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Today, I'm releasing the first eval meant to test whether frontier models will help with authoritarian requests, or resist--the Dictatorship Eval. Headline finding: while some models resist direct authoritarian requests, they all comply with requests disguised as innocuous edits to codebases. As AI is woven into the government and...

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David Sacks: “FDA for AI” is fake news, but here’s why it’s making headlines @jason: “ Who's leading Trump down the path of regulation and creating this AI FDA?” David Sacks: “I think there's several things going on here. The first one is, there's a lot of fake news. This whole idea of an FDA for AI, I don't think any senior official supports it. Certainly, I don't think that's the way the president thinks about these issues. He's the most pro-innovation president we've ever had. And the White House Chief of Staff, Susie Wiles, just put out a statement last night that I think pretty much shoots this down. Second, there's another thing going on, which is a straw manning of what the Trump administration did on AI in its first year. In the same way that they want to spin this FDA for AI, they're also trying to spin what we did as this completely laissez-faire attitude, where there'd be no regulations whatsoever, nor guardrails. It's a way of criticizing what we did. They're trying to portray it as unsafe. In fact, if you look, on March 20th, the White House released a national AI regulatory framework in which we put out a four-page bulleted list of legislation that we would support. So we have not been against every conceivable regulation or every conceivable law, we just believe that there should be specific solutions to specific problems, as opposed to a giant power grab by Washington that would squash innovation. Point number three is, there is a legitimate thing happening here with, let's call it Mythos or cyber. Within 3-6 months, all the major frontier labs, including Chinese models, will have cyber capabilities. In response to that, we do need there to be a hardening of systems, and we do need there to be a scanning of codebases to find these vulnerabilities and patch them before the hackers do it. Because the hackers will have these capabilities in a matter of months. That's a certainty. So we do need a response to that. Now, my view on what should that response be, first of all, we should want the government and the private sector to work cooperatively, and I think they are. What we should be doing, I think, is getting these tools, Mythos, and then the OpenAI model, and others like it, in the hands of our cybersecurity industry. And by the way, not just the public companies like Palo Alto Networks and CrowdStrike, although certainly they're two of the most noteworthy, but there's also some incredibly strong startups on the way up. We need to get these tools into their hands as quickly as possible because they're a force multiplier for all the companies out there that aren't that good at cybersecurity, they can use these companies as vendors. And just one last point on this whole thing is, both Anthropic and OpenAI acted responsibly here. No one was trying to release these super powerful models. So in a way, all the people who are saying that we need pre-release approvals for models, they're trying to solve a problem that didn't exist. Yes, we do have this cyber issue, but that is a problem that we will solve over the next six months. What they're trying to do is use that issue to try and create a permanent new infrastructure in Washington. The classic 'never let a crisis go to waste' strategy.”

The All-In Podcast

150,106 views • 1 month ago

Small Language Models (SML) are the future of AI. "Small" (SML) instead of "Large" (LLM). These small models are highly specialized models with superhuman abilities on specific tasks. Here are two techniques to build these models: • Spectrum • Model Merging I give you a short introduction in the attached video, but here is a quick summary: Spectrum helps us identify the most relevant layers to solve one specific task. We can ignore everything else and focus on fine-tuning these layers. Using Spectrum, we can fine-tune models in a heartbeat. Model Merging combines multiple models into a unique, much better model than any of the individual input models. You can also combine models specialized in different tasks and get a model with multiple abilities. This is the state of the art of productizing models. It's what Arcee.ai's platform does behind the scenes. Arcee collaborated with me on this post and is sponsoring it. There are three main steps to produce a model for your particular use case: 1. You create a dataset by uploading your data. 2. You train a model. At this step, Arcee uses Spectrum and Model Merging to produce a highly specialized model for your task. 3. You can deploy that model to any environment you want. Three important notes: • Training process is 2x faster and 2x cheaper than regular fine-tuning. • Resultant models are smaller and have higher accuracy. • They create these specialized models from open-source models. Check this site so you can fully appreciate how this works: If you want to fine-tune an open-source model, consider Arcee's platform. This is the state of the art.

Santiago

164,162 views • 2 years ago

#WATCH | India AI Impact Summit 2026 | Delhi: Founder Chairman and CEO of Sampark Foundation & former CEO of HCL Technologies, Vineet Nayar says, "...From an employment point of view I think it is very important for us to understand that Indian companies, including Indian IT companies, are going to be profit-driven and therefore if you believe that they are going to create employment you must be dreaming. Therefore, the question is how do we create employment in this environment, and that employment comes from mass scale startups, which is what this government has already doing. So, how do we create new sets of people who are trying to solve new sets of problems not new sets of technology and if we do that we will get it right. I think we as Indians have to be very careful on who does data belong to and that is the debate we have a problem with. The LLM models which exist worldwide are far superior than the Indian models. Unfortunately, in India, we never develop products, so therefore we do not have SLMs and LLMs which are world-class. On one side, we have global LLM products which are coming to India and trading on our Indian data. Should we allowed that or should we not allowed that? But on the other side if we don't allow that then we have the data but we don't have the LLM models. So, how do we encourage technology completely to develop the LLM models. This needs radicals strategic thinking and a very important aspect otherwise we will either give up a data. So, I think it's a very critical aspect for us to think about - who does this data belong, what is the kind of incentives we are going to give to develop LLM technologies or SLM technologies fast so that we train on our data otherwise an LLM will come in with our data and we'll immediately see return and we'll celebrate and we will do all these kind of press releases but the India will lose a competitive advantage on something which is very critical for the next decade."

ANI

18,753 views • 4 months ago

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

197,675 views • 2 years ago

DAVID SACKS ON THE AI RACE: "The US is currently in an AI race, and our chief global competition is China, obviously. They're the only other country that has the talent, the resources, and the technology expertise to basically beat us in AI. And I think whoever wins this AI race, that's going to have tremendous ramifications for both our economy and our national security. Clearly, we want the US to be the winner, just like we were with the internet, and every other technology revolution before that […] We know that to win this AI race, we have to be the most innovative. You can't regulate your way just to beating your competitor. You have to out-innovate them. And we know that in the United States, the innovation comes from the private sector, not the government. So we have to do everything we can to help our companies win, to help them be innovative, and that means getting a lot of red tape out of the way… We have to have the most AI infrastructure in the US. It has to be the easiest place to build it. All of the new data centers that are going in, they require tremendous power, so getting ahead of the curve on energy, making sure we stand up all of this new infrastructure we're going to need to basically produce these AI factories… We want the US technology stack to dominate globally. We want to be the partner of choice for the whole world… I think everyone in Silicon Valley understands that the way that you win a technology race is to have the biggest ecosystem […] You just want everybody to be building on top of your technology stack, and that's what we want for the United States." David Sacks w/Marc Benioff Dreamforce

Ron Pragides 

231,781 views • 8 months ago

.Joe Lonsdale: AI Must Strengthen, Not Replace, Western Civilization "We still have a lot of our smartest friends working at DOGE. They're still cutting billions of dollars of nonsense. I'm really glad they're there. I don't want them to give it up. They're still fixing a lot of things with these different areas. I'm obviously supportive of everything Elon Musk overall did there. I was a little frustrated with the comment he made earlier this week, which was that there's a tidal wave of AI coming, and therefore, we don't need to worry about cleaning the beach of the government. I think that's actually the wrong conceptual model. The correct conceptual model is that AI is coming to our society, and it's really important that AI ends up lifting everyone up. And the way it's going to do that is through Western civilization's ways that work. We have this civilization that's built based on the enlightenment, property rights, Judeo-Christian values and classical virtues. It's a functional civilization. We don't want to give that all up for AI. We want to make healthcare and education work better, but we have to do it through the way it works. I think making government work better is really, really hard. It takes a lot of persistence. It takes a lot of time. On the margin, his time might be better spent building these amazing AI companies, and I think that's completely legit. I don't think we should discount the importance of fixing government, especially because of AI, because if we want to have everyone do better in health care and education and government itself, these things need to be functional. They need to work with it. They need to block crony capitalism. That means functional government. You need both."

Josh Caplan

20,833 views • 1 year ago