The AI Daily Brief: Artificial Intelligence News and Analysis - AI's Battle for Your Context

Starting point is 00:00:00 Today on the AI Daily Brief, why the biggest battle in AI is the battle for your personal context. Before that in the headlines, could this be the biggest year for IPOs in history? The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors. Assembly, landfall, Zen Coder, and Superintelligent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on novel podcasts. If you're interested in sponsoring the show, you can send us a note at sponsors at AIdailybrief.

Starting point is 00:00:39 com.A.I. And finally, also at AIdailybrief.com. A.I., you can find out about all the other goings on in the world of AIDB, including AIDB Intel, our new operators community, our AIDB New Year's self-guided skills course, and the new AIDB Intel service, which will have much more info coming in the next week or so. But with that out of the way, let's dive in. Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in around five minutes.

Starting point is 00:01:03 We kick off today with two stories that I discussed in my 2026 predictions, one where it looks like I might be wrong, one where it looks like I might be right. The one where I might be wrong is that contra to my base case, that neither OpenAI or Anthropic ultimately go public in 26, the New York Times finds a lot of evidence that they are getting ready. They wrote, Anthropic and OpenAI have taken early steps to go public, people familiar with the companies said. And SpaceX, Elon Musk's rocket company, has interviewed banks to lead an IPO, according to two people with knowledge of the situation. Now, these three companies are already valued between $350 and $800 billion each, add in a premium for the public offering, and we could easily see multiple trillion dollar

Starting point is 00:01:43 IPOs this year. That is extraordinarily rare. The only real comparison at those levels are the $1.7 trillion valuation for the Saudi Aramco IPO in 2019. No tech startup has ever come close. Morgan Stanley's Adi Maloy said, we're going to get into a period of potentially unprecedented IPO deal sizes, but we are confident they're executable given the scale of these companies and the investor interest. Now, Malloy in this case is referring to concerns that the public markets can't handle deals of this size. As part of all of the AI bubble chatter, there's been talk that investment banks might force existing shareholders into a rolling unlock rather than the more usual six-month cliff to stagger the selling. Others expect demand to be so hot that selling won't be an issue. Certainly it is the case that despite claims that the current stock market is starting to resemble the dot-com boom,

Starting point is 00:02:27 we haven't seen anything comparable to the thousands of IPOs for emerging tech companies that mark that era. What that means is that for most investors, this would be the first time that they got access to pure play companies developing AI. Jeremy Abelson, a VC at Irving investors, said, in two decades, I haven't seen private companies that are this meaningful and are this impactful. Not only are they bigger and more relevant, but they're incredible companies with numbers that we've never seen before. You can expect analysis of these big three to dominate finance discussions over the coming year, with very loud opinions on both sides of the argument. Some compared this moment to the record-breaking Facebook IPO in 2012. That listing both solidified social media as a major category

Starting point is 00:03:05 and was also seen as an utter catastrophe in the market, with the Wall Street Journal calling it a fiasco. The stock was down 15% after a week and took 14 months to trade above its IPO price. At the time, it was the third largest IPO in history. Although in the current frame of reference, its $90 billion valuation was exceedingly modest. Jeff Thomas, the head of listings at NASDAQ said, when these mega deals happen, it takes some of the air out of the room. You want to try to get ahead of it. Others noted that transparent information on the leading AI companies could diffuse the bubble chatter. Said notable cap, Jeff Richards, there is such a big information gap right now. The biggest positive for this entire market would be if a bunch of these companies went public and people could actually see the numbers.

Starting point is 00:03:44 Now, my argument for why I didn't think that Open AI and Anthropic would ultimately go public this year is a, public market reporting is a total pain in the butt, especially when they're in the category that is already the most under scrutiny, and B, I think there is plenty of capital still available in private markets for their financing needs. Now, B, might be more dubious that I'm giving a credit for, not because there isn't private capital, but just because the scale of the need might be so huge, and there is also, of course, a competitive dynamic thing. There are lots of good reasons, for example, for Anthropic to want to scoot in ahead of Open AI, and lots of good reasons for Open AI to not want to let that happen. For that reason alone, we may be headed into a very big year

Starting point is 00:04:19 when it comes to public markets. Now, the prediction I did a little bit better on then is one where I said that Anthropic was going to continue to be hard to displace when it came to its lead in coding, and that I thought that Microsoft was likely to get much closer to Anthropic over the course of the year. According to the information, Microsoft has indeed quietly become one of Anthropics' largest customers

Starting point is 00:04:37 over recent months. As of July last year, Microsoft began using Anthropic to power coding agents and GitHub co-pilot. But the big shift began in September when OpenAI and Microsoft agreed to the amicable end of their exclusive partnership. Microsoft quickly announced they would add support for Anthropics models within their co-pilot products. The new multi-model version of copilot routes each tasks to the most appropriate model. And for many of the tasks in Microsoft's productivity suite,

Starting point is 00:04:59 the right choice seems to be an anthropic model. The report stated that Claude Sonnet 4.5 has a 15% performance advantage over GPT-40 in agent mode for complex Excel tasks, although why the hell anyone's using 4O is beyond me, while the super long context window of Claude Opus 4.1 is being used for mass summarization and analysis tasks. Haiku 4.5 is also seeing heavy use due to his cost and speed advantage for smaller tasks. Business customers didn't have to upgrade or change anything in their plans, but as of last week, they're now receiving access to Anthropic models by default. The information reports that Microsoft has spent more than $40 million per month with Anthropics

Starting point is 00:05:32 starting in July, a $500 million annualized pace that is likely a lot higher now, given that the models are seeing more use. In addition, the report states that Microsoft Cloud staff have been incentivized to sell Anthropic products. And finally, deepening the new ties, Anthropic will reportedly work with Microsoft to develop new Claude Power features for co-pilot over the coming months. A liquid on Twitter said what I think a lot of people feel, Anthropic and Microsoft was the partnership that made sense all along. Speaking of partnerships and OpenAI, Chip Startup Cerebris has landed a $10 billion compute deal with the company. The three-year deal will see Cerebris provide OpenAI with 750 megawatts

Starting point is 00:06:08 worth of AI inference compute. A press release said that OpenAI plan to integrate Cerebris's chips into their broader computing network to provide faster response time. Cerever's CEO Andrew Feldman posted, this has been a decade in the making. Deployment begins in early 2026, and when fully rolled out, it will be the largest high-speed AI inference deployment in the world. He claimed that Cerebrus' uniquely designed chips are now able to deliver 15x faster inference without sacrificing model size or accuracy. He added, as models grow more capable, speed becomes the bottleneck.

Starting point is 00:06:37 Slow systems limit what users can do, how often they engage, and whether AI becomes infrastructure or remains a novelty. Matthew Berman wrote, I've always wondered why OpenAI didn't use GROC or Cerebris, they're so fast. Now we know why GROC was bought by NVIDIA. Everything is moving to specialized chips. Revenue is made at inference. ChatGBT is about to be a hundred times faster. Now lastly today, we stay on Open AI but move to some serious industry psychodrama. A trio of leading AI researchers are returning to Open AI amid allegations of corporate espionage.

Starting point is 00:07:07 On Wednesday night we had dueling tweets. Former OpenAI CTO and now CEO of Thinking Machines Labs, Miramirani wrote, We have parted ways with Barrett Zof. Sumith Jantala will be the new CTO of Thinking Machines. He's a brilliant and seasoned leader who has made important contributions to the field of AI for over a decade, and he's been a major contributor to our team.

Starting point is 00:07:25 We could not be more excited to have him take on this new responsibility. Meanwhile, about an hour later, OpenAI, CEO of Applications, Fiji Simo tweeted, excited to welcome Barrett Zoff, Luke Metz, and Sam Schoenholz back to Open AI. This has been in the works for several weeks and we're thrilled to have them join the team. Barrett will report to me, Luke and Sam will report into Barrett.

Starting point is 00:07:42 More to come on what they'll focus on soon. Now, by way of background, these three left OpenAI in late 2024 alongside CTO Miramir Maradi as part of a mass exodus of talent. They were pivotal in the subsequent founding of Maradi's Thinking Machines Lab. Zolf and Metz were in fact listed as co-founders of TML, with Zof also receiving the CTO title. This is a significant personnel move that could have implications for the course of both companies. Zof first joined OpenAI in 2022 to serve as their VP of research.

Starting point is 00:08:08 Prior to that, he was at Google DeepMind for six years. At OpenAI, he built the post-training team from scratch with John Shulman, who also left to co-found TML. That team yielded the O1 model and helped kickstart the new reasoning paradigm. Metz and Schoenholz are also leading experts on post training and reinforcement learning. Now, for TML, it's very difficult to know how bad a sign this is. The departure of two co-founders and another senior researcher obviously isn't a great indication of how things are going. Anonymous Twitter poster Signal wrote,

Starting point is 00:08:33 So like, Thinking Machines completely imploded today? Someone DM me the T, please? And yet at the same time, adding to the intrigue, Kylie Robeson of Core Memory reported the story with a different twist, writing, Thinking Machines has terminated its CTO Barrett Zof due to unethical conduct, according to two sources familiar with the matter. CEO Miramiradi announced the news that in all hands with employees today. Max Zeph followed up with this angle for Wired, writing that his sources at TML said that Zof had shared confidential company information with competitors. The timeline was laid out in a memo written by Fiji Simo on Wednesday and shared with Wired. Zeph wrote, according to the memo from Simo, Zof,

Starting point is 00:09:07 told Thinking Machine CEO Miramir Maradi on Monday he was considering leaving. He was then fired on Wednesday. Simo went on to write that OpenAI doesn't share the same concerns about Zof as Maradi. I don't know, man, obviously from outside it's hard to tell exactly what's going on, but from a sheer talent perspective, you gotta think it was a good day for open AI. That, however, is going to do it for today's headlines. Next up, the main episode. If you're building anything with voice AI, you need to know about assembly AI. They've built the best speech-to-text and speech-understanding models in the industry, the quiet infrastructure, behind products like Granola, Dovetail, Ashby, and Cluley.

Starting point is 00:09:44 Now, as I've said before, voice is one of the most important modalities of AI. It's the most natural human interface, and I think it's a key part of where the next wave of innovation is going to happen. Assembly AI's models lead the field in accuracy and quality, so you can actually trust the data your product is built on. And their speech understanding models help you go beyond transcription, uncovering insights, identifying speakers, and surfacing key moments automatically. It's developer first, no contracts, pay only for what you've, use and scales effortlessly. Go to assemblyaI.com slash brief, grab $50 in free credits, and start

Starting point is 00:10:17 building your voice AI product today. If you're listening to this, you already know how fast AI is writing the rules for innovation, disruption, and value creation. And this new era demands a new kind of patent law firm. Landfall IP was built from the ground up to operate differently, orchestrating how human expertise and AI work together for better patents at founder speed, created by world-class patent attorneys who saw a better way, Landfall IP lets AI execute the repeatable while attorneys elevate to create the exceptional. Landfall isn't adapting to AI. They were built for it. Have a new idea? Try the Discovery Agent for free.

Starting point is 00:10:52 It's a confidential tool that helps innovators synthesize their inventions and instantly see patentable insight. Visit landfallip.com to learn more. That's landfallip.com. If you're using AI to code, ask yourself, are you building software or are you just playing prompt roulette. We know that unstructured prompting works at first, but eventually it leads to AI slop and technical debt. Enter Zenflow. Zenflow takes you from vibe coding to AI-first engineering. It's the first AI orchestration layer that brings discipline to the chaos. It transforms free-form prompting into spec-driven workflows and multi-agent verification, where agents actually cross-check each other to prevent drift. You can even command a fleet of parallel agents to implement

Starting point is 00:11:34 features in fixed bugs simultaneously. We've seen teams accelerate delivery 2x to 10x. Stop gambling with prompts. Start orchestrating your AI. Turn raw speed into reliable production-grade output at zenflow.3. Today's episode is brought to you by Super Intelligence. Super Intelligent is a platform that very simply put is all about helping your company figure out how to use AI better.

Starting point is 00:11:57 We deploy voice agents to interview people across your company, combine that with proprietary intelligence about what's working for other companies, and give you a set of recommendations around use cases, change management initiatives that add up to an AI roadmap that can help you get value out of AI for your company. But now we want to empower the folks inside your team who are responsible for that transformation with an even more direct platform. Our forthcoming AI Strategy Compass tool is ready to start to be tested. This is a power tool for anyone who is responsible for AI adoption or AI transformation inside their companies. It's going to allow you to do a lot of the things that we do at Superintelligent, but in a much more automated, self-managed

Starting point is 00:12:32 way and with a totally different cost structure. If you are interested in checking it out, go to AIDailybrief.ai slash compass, fill out the form and we will be in touch soon. Welcome back to the AI Daily Brief. Today we were talking about Google Gemini's big upgrade that they are calling personal intelligence. Yesterday, they announced the very obvious and yet very useful ability to connect Gemini with all the information from other Google apps that you interact with, like Gmail,

Starting point is 00:13:00 photos, search, YouTube, all of course in an effort to help make Gemini more personalized for the individual user. What's interesting is that I believe that it. at core, you can view almost every single move being made in and around consumer AI as in some way a battle for personal context. So let's look at what I mean. Big news from earlier this week was the announcement of Claude Co-work. It's basically Claude code, but simplified in a way that it's designed for non-technical users. You don't have to deal with the terminal anymore. It lives right inside your Claude Desktop app, and it allows you to do the types of things that people have been

Starting point is 00:13:33 using Claude Code for outside of coding. Now, the big thing that has made Claude Code and now ClaudeCod co-work powerful is that it has access to a unique set of context, which is the stuff on your desktop. What makes it different than just the Claude Chat window or the ChatGPT window or the Gemini window is that instead of having to upload the context that's relevant for any particular thing you're trying to do, you just point it at the relevant part of the computer. Now, of course, in addition to having that better context, co-work and Cloud Code can also do things and interact with your desktop, making it more agentic, but that power comes from its ability to access everything on your computer. And yet, even with you,

Starting point is 00:14:08 With that, a lot of the issues that people have discussed when it comes to Claude Co-work over the last few days, which admittedly are more likely having to do with the fact that it was built in the 10 days previous isn't around connecting other types of context. While Claude Co-work and Cloud Code have access to what's on your machine, if you live in the modern world, there's going to be lots of other data sources and places where your data lives that are not just on your desktop. And for that, Cloud gives you access to things via what they call connectors. Connectors are ways to link things like Google Drive, obviously powered by the model

Starting point is 00:14:38 context protocol, and in the first couple of days after Claude Co-work went live, a lot of people's challenges have been in and around making those connectors work. The point being in some ways that we are so hungry for personal context that just having access to our full computers isn't enough, we still need access to everything that exists on the web as well. So, okay, we've repositioned Claude Co-work and Claude Code as powerful because of the way they give you unique access to your desktop context. How are the other things that AI companies are launching right now also in some way about this battle for personal context. I would argue that when it comes to chat GPT, a huge anchor to their strategy has always been to try to leverage the fact that because chat GPT was many people's default,

Starting point is 00:15:16 it has a huge amount of personal context in the form of past chats. And when you view everything in the battle for personal context, all of a sudden, open AI strategy, to add more and more applications all of the time with an incredible shipping velocity, starts to make a little more sense. They are trying with each new app release to get more personal context, which makes the switching costs of leaving and going to another AI service more and more costly in terms of that lost context. For months now, folks have been talking about how memory is the next big moat, and I think that that's dead on. Now, bringing it back to things that have been released recently, so far from OpenAI, the biggest

Starting point is 00:15:50 product that we've got in January is the introduction of ChatCHIPT Health. It's a dedicated health experience inside the app whose entire purpose is to collect a huge amount of personal health context and organize it in a single place that makes it accessible to the AI. In their announcement post, they wrote, Today, health information is often scattered across portals, apps, wearables, PDFs, and medical notes, so it's hard to see the full picture,

Starting point is 00:16:12 and people are left to navigate a complex healthcare system on their own. Now, as they point out, people are already using chat GPD to help navigate all this, but now they're allowing you to port all of that context in. And they are really trying to pull that health context from everywhere it lives. Just a few days later, we got Anthropics' answer to that in their Claude for Healthcare. A big part of that Claude for Healthcare announcement

Starting point is 00:16:33 was about connecting personal health data. The announcement came with a bunch of new connectors rolling out specifically for that type of personal context. I would even argue that Grock's big play, outside of having Elon for fundraising and for building the biggest supercomputers in the world, is once again around personal context. The unique personal context that Grock has access to

Starting point is 00:16:52 is everything that happens in and around X slash Twitter. Which for those of you who aren't on X slash Twitter might not seem like it matters, but for those of us who are and who have been for a very long time is a very significant part of personal context. Okay, so now you're starting to see all of these different moves through the lens of personal context, but Google's latest announcement is in some ways the clearest yet.

Starting point is 00:17:13 Yesterday, CEO Sundarpa Chai tweeted, answering a top request from our users, we're introducing personal intelligence in the Gemini app. You can now securely connect to Google apps for an even more helpful experience. Personal intelligence combines two core strengths, reasoning across complex sources and retrieving specific details,

Starting point is 00:17:28 e.g. from an email or photo to provide uniquely tailored answers. It's built with privacy at the center, and you choose exactly which apps to connect, with the connected app settings off by default. Some of the examples that Google gives about how this might be useful are really concentrated on day-to-day life. This is not about work. In their announcement thread, they wrote, Ever need to buy parts for your car but don't have the info handy? Ask Gemini to recommend tires for my car.

Starting point is 00:17:51 By referencing connected apps like Gmail and photos, it can understand your car's make and model and even the types of trips you take, to give recommendations of tires and info like your license plate number, to make your visit to the auto shop go more smoothly. When a user asks for recommendations around travel, instead of it being generic lists, the specific travel dates that can be found in Gmail, plus other evidence, like in their example,

Starting point is 00:18:09 your love for nature photography found in Google Photos, lead to more personalized recommendations. People's first instinct was that this was a big deal, and that in many ways it was inevitable, but kind of a killing blowplay from Google. AI YouTuber Matthew Berman writes, Gemini will now be my daily driver AI for the next few weeks, all because of personal intelligence.

Starting point is 00:18:27 Google would have never allowed this kind of featured a release just 18 months ago. They would have been too nervous, too much red tape. But now they got out of their own way and allowed users to choose. Google is so well positioned to win AI. Apple, where you at? Akash Gupta writes, Google just reveal the AI moat nobody can replicate. Every AI company is racing to build memory and personalization. Google connects to a decade of your Gmail threads, every photo you've ever taken, your complete YouTube watch history, and every search query you've made since 2005. The question for every other AI company, how do you compete on personalization when your competitor has the user's entire digital life and you're starting from

Starting point is 00:19:00 a blank conversation. I think there are a couple answers to this. First of all, I do think it's important to note that while it does seem obvious that this would make AI better for a variety of use cases, I don't think we yet have enough evidence to know exactly the full complexity of the way that AI gets used over time. To be clear, I am far from the average consumer and user of AI. And yet, I do represent a type of user of AI, and I couldn't care less about this. I tried. For my work-related use cases, I care about the quality of AI strategic thinking, its ability to process and articulate multiple angles around the same decisions, how good it is at accessing other types of data, how good it is at analyzing types of data I give it access to,

Starting point is 00:19:40 how good it is at building the things that I need. There's not a universe in which I'm switching models because I can get better travel recommendations or need a shortcut way to figure out what my license plate is. And to be clear, this is not at all a knock on these new features from Google, nor an argument that I'm anywhere near the normal consumer. My point is solely that when it comes to these big, bold claims that Gemini is killing everyone because of this, I think there's going to be a lot of types of different AI users, all of whom have different types of priorities. Still, let's assume that this type of personalization is really valuable for many, if not most consumers. Well, another path is to ask who else has access to that data,

Starting point is 00:20:14 which brings us back to Matthew Berman's question, Apple, where are you at? When Apple announced Apple intelligence way back when, it was all with this same argument. The pitch was simple, helpful day-to-day use cases that took advantage of the context that Apple had about you because it powers all of your devices. Now, obviously, it has not delivered on that promise. One of the big takeaways after Google I.O. last year, in fact, was that Google had basically shipped everything that Apple's AI wanted to do. And now, of course, Gemini is going to actually power Apple intelligence. And yet, Apple still does have an enormous amount of personal context that others don't have. Google, for example, does not have your iMessages. And for iPhone users, iMessages tend to represent

Starting point is 00:20:55 dozens of gigabytes of personal context that is extraordinarily valuable. And frankly, when it comes to a personal level, more valuable for many use cases than the stuff that's in your Gmail. Apple also has something else, ownership of devices that operate in the physical world. And I think when you start to view everything through the lens of this battle for personal context, OpenAI's hardware decisions start to make a little more sense. Hardware allows them to go after a very specific type of personal context, which is the personal context of how you interact in the physical world. One thing that Apple did last year that did capture people's attention was the new live translation feature they announced for Apple AirPods. Unlike many other form factors for AI devices,

Starting point is 00:21:35 AirPods are something we already interact with. It's not at all weird or abnormal to talk to someone who has AirPods in. And so to the extent that AirPods can become a starting point for AI to interact with your physical experience, it could unlock a whole additional set of that personal context. This is why it wasn't all that surprising when we found out that it seems like at least one of the form factors that OpenAI and Johnny Iver are exploring is something at least tangentially related to an AirPods. Make no mistake about it, Google giving Gemini access to all of this information is a major inflection point and a major upgrade in their positioning when it comes to the consumer AI race. But it's still early innings and a lot of battles yet to be fought and a lot of personal

Starting point is 00:22:12 context that still needs to be organized. For now that that is going to do it for today's AI Daily Brief. Appreciate you listening or watching as always. Until next time, Peace.

The AI Daily Brief: Artificial Intelligence News and Analysis - AI's Battle for Your Context

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.