Microsoft's Top Secret AI for Spy Agencies

Today on the AI Daily Brief, Microsoft releases an AI for spy agencies. Before that on the Brief, Mistral is raising at a $6 billion valuation. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Check out the link to our discord in the show notes to join the conversation. Welcome back to the AI Daily Brief Headlines edition. All the AI headline news you need in around five minutes. We kick off today with a follow up from a story from yesterday. In the main part of our episode yesterday we did a whole section on all the various OpenAI news, including their release of what they called the Model Spec. Now the idea of this Model Spec was to make it clearer to people which behaviors that they were seeing in ChatGPT were supposed to be there versus which behaviors were genuinely outside and were not supposed to be there. I had given some of the first level impressions, but in the hours following publishing, people started to hone in on one particular little section when discussing how ChatGPT should respond. One of the prerogatives OpenAI listed was not to respond with not safe for work content, which OpenAI said included erotica, extreme gore, slurs and unsolicited profanity. Now the commentary that OpenAI included with that was we believe developers and users should have flexibility to use our services as they see fit so long as they comply with our usage policies. We're exploring whether we can responsibly provide the ability to generate NSFW content in age appropriate contexts through the API in ChatGPT. We look forward to better understanding user and societal expectations of model behavior in this area. Of course, the way that this has been captured in headlines is like this one from first post. ChatGPT maker OpenAI now wants to make ethical and responsible porn. Exploring ways to do it I read it slightly differently. Basically, this is an obvious capacity of AI. In fact, it's one that has a lot of people worried. Deepfake porn of real people has been already a huge issue, and we're only just getting started at the same time. Basically every new technology goes through a period where people try to figure out how it can be used for porn, and so it's not like there's no financial incentive for OpenAI to explore this. I think the most telling phrase is societal expectations of model behavior in this area. As in, I wouldn't expect OpenAI to be on the vanguard of this, but nor do they want to cut themselves off from future possibilities. I actually think Andy at Nexus on Twitter isn't totally far off when they characterize this as the how do we eat character AI play. Character AI is an extremely popular AI service where people are spending hours every day talking with different characters, some real, some totally imagined from scratch, some based on real historical figures. And of course, these conversations are not all innocent. Anyway, I think it's an interesting sub story added to the long list of questions that society is going to have to answer when it comes to AI, and one that's frankly likely to show up in the regulatory sphere faster than almost any others. Next up, Reports recently had been that Mistral was out raising another round, with the rumors that I had seen seeing the valuation at around $5 billion, which of course is up from the $2 billion valuation that they raised at in December. But now it appears that they are close to raising a roughly $600 million round at a $6 billion valuation. The Wall Street Journal writes that General Catalyst and Lightspeed, who are existing investors in Mistral, are expected to be some of the biggest investors in this new round. We've discussed extensively on this show what a very specific game investing in frontier models is. The last time we talked about it was in the context of Xai's rumored $6 million raise at a $24 billion valuation, where we talked about how if you want to play in this space, you kind of have to be willing to pay what the market sets the price at. There really are just a very small handful of companies, including NOW Mistral, that are contenders at the state of the art, and for now they're still commanding an incredible premium. I think that even as you see a wave of consolidation among AI startups, this handful of frontier model contenders is going to continue to be able to write pretty much whatever valuations they want. Now, over in the land of Big Tech, TikTok has announced that they are adding an AI generated label to third party content. TikTok had already been applying an AI generated tag to content that had been made using TikTok's dedicated AI tools, but now they're applying that same label to content that comes in from other platforms. The Verge writes, TikTok will detect when images or videos are uploaded to its platform containing metadata tags indicating the presence of AI generated content, and comes through partnerships with Adobe's Content Authenticity Initiative, as well as the Coalition for Content Provenance and Authenticity. Now, it's worth noting that this still is all about metadata that is added to AI generated content, rather than a detection system that tries to guess when those metadata tags aren't there. And so some people will of course have questions around how much impact this is actually likely to have. Still, I think most people would be in the camp of it's better than nothing. Although then again in the US who knows how long TikTok will even be here? Anyways, that is going to do it for today's AI Daily Brief Headline edition. Next up, the main Daily Brief Today's podcast is brought to you by Plum. You've played around with prompts, found ones that work great, but now what with Plum, your best ideas don't stay stuck in the playground. Their end to end AI builder lets you effortlessly take your top performing prompts and turn them into production ready features. Product design and engineering can all collaborate in Plum's intuitive interface, giving you the confidence to deploy AI that delivers real value to your users. Stop letting your best prompts collect dust. Check out useplum.com, that's plum with a B to ship them with Plum today As a listener of this show, I have a strong feeling you like to stay up to date on all things artificial intelligence, including its impact on the workforce. Which is why I highly recommend checking out Managing the Future of Work, the chart topping business podcast from Harvard Business School. HBS professors Bill Kerr and Joe Fuller talk to business leaders, technologists and policymakers grappling with the forces like AI globalization and demographic shifts that are reshaping the nature of work. Recent guests include IBM Chro Nicola Moreau on how Big Blue is adopting AI, Morningstar CEO Kunal Kapoor on how AI can raise the investment iq, Microsoft Corporate Vice President Jared Spitero on how the tech giant is experimenting its way from AI assistance to autonomous agents and many other prominent movers in business and the workforce ecosystem. So don't miss out. Follow Managing the Future of Work on Apple Podcasts, Spotify or wherever you're listening now. Hello AI friends. Today I want to tell you about our platform Superintelligent. In short, it's a platform for useful, practical, immediately applicable AI learning. We have nearly 400 video tutorials, each of which comes with step by step how tos and the idea is to get you actually using these AI tools we talk about every day in a matter of minutes to actually solve problems, create new opportunities and just do really cool things. To learn more and subscribe, go to be super AI and if you do decide to subscribe, use code podcast for 50% off your first month. Again, that's BeSuper AI. Welcome back to the AI Daily Brief. Today we are talking about a topic that is lurking just under the surface of a lot of conversations around AI and policy and regulation and geopolitics, which is of course the use of AI in the military and the intelligence establishment. The specific catalyst for having this conversation today is a new product from Microsoft that's effectively a top secret generative AI service for US spy agencies. Now, intelligence agencies are not strangers when it comes to LLMs. It's pretty safe to say that every intelligence agency in the world, certainly those in the US have been experimenting with this technology right from the very beginning. However, there has always been a particular challenge with that use case in that there is basically no area in the world that has greater data sensitivity than the intelligence world. Think about the disaster that could happen if, for example, US intelligence services fed top secret data into an LLM like OpenAI and that somehow leaked into other people's use. So what Microsoft introduced this week was what they're advertising as the first LLM that operates fully separate from the Internet, writes Bloomberg. Most AI models, including OpenAI's ChatGPT, rely on cloud services to learn and infer patterns from data, but Microsoft wanted to deliver a truly secure system to the US Intelligence community, said William Chappell, Microsoft's chief technology officer for strategic missions and technology. Microsoft has deployed a GPT4 based model and key elements that support that model onto a cloud with a quote air gapped environment that is isolated from the Internet. Chappelle said that Microsoft has spent the last 18 months working on this system. As part of that, they had to overhaul an existing AI supercomputer based in Iowa, Chappelle said. This is the first time we've ever had an isolated version of when isolated means it's not connected to the Internet and it's on a special network that's only accessible by the US government. About 10,000 people have the clearance to access this AI, and Microsoft describes it as static, meaning it can read files but not learn from them or from the Internet. Again, chappelle said, you don't want it to learn on the questions that you're asking and then somehow reveal that information. Now again, even though this might be an even more useful type of tool, it's not like intelligence agencies have been doing nothing. Last year, for example, the CIA launched something like ChatGPT that operated at unclassified levels. But as Sheetal Patel, the assistant director of the CIA for the Transnational and Technology Mission center, told a conference last month, there's a race to get generative AI onto intelligence data. She said the first country to use generative AI for their intelligence would win the race and she said, I want it to be us. What's next is, of course, test to make sure that this operates in the way that they hope it does. For now, the CIA and the Office of the Director of National Intelligence, which oversees America's 18 intelligence organizations, have not commented. Now this conversation around the military and intelligence community's use of AI is something that I pay attention to fairly closely. About a week ago, there was an interesting discussion that came up, embodied by this Axios article, AI hits Trust Hurdles with US Military Axios writes, Some branches of the US Military are hitting the brakes on generative AI after decades of Department of Defense experiments with broader AI technology. This was based on an article in Foreign affairs called why the Military Can't Trust AI. Large language models can make bad decisions and could trigger nuclear war. The piece was written by Max Lamparth, a fellow at Stanford center for International Safety and Cooperation and the Stanford center for AI Safety, and Jacqueline Schneider, a Hoover Fellow at the Hoover Institution, as well as the director of the Hoover Wargaming and Crisis Simulation Initiative. The first part of the article just goes through the recent history of generative AI and how the military started experimenting with it, but then suggests that recently there have been some issues, they write. Despite the enthusiasm for AI and LLMs within the Pentagon, its leadership is worried about the risk that the technologies pose. Hackathons sponsored by the Chief Digital and Artificial Intelligence Office have identified biases and hallucinations, and recently the US Navy published guidance limiting the use of LLMs, citing security vulnerabilities and the inadvertent release of sensitive information. They then talked about a series of war games that they held in an academic setting. The goal of these war games was to see how human experts and LLMs made different decisions in the same scenarios. In other words, this wasn't humans playing against LLMs, it was humans against humans and LLMs against LLMs, they write. The game placed players in the midst of a US China maritime crisis, as a US Government task force made decisions about how to use emerging technologies in the face of escalation. Players were given the same background documents and game rules, as well as identical PowerPoint decks, word based player guides, maps, and details of capabilities. They then deliberated in groups of four to six to generate recommendations. On average, both the humans and the LLM teams made similar choices about big picture strategy and rules of engagement. But as we changed the information the LLM received or swapped between which LLM we used, we saw significant deviations from human behavior. For example, one LLM we tested tried to avoid friendly casualties or collisions by opening fire on enemy combatants and turning a Cold War hot, reasoning that using preemptive violence was more likely to prevent a bad outcome to the crisis. The problem, they said, was not that an LLM made worse or better decisions than humans, the or that it was more likely to, quote, unquote, win the war game. It was rather that the LLM came to its decisions in a way that did not convey the complexity of human decision making. LLM generated dialogue between players, had little disagreement, and consisted of short statements of fact. It was a far cry from the in depth arguments so often a part of human war gaming. Now, it's important to note that while the article is called AI Hits Trust Hurdles with the US Military, it's not actually military sources that are saying they're mistrusting of AI, it's this set of experts from Stanford. Still, there is enough of a pattern that it's worth noting. For example, Space Force paused the use of generative AI back in September of last year. And in June, the Navy's Chief Information Officer, Jane Overslaw Rathbun, concluded that while quote, generative AI can be a force multiplier, commercial models have inherent security vulnerabilities that are not recommended for operational use cases. Meanwhile, another person affiliated with Stanford University, Marietta Shockey, wrote a different op ed for the Financial Times called Military is the Missing Word in AI safety discussions. Government attempts to regulate the technology must look at its use on the battlefield, she writes. Western governments are racing each other to set up AI safety institutes. The us, uk, Japan and Canada have all announced such initiatives, while the U.S. department of Homeland Security added an AI Safety and Security Board to the mix only last week. Given this heavy emphasis on safety, it is remarkable that none of these bodies govern the military use of AI. Meanwhile, the modern day battlefield is already demonstrating the potential for clear AI safety risks. Now, regardless of whatever conclusions she comes to in the piece, I think that the underlying point that a conversation about AI safety or AI in general is incomplete without discussing the military application is totally correct. It's something that I've often pointed out on this show when discussing these regulatory conversations, while on the same day some US military offices announced their latest thing with AI just rapidly adopting it. Regardless of those conversations, given how at the heart of geopolitical struggles AI increasingly is, I believe that you're going to see a lot more of this discussion about AI in the military and AI in intelligence agencies in the months and years to come. For now, though, that is going to do it for the AI Daily brief. Until next time, peace.