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J-Cal: Nvidia is taking the gloves off with its open source model. They will own the whole stack. “You will not be able to tell the difference between Jensen Huang's open source LLM and Claude for 95% of your searches, I guarantee you. Now, why has Nvidia and Jensen... downplayed their open source model until this moment? Why would he do that? Why would he never bring it up in the All-In interview, never bring it up? Because his top customers (OpenAI, Anthropic, etc.) were very concerned, from what I understand, about the fact that Nvidia had made so much progress on their open source model. But suddenly, after OpenAI announced their Jalapeno chips, after Anthropic started making chips, after AMD did successful projects with both of these companies, after Elon said he's going to do his own fab, Nvidia's taking the gloves off. They are going to own the whole stack. You get the hardware from them, and you're going to get a model that's competitive with OpenAI's for free.”show more

The All-In Podcast

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227,561 просмотров • 1 месяц назад •via X (Twitter)

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Jcal says Sam Altman provoked Jensen into directly competing with OpenAI "I think Jensen is going all in on open source based on these two acquisitions, Hugging Face and Poolside. I think Sam Altman poked the tiger." "If you look at what he did, he had done that huge $100 billion deal with $NVDA back in 2025. Then he announced the $AMD deal. Jensen was clearly not pleased about that." "Right after, Sam said he's going to make his own inference, jalapeño, and that he was going to do the deal with $AMD, then Jensen came out was like, 'Well, by the way, we don't actually have to do these investments in OpenAI.'" "I think he's speed-running open source, and you're going to be able to buy your entire stack from $NVDA next year. He is going to own open source. That is a really interesting moment in time because we were sitting here 6, 12 months ago saying open source would never catch up." "Jensen is doing an open source self-driving project. Now he owns Hugging Face, the leading open source indexer where everybody goes to try the new models.”

Jcal says Sam Altman provoked Jensen into directly competing with OpenAI "I think Jensen is going all in on open source based on these two acquisitions, Hugging Face and Poolside. I think Sam Altman poked the tiger." "If you look at what he did, he had done that huge $100 billion deal with $NVDA back in 2025. Then he announced the $AMD deal. Jensen was clearly not pleased about that." "Right after, Sam said he's going to make his own inference, jalapeño, and that he was going to do the deal with $AMD, then Jensen came out was like, 'Well, by the way, we don't actually have to do these investments in OpenAI.'" "I think he's speed-running open source, and you're going to be able to buy your entire stack from $NVDA next year. He is going to own open source. That is a really interesting moment in time because we were sitting here 6, 12 months ago saying open source would never catch up." "Jensen is doing an open source self-driving project. Now he owns Hugging Face, the leading open source indexer where everybody goes to try the new models.”

dnap

231,049 просмотров • 5 дней назад

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

278,185 просмотров • 1 месяц назад

Gavin Baker says the future for the world's biggest companies is open models and private context: "I think the future is an ensemble of models. There's a Pareto curve. No one model is going to be the best at everything." "For the global 1,000 biggest companies, you're going to take whatever the best open-source model is. I think probably in the very near future, that's going to be an Nvidia model." "Everybody says 'Well, in a world where open-source wins, who funds the training?' Chip companies can fund the training." "It's trivial to do a $50 to $100 billion training run for Jensen, but I do think you're going to see American open-source led by Nvidia get really close to the frontier." "Sharing your own enterprise context, that's truly your IP, that's truly the value of your company, the context embedded in all of your data, sharing that with a frontier lab may be hazardous for your financial health." "I think what you'll see these companies do is they'll have their own model on their data, and it will work with one or two other frontier models, checking each other... I think that feels like a very likely future to me." Gavin Baker David George

Gavin Baker says the future for the world's biggest companies is open models and private context: "I think the future is an ensemble of models. There's a Pareto curve. No one model is going to be the best at everything." "For the global 1,000 biggest companies, you're going to take whatever the best open-source model is. I think probably in the very near future, that's going to be an Nvidia model." "Everybody says 'Well, in a world where open-source wins, who funds the training?' Chip companies can fund the training." "It's trivial to do a $50 to $100 billion training run for Jensen, but I do think you're going to see American open-source led by Nvidia get really close to the frontier." "Sharing your own enterprise context, that's truly your IP, that's truly the value of your company, the context embedded in all of your data, sharing that with a frontier lab may be hazardous for your financial health." "I think what you'll see these companies do is they'll have their own model on their data, and it will work with one or two other frontier models, checking each other... I think that feels like a very likely future to me." Gavin Baker David George

a16z

38,362 просмотров • 2 дней назад

🚨🇨🇳🇺🇸 TRUMP: CHINA IS GOING TO TALK WITH NVIDIA ABOUT U.S. CHIP DEALS “We did discuss chips, and he’s going to be talking to Nvidia and others about taking chips. Look, we make great chips and Nvidia’s the leader, and I’ll be speaking to Jensen from Nvidia, but they’re going to be discussing that with Nvidia to see whether or not they can do it. I said, that’s really between you and Nvidia.” Source: The White House

🚨🇨🇳🇺🇸 TRUMP: CHINA IS GOING TO TALK WITH NVIDIA ABOUT U.S. CHIP DEALS “We did discuss chips, and he’s going to be talking to Nvidia and others about taking chips. Look, we make great chips and Nvidia’s the leader, and I’ll be speaking to Jensen from Nvidia, but they’re going to be discussing that with Nvidia to see whether or not they can do it. I said, that’s really between you and Nvidia.” Source: The White House

Mario Nawfal

240,579 просмотров • 10 месяцев назад

Gavin Baker: "I think Anthropic is worth $3 trillion today - that's roughly where it would trade as a public company - but they're mistaken that open source is bad for AI - it just kills the labs' margin and hands it to the infrastructure" this is him explaining what he actually invests in - and why his last call on this show is up 14x His words: "OpenAI launched their own chip and basically said 'f you' to Jensen - don't be surprised if Nvidia starts an OpenAI competitor - you heard it here first" "Nvidia is the American open source champion - they can release GLM 5.2 or better whenever they want" "DRAM is probably going to be 30 to 40% of all hyperscaler capex next year. hundreds of billions of dollars going straight to DRAM - it's wild" "there's a whole segment on X focused on bottlenecks - I call them the bottleneck bros. they do some work with Claude, find some esoteric Japanese company" bookmark & watch today ↓

Gavin Baker: "I think Anthropic is worth $3 trillion today - that's roughly where it would trade as a public company - but they're mistaken that open source is bad for AI - it just kills the labs' margin and hands it to the infrastructure" this is him explaining what he actually invests in - and why his last call on this show is up 14x His words: "OpenAI launched their own chip and basically said 'f you' to Jensen - don't be surprised if Nvidia starts an OpenAI competitor - you heard it here first" "Nvidia is the American open source champion - they can release GLM 5.2 or better whenever they want" "DRAM is probably going to be 30 to 40% of all hyperscaler capex next year. hundreds of billions of dollars going straight to DRAM - it's wild" "there's a whole segment on X focused on bottlenecks - I call them the bottleneck bros. they do some work with Claude, find some esoteric Japanese company" bookmark & watch today ↓

bodila

105,712 просмотров • 1 месяц назад

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

64,611 просмотров • 4 месяцев назад

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Vikram M

12,078 просмотров • 1 месяц назад

ELON: OPENAI WAS MEANT TO BE NONPROFIT AND OPEN SOURCE He’s explaining the original intent and where it went off course. “I came up with the name OpenAI as an open source and nonprofit organization. I funded OpenAI for the first roughly fifty million dollars. It was intended to be a nonprofit, open source company. Now they’re trying to change that for their own financial benefit into a for profit company that is closed source.” Source: Astro Greek

ELON: OPENAI WAS MEANT TO BE NONPROFIT AND OPEN SOURCE He’s explaining the original intent and where it went off course. “I came up with the name OpenAI as an open source and nonprofit organization. I funded OpenAI for the first roughly fifty million dollars. It was intended to be a nonprofit, open source company. Now they’re trying to change that for their own financial benefit into a for profit company that is closed source.” Source: Astro Greek

Mario Nawfal

40,859 просмотров • 7 месяцев назад

Elon exposes OpenAI -- OpenAI execs betrayed the founding mission as soon as there was revenue and profits to be had -- If it started as a for-profit, Elon would own 50% Elon Musk: “There's a mountain of evidence that shows that OpenAI was created as an open source nonprofit.” “That's the exact description in the incorporation documents. They have completely violated that.” “And they tried to change the definition of OpenAI to mean open to everyone instead of open source, even though it always meant open source.” “ I came up with the name. That’s how I know.” “ I mean, essentially, since I came up with the idea for the company, named it, provided the A, B, and C rounds of funding, recruited the critical personnel, and told them everything I know, if that had been a commercial corporation, I'd probably own half the company.” “It was totally at my discretion. I could have done that.” “But I created it as an open source nonprofit for the world.” Chamath: “ Do you think the right thing to do is to take those models and just open source them today?” Elon: “ Yeah, I think that is what it was created to do, so it should.” “Try using any of the recent so-called OpenAI open source models, they don't work.” “They open sourced a broken, non-working version of their models as a fig leaf.” “I mean, do you know anyone who's running OpenAI's open source models? Jason: “No.” Elon: “Exactly.”

Elon exposes OpenAI -- OpenAI execs betrayed the founding mission as soon as there was revenue and profits to be had -- If it started as a for-profit, Elon would own 50% Elon Musk: “There's a mountain of evidence that shows that OpenAI was created as an open source nonprofit.” “That's the exact description in the incorporation documents. They have completely violated that.” “And they tried to change the definition of OpenAI to mean open to everyone instead of open source, even though it always meant open source.” “ I came up with the name. That’s how I know.” “ I mean, essentially, since I came up with the idea for the company, named it, provided the A, B, and C rounds of funding, recruited the critical personnel, and told them everything I know, if that had been a commercial corporation, I'd probably own half the company.” “It was totally at my discretion. I could have done that.” “But I created it as an open source nonprofit for the world.” Chamath: “ Do you think the right thing to do is to take those models and just open source them today?” Elon: “ Yeah, I think that is what it was created to do, so it should.” “Try using any of the recent so-called OpenAI open source models, they don't work.” “They open sourced a broken, non-working version of their models as a fig leaf.” “I mean, do you know anyone who's running OpenAI's open source models? Jason: “No.” Elon: “Exactly.”

The All-In Podcast

387,223 просмотров • 10 месяцев назад

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,565 просмотров • 5 месяцев назад

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.

Milk Road AI

34,385 просмотров • 2 месяцев назад

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.

Harper Carroll

30,392 просмотров • 1 месяц назад

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

15,498 просмотров • 6 дней назад

NVIDIA just released a new open source transcription model, Nemotron Speech ASR, designed from the ground up for low-latency use cases like voice agents. Here's a voice agent built with this new model. 24ms transcription finalization and total voice-to-voice inference time under 500ms. This agent actually uses *three* NVIDIA open source models: - Nemotron Speech ASR - Nemotron 3 Nano 30GB in a 4-bit quant (released in December) - A preview checkpoint of the upcoming Magpie text-to-speech model These models are all truly open source: weights, training data, training code, and inference code. This is a big deal! Jensen said in the CES keynote yesterday that he expects open source models to catch up to proprietary models this year in a number of categories. NVIDIA is putting their weight behind making this happen. (As Alan Kay said, the best way to predict the future is to invent it.) The code for this agent is open source too, of course. You can deploy it to production with Modal and Pipecat AI cloud, or run locally on an NVIDIA DGX Spark or RTX 5090.

NVIDIA just released a new open source transcription model, Nemotron Speech ASR, designed from the ground up for low-latency use cases like voice agents. Here's a voice agent built with this new model. 24ms transcription finalization and total voice-to-voice inference time under 500ms. This agent actually uses three NVIDIA open source models: - Nemotron Speech ASR - Nemotron 3 Nano 30GB in a 4-bit quant (released in December) - A preview checkpoint of the upcoming Magpie text-to-speech model These models are all truly open source: weights, training data, training code, and inference code. This is a big deal! Jensen said in the CES keynote yesterday that he expects open source models to catch up to proprietary models this year in a number of categories. NVIDIA is putting their weight behind making this happen. (As Alan Kay said, the best way to predict the future is to invent it.) The code for this agent is open source too, of course. You can deploy it to production with Modal and Pipecat AI cloud, or run locally on an NVIDIA DGX Spark or RTX 5090.

kwindla

274,679 просмотров • 8 месяцев назад

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 просмотров • 4 месяцев назад

.Josh Wolfe: Anybody Using DeepSeek App Is 'Absolute Fool' "Anybody using the DeepSeek app is an absolute fool. If you're using DeepSeek on companies like Together Compute, one of Lux's companies, which can get rid of the CCP censorship, then it's probably okay. But remember, the open-source movement is something we deeply believe in. Most great technologists, entrepreneurs, and venture capitalists are on the side of open source. The closed-source models that have consumed tens of billions of dollars are the ones that are really going to be at risk. When you look at Hugging Face, a major repository, or Together Compute, Runway ML, and a lot of Lux's companies, they have been pioneers in open source. Now, why am I not worried about open source, even with the DeepSeek model? As long as you don't have the CCP censorship on it, the models with their open weights allow people to run on their proprietary data. This means companies like pharma or defense companies that have their own siloed, proprietary data—think about Bloomberg with their proprietary longitudinal data, or Meta with their data—are the ones who will have the edge. Even as open source takes hold, these companies will still dominate. I’m not worried about open source being the problem. I’m more concerned about people overfunding closed models with no proprietary source. A lot of capital is going to be burned there, and we’re already seeing that with people worried about OpenAI in some aspects."

.Josh Wolfe: Anybody Using DeepSeek App Is 'Absolute Fool' "Anybody using the DeepSeek app is an absolute fool. If you're using DeepSeek on companies like Together Compute, one of Lux's companies, which can get rid of the CCP censorship, then it's probably okay. But remember, the open-source movement is something we deeply believe in. Most great technologists, entrepreneurs, and venture capitalists are on the side of open source. The closed-source models that have consumed tens of billions of dollars are the ones that are really going to be at risk. When you look at Hugging Face, a major repository, or Together Compute, Runway ML, and a lot of Lux's companies, they have been pioneers in open source. Now, why am I not worried about open source, even with the DeepSeek model? As long as you don't have the CCP censorship on it, the models with their open weights allow people to run on their proprietary data. This means companies like pharma or defense companies that have their own siloed, proprietary data—think about Bloomberg with their proprietary longitudinal data, or Meta with their data—are the ones who will have the edge. Even as open source takes hold, these companies will still dominate. I’m not worried about open source being the problem. I’m more concerned about people overfunding closed models with no proprietary source. A lot of capital is going to be burned there, and we’re already seeing that with people worried about OpenAI in some aspects."

Josh Caplan

40,039 просмотров • 1 год назад

NVIDIA AQCURIES HUGGING FACE FOR $12.9B. Jensen on the value of open source models: "I recommended that people use closed models as much as they can because they are developing rapidly. We use Claude, Codex, Perplexity, and Cursor at Nvidia. However, there are so many companies that have domain expertise, companies that have sovereignty reasons, they do their own research, those companies need to have control and ownership over their own intellectual proprietary. Open sourced models have become sufficiently good to allow companies to build their own AI."

NVIDIA AQCURIES HUGGING FACE FOR $12.9B. Jensen on the value of open source models: "I recommended that people use closed models as much as they can because they are developing rapidly. We use Claude, Codex, Perplexity, and Cursor at Nvidia. However, there are so many companies that have domain expertise, companies that have sovereignty reasons, they do their own research, those companies need to have control and ownership over their own intellectual proprietary. Open sourced models have become sufficiently good to allow companies to build their own AI."

amit

94,570 просмотров • 7 часов назад

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

290,118 просмотров • 10 дней назад

Why enterprises are going to want to own their own intelligence? "Enterprises are going to want to own their own intelligence. They're going to want AI sovereignty, meaning that you own your whole supply chain of AI. You can take an open source model, fine-tune it on your own company's data, and own your stack end-to-end. People are going to care about sovereignty, cost, and self-improving, and they're not necessarily going to want to give their data to an external third-party service that might even be competing with them one day." Anastasios Nikolas Angelopoulos Will enterprises really care about owning their own intelligence and even be setup to do so in the future Nikesh Arora Vinod Khosla Matt Turck Andy Pavlo (@andypavlo.bsky.social) Brad Gerstner

Why enterprises are going to want to own their own intelligence? "Enterprises are going to want to own their own intelligence. They're going to want AI sovereignty, meaning that you own your whole supply chain of AI. You can take an open source model, fine-tune it on your own company's data, and own your stack end-to-end. People are going to care about sovereignty, cost, and self-improving, and they're not necessarily going to want to give their data to an external third-party service that might even be competing with them one day." Anastasios Nikolas Angelopoulos Will enterprises really care about owning their own intelligence and even be setup to do so in the future Nikesh Arora Vinod Khosla Matt Turck Andy Pavlo (@andypavlo.bsky.social) Brad Gerstner

Harry Stebbings

19,434 просмотров • 1 месяц назад