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Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now: "I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek... and with Qwen, but I would much rather prefer that the leading models are American." "Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed." "There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in." "The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure." "It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that." Sriram Krishnanshow more

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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

138,592 Aufrufe • vor 5 Tagen

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

110,207 Aufrufe • vor 12 Tagen

Open source/weight models are often used in regulated industries like Health Care or Financial Services, where they handle personally identifiable data, and can't send it to proprietary LLM providers. We recently chatted to Vaibhav (VB) Srivastav about the partnership VS Visual Studio Code and Hugging Face inference providers have to let you use open weight models directly in your IDE! Something that surprised me was just how fast inference providers like Cerebras make it to generate code! In this episode we made a journaling CLI tool using Qwen! I personally love open source and hope more of these models will become small enough to run locally!

Open source/weight models are often used in regulated industries like Health Care or Financial Services, where they handle personally identifiable data, and can't send it to proprietary LLM providers. We recently chatted to Vaibhav (VB) Srivastav about the partnership VS Visual Studio Code and Hugging Face inference providers have to let you use open weight models directly in your IDE! Something that surprised me was just how fast inference providers like Cerebras make it to generate code! In this episode we made a journaling CLI tool using Qwen! I personally love open source and hope more of these models will become small enough to run locally!

Marlene Mhangami

18,215 Aufrufe • vor 8 Monaten

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 Aufrufe • vor 3 Monaten

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

1,251,510 Aufrufe • vor 3 Monaten

“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

63,397 Aufrufe • vor 1 Monat

Jack Dorsey says the real danger isn't open source AI, it's five CEOS deciding what the world is allowed to build with AI. "These AI companies are building platforms and they're all incentivized around their own particular models. You have to ask them for permission, you have rate limits, and you have all these things. Even what the models spit back are constrained." "What are the technologies where you don't need permission from a company, from a CEO, to work on what you want, to build what you want, to build a business around that? Those are the things that are durable. That's why these open protocols are significant and important." "It limits the potential of really great ideas bringing humanity forward because it's a decision of a group of CEOs that think they know best. They may know best for their company, but they don't know the best for the creativity of the world and what people actually want to do with it." "Fortunately, there's a great movement in open source AI, and DeepSeek was an important moment in this space for exactly that reason to show a different path and to provide something that is not only competitive but better than the models that the corporations are putting out there." "We should not be reliant upon five companies telling us that they know best, and there should not be open source because it's dangerous. No, we should have these things in the open and race towards solutions that stay ahead of all the dangers." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:

Jack Dorsey says the real danger isn't open source AI, it's five CEOS deciding what the world is allowed to build with AI. "These AI companies are building platforms and they're all incentivized around their own particular models. You have to ask them for permission, you have rate limits, and you have all these things. Even what the models spit back are constrained." "What are the technologies where you don't need permission from a company, from a CEO, to work on what you want, to build what you want, to build a business around that? Those are the things that are durable. That's why these open protocols are significant and important." "It limits the potential of really great ideas bringing humanity forward because it's a decision of a group of CEOs that think they know best. They may know best for their company, but they don't know the best for the creativity of the world and what people actually want to do with it." "Fortunately, there's a great movement in open source AI, and DeepSeek was an important moment in this space for exactly that reason to show a different path and to provide something that is not only competitive but better than the models that the corporations are putting out there." "We should not be reliant upon five companies telling us that they know best, and there should not be open source because it's dangerous. No, we should have these things in the open and race towards solutions that stay ahead of all the dangers." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:

Uncover AI

36,393 Aufrufe • vor 11 Tagen

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."

MTS

14,406 Aufrufe • vor 28 Tagen

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

132,823 Aufrufe • vor 3 Tagen

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

86,163 Aufrufe • vor 26 Tagen

Elon Musk: It should be harder to establish a rule than to remove it. “I'm not completely libertarian in the sense I don't think there should be regulations at all. I just think that the natural bias of regulations is to last forever. You have to actively delete a regulation or a law, the way things are set up in most laws. Some laws have sunset provisions. And the problem with that is you get vested interests who like that law, and there's an inertia around it. And so over time, the body of law and regulations grows and grows and grows. It is something that I think is not ultimately good for society. So, in fact, I think it would generally be a good idea to have it such that it's hard to establish a rule and easy to remove one.” Montana Job Summit, September 16, 2013

Elon Musk: It should be harder to establish a rule than to remove it. “I'm not completely libertarian in the sense I don't think there should be regulations at all. I just think that the natural bias of regulations is to last forever. You have to actively delete a regulation or a law, the way things are set up in most laws. Some laws have sunset provisions. And the problem with that is you get vested interests who like that law, and there's an inertia around it. And so over time, the body of law and regulations grows and grows and grows. It is something that I think is not ultimately good for society. So, in fact, I think it would generally be a good idea to have it such that it's hard to establish a rule and easy to remove one.” Montana Job Summit, September 16, 2013

ELON CLIPS

32,677 Aufrufe • vor 9 Monaten

In between major AI model breakthroughs, new models still ship, but they’re not fundamentally expanding what you can do with them. Braintrust CEO Ankur Goyal says that’s exactly when open source starts to surge: "When new models come out, people forget about open source and forget about economics because it changes fundamentally what you can do." "Programming is a good example. The workflow today is completely different than it was a year ago. If you tried to use models from a year ago today, you wouldn't be able to do crazy stuff like OpenClaw or whatever people are building nowadays." "When models don't change at that speed, people optimize the performance on the use cases that they have." "If you look at usage on our platform, almost half the token usage is coming from open source models from a very small number of companies that have figured out how to optimize use cases really well."

In between major AI model breakthroughs, new models still ship, but they’re not fundamentally expanding what you can do with them. Braintrust CEO Ankur Goyal says that’s exactly when open source starts to surge: "When new models come out, people forget about open source and forget about economics because it changes fundamentally what you can do." "Programming is a good example. The workflow today is completely different than it was a year ago. If you tried to use models from a year ago today, you wouldn't be able to do crazy stuff like OpenClaw or whatever people are building nowadays." "When models don't change at that speed, people optimize the performance on the use cases that they have." "If you look at usage on our platform, almost half the token usage is coming from open source models from a very small number of companies that have figured out how to optimize use cases really well."

TBPN

16,294 Aufrufe • vor 5 Monaten

You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:

You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:

Santiago

324,602 Aufrufe • vor 2 Jahren

Elon Musk: I'm not completely libertarian. I just think it should be harder to establish a rule than to remove it. “I'm not completely libertarian in the sense I don't think there should be regulations at all. I just think that the natural bias of regulations is to last forever. You have to actively delete a regulation or a law, the way things are set up in most laws. Some laws have sunset provisions. And the problem with that is you get vested interests who like that law, and there's an inertia around it. And so over time, the body of law and regulations grows and grows and grows. It is something that I think is not ultimately good for society. So, in fact, I think it would generally be a good idea to have it such that it's hard to establish a rule and easy to remove one.” Montana Job Summit, September 16, 2013

Elon Musk: I'm not completely libertarian. I just think it should be harder to establish a rule than to remove it. “I'm not completely libertarian in the sense I don't think there should be regulations at all. I just think that the natural bias of regulations is to last forever. You have to actively delete a regulation or a law, the way things are set up in most laws. Some laws have sunset provisions. And the problem with that is you get vested interests who like that law, and there's an inertia around it. And so over time, the body of law and regulations grows and grows and grows. It is something that I think is not ultimately good for society. So, in fact, I think it would generally be a good idea to have it such that it's hard to establish a rule and easy to remove one.” Montana Job Summit, September 16, 2013

ELON CLIPS

51,729 Aufrufe • vor 1 Jahr

SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. clem 🤗, co-founder and CEO of Hugging Face: "There was an interesting study from Stanford published last year showing that 70% of the queries that people ask to ChatGPT could be accurately answered locally on your laptop. For free." "Most of the AI workloads that people do today with frontier models could be done by models that are cheaper, faster, more customizable, more controllable. And they don't do it because frankly it's a pain to pick the right model." "You're subsidized so you don't have to care because you have your subscription, so you route everything to Einstein. 'Hey Einstein, what's the weather today?'" "In normal life, he would be like, 'I'm not answering your silly question.' But because it's AI and subsidized by the AI labs, all the questions are getting routed to Einstein versus in an ideal world you have different models that are more specialized and better at answering your questions in different domains." "It's possible that routing is gonna redistribute a lot of the value capture from frontier models to a more long tail of models. It's like AI maturing... we are in the first phase where it's very simple, everyone using just one giant model. Now we're moving to the second phase."

SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. clem 🤗, co-founder and CEO of Hugging Face: "There was an interesting study from Stanford published last year showing that 70% of the queries that people ask to ChatGPT could be accurately answered locally on your laptop. For free." "Most of the AI workloads that people do today with frontier models could be done by models that are cheaper, faster, more customizable, more controllable. And they don't do it because frankly it's a pain to pick the right model." "You're subsidized so you don't have to care because you have your subscription, so you route everything to Einstein. 'Hey Einstein, what's the weather today?'" "In normal life, he would be like, 'I'm not answering your silly question.' But because it's AI and subsidized by the AI labs, all the questions are getting routed to Einstein versus in an ideal world you have different models that are more specialized and better at answering your questions in different domains." "It's possible that routing is gonna redistribute a lot of the value capture from frontier models to a more long tail of models. It's like AI maturing... we are in the first phase where it's very simple, everyone using just one giant model. Now we're moving to the second phase."

MTS

49,884 Aufrufe • vor 27 Tagen

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."

Cameron Jourdan

619,229 Aufrufe • vor 2 Monaten

"Yes, it’s too soon to tell, but it is interesting that large language models, as opposed to social media, have tended to be much more aligned with what we would consider objective reality and truth. That is, I think it’s not so easy to get a large language model to endorse a ridiculous conspiracy theory, such as that the 2020 U.S. election was stolen or that COVID vaccines are actually microchips that Bill Gates is implanting to surveil us. All of those ideas are very easy to find on social media. And it may indeed be, as you say, that large language models tend to gravitate toward common priors—namely, all the knowledge that’s out there on the web. But, in particular, during pre-training and post-training—the fine-tuning process—they are engineered to be aligned with truth and reality. And that is because the AI companies have a different business model than the social media companies." From an episode of Scaling Theory with Thibault Schrepel: Steven Pinker on Common Knowledge, From Eye Contact to the Super Bowl

"Yes, it’s too soon to tell, but it is interesting that large language models, as opposed to social media, have tended to be much more aligned with what we would consider objective reality and truth. That is, I think it’s not so easy to get a large language model to endorse a ridiculous conspiracy theory, such as that the 2020 U.S. election was stolen or that COVID vaccines are actually microchips that Bill Gates is implanting to surveil us. All of those ideas are very easy to find on social media. And it may indeed be, as you say, that large language models tend to gravitate toward common priors—namely, all the knowledge that’s out there on the web. But, in particular, during pre-training and post-training—the fine-tuning process—they are engineered to be aligned with truth and reality. And that is because the AI companies have a different business model than the social media companies." From an episode of Scaling Theory with Thibault Schrepel: Steven Pinker on Common Knowledge, From Eye Contact to the Super Bowl

Steven Pinker

57,812 Aufrufe • vor 19 Tagen

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 Aufrufe • vor 19 Tagen

Sora animates with this wonderful wonky, sketchy dreamlike quality that perfectly captures the nostalgic atmosphere of a hazy 90's suburban summer afternoon. While Seedance is just as sophisticated and in some aspects superior, I will miss the quality of Sora. Sora feels like 35mm film, with the nuanced way it captures lighting, color, and perspective, while Seedance feels digital - a bit too clean. I am confident that I can replicate this sketchy quality in Seedance by tweaking my prompts, but Sora has a unique way of animating that really should be preserved. There are many more bugs and mistakes with Sora, but when it gets it right, it REALLY hits a level of artful magic that sets it above all other models. I am shocked that I still appear to be the only person who is creating AI-Generated 2D animation with original characters while developing a unique Western style. Practically no one is doing 2D AI-animation at all, and when they do, it is usually an attempt to mimic an Anime style. 2D really should be attempted more by AI Filmmakers!! Especially with a Western model like Sora, before it is terminated in the fall. Really, everyone should be taking advantage of the way this model so skillfully animates, with the heart and soul of a seasoned professional. I personally feel AI-generated animation is superior to 3D/realistic AI filmmaking. While AI-generated realism is an attempt to mimic real life through a lens, 2D animation IS what it is - not a replica of anything, just a cartoon. I love all my AI filmmaker bros and all of the cutting edge work going on, but I urge all of you to give 2D animation a chance. : ) I'm still not giving up hope that we can save Sora somehow. Now that I see that Seedance is able to animate 2D brilliantly and beautifully, I know that it's not some hidden secret, and we can replicate the weights and maths of Sora. If we can't preserve Sora, we can make a comparable model. It's not just in the interest of AI-Animators like me to preserve this model, but in the interest of the entire American AI community if they want Western AI to be superior. If not, Chinese video models will dominate. And while I am perfectly happy to use a Chinese model and I am just eternally grateful that this technology exists at all, I would love to see American audiovisual models continue to be developed! #AIAnimation #AIFilmmaking #AIArt #SaveSora #SummerofSora #WillStancilShow Elon Musk Marc Andreessen 🇺🇸 Sora Bill Peebles NVIDIA Sam Altman

Sora animates with this wonderful wonky, sketchy dreamlike quality that perfectly captures the nostalgic atmosphere of a hazy 90's suburban summer afternoon. While Seedance is just as sophisticated and in some aspects superior, I will miss the quality of Sora. Sora feels like 35mm film, with the nuanced way it captures lighting, color, and perspective, while Seedance feels digital - a bit too clean. I am confident that I can replicate this sketchy quality in Seedance by tweaking my prompts, but Sora has a unique way of animating that really should be preserved. There are many more bugs and mistakes with Sora, but when it gets it right, it REALLY hits a level of artful magic that sets it above all other models. I am shocked that I still appear to be the only person who is creating AI-Generated 2D animation with original characters while developing a unique Western style. Practically no one is doing 2D AI-animation at all, and when they do, it is usually an attempt to mimic an Anime style. 2D really should be attempted more by AI Filmmakers!! Especially with a Western model like Sora, before it is terminated in the fall. Really, everyone should be taking advantage of the way this model so skillfully animates, with the heart and soul of a seasoned professional. I personally feel AI-generated animation is superior to 3D/realistic AI filmmaking. While AI-generated realism is an attempt to mimic real life through a lens, 2D animation IS what it is - not a replica of anything, just a cartoon. I love all my AI filmmaker bros and all of the cutting edge work going on, but I urge all of you to give 2D animation a chance. : ) I'm still not giving up hope that we can save Sora somehow. Now that I see that Seedance is able to animate 2D brilliantly and beautifully, I know that it's not some hidden secret, and we can replicate the weights and maths of Sora. If we can't preserve Sora, we can make a comparable model. It's not just in the interest of AI-Animators like me to preserve this model, but in the interest of the entire American AI community if they want Western AI to be superior. If not, Chinese video models will dominate. And while I am perfectly happy to use a Chinese model and I am just eternally grateful that this technology exists at all, I would love to see American audiovisual models continue to be developed! #AIAnimation #AIFilmmaking #AIArt #SaveSora #SummerofSora #WillStancilShow Elon Musk Marc Andreessen 🇺🇸 Sora Bill Peebles NVIDIA Sam Altman

Emily Youcis

18,940 Aufrufe • vor 2 Monaten

Earlier this week at GTC, we announced our partnership with Nvidia. We will work with Nvidia to build strong, American open-source models that are at the frontier of scientific reasoning. These models will be essential for the US to compete with China on science in the coming decades. Jensen is committing to spend tens of billions of dollars developing open-source models, and we are excited to be a partner with them in figuring out how to benchmark, train and use those agents to accelerate scientific research. We have already open-sourced some of the work we have done with them, and are looking forward to open-sourcing more. There are few things today that are more important. See our blog post below, and watch the video to learn more, narrated by the man himself.

Earlier this week at GTC, we announced our partnership with Nvidia. We will work with Nvidia to build strong, American open-source models that are at the frontier of scientific reasoning. These models will be essential for the US to compete with China on science in the coming decades. Jensen is committing to spend tens of billions of dollars developing open-source models, and we are excited to be a partner with them in figuring out how to benchmark, train and use those agents to accelerate scientific research. We have already open-sourced some of the work we have done with them, and are looking forward to open-sourcing more. There are few things today that are more important. See our blog post below, and watch the video to learn more, narrated by the man himself.

Sam Rodriques

23,301 Aufrufe • vor 4 Monaten