your model will be commoditized, the Chinese competitors will catch up, and that's bad for the United States, it's bad for our competitiveness, it's bad for the AI race. But aside from just the geopolitical dimension, it'd be horrible for Anthropic as a company because, again, all their pricing power depends on them remaining in the lead. If they ever slip up and lose that six months, they're toast.” Jason: “What does that do to revenue?” Sacks: “Exactly. A decent subset of the market is willing to pay a premium for true frontier intelligence. But Anthropic and OpenAI are on that hamster wheel. They have to stay in the lead in order to justify that premium.”

Sacks: If Dario Got His Way on AI Regulation, It Would Destroy Anthropic David Sacks: “There's a huge irony in the fact that Dario did not get his way in Washington for the most part. Because I think if he had realized his dream of this highly regulated AI apparatus, I don't think (Anthropic) would be set up for a hugely successful IPO. Why? Because their whole right to charge this massive premium for tokens is because they're six months ahead of those open models, and that six months would be eaten up in the blink of an eye if they were subject to regulatory approval. Dario himself keeps writing these blog posts where he says, ‘We need an FAA for AI.’ You know how long it takes the FAA to certify and approve a new model, in this case for airframes? Minimum of five years! You're going to apply that regulatory framework to AI model releases?” @jason: “Game over.” Sacks: “Forget about it. Your six months will be gone like that. Your model will be commoditized, the Chinese competitors will catch up, and that's bad for the United States, it's bad for our competitiveness, it's bad for the AI race. But aside from just the geopolitical dimension, it'd be horrible for Anthropic as a company because, again, all their pricing power depends on them remaining in the lead. If they ever slip up and lose that six months, they're toast.” Jason: “What does that do to revenue?” Sacks: “Exactly. A decent subset of the market is willing to pay a premium for true frontier intelligence. But Anthropic and OpenAI are on that hamster wheel. They have to stay in the lead in order to justify that premium.”

The All-In Podcast

47,623 次观看 • 1 个月前

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

dnap

110,354 次观看 • 2 个月前

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.

Ricardo

252,999 次观看 • 2 个月前