AI's Battle for Your Context

0:00Today 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. Alright friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Assembly, Landfall, Zencoder, and Superintelligent to get an ad-free version of the show, go to patreon.com slash AI Daily Brief or you can subscribe on Apple Podcasts, if you are interested in sponsoring the show. You can set us a note at sponsors at aidelebrief.ai and finally also at aidelebrief.ai 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

1:02around 5 minutes. 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, contrary to my base case, that neither OpenAI or Anthropic ultimately go public in 2026, the New York Times finds a lot of evidence that they are getting ready. They wrote, andthropic in 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 an premium for the public offering, and we can easily see multiple trillion dollar IPOs this year. That is extraordinarily rare. The only real comparison at those levels are the $1.7 trillion valuation for the Saudi Ramco IPO in 2019. No tech startup has ever come close. Morgan Stanley's Eddie 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

2:04and the investor interest. Now, Maloy 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. shareholders 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, 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, and was also seen as

3:06an 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 capitals, 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. My argument for why I didn't think that open AI and anthropic would ultimately go public this year is a public market reporting as 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 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

4:07course, 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 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 anthropic's largest customers over recent months. As of July last year, Microsoft began using anthropic to power coding agents in GitHub co-pilot, but the big shift began in September when open AI and Microsoft agreed to the emicable end of their exclusive partnership. Microsoft quickly announced they would add support for anthropic's models within their co-pilot products. The new multi-model version of co-pilot routes each task to the most appropriate model, and for many of the tasks in Microsoft's productivity suite, 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

5:07in agent mode for complex Excel tasks, although why the hell anyone's using 40 is beyond me, while the super long context window of Claude Opus 4.1 is being used for mass summarization and analysis tasks. High Coup 4.5 is also seeing heavy use due to its 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 anthropic 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, andthropic will reportedly work with Microsoft to develop new cloud power features for co-pilot over the coming months. A liquid on Twitter said what I think a lot of people feel, andthropic 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 worth of AI inference

6:09compute. A press release said that OpenAI planned to integrate cerebris's chips into their broader computing network to provide faster response time. Cerebris 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 cerebris's 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. Those 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 Grocker cerebris, they are 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 100 times faster. Now, lastly today, we stay on OpenAI but move to some serious industry psychodrama. A trio of leading AI researchers are returning to OpenAI amid allegations of corporate espionage On Wednesday night, we had dueling tweets.

7:10Former OpenAI CTO and now CEO of Thinking Machines Labs, Mirror Morati, wrote, �We have parted ways with Barrett's Oath. Sumith Gentala 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. 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's Oath, Luke Metz, and Sam Schoenholz back to OpenAI. 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, more to come on what they�ll focus on soon.� Now by way of background, these three left OpenAI in late 2024 alongside CTO Mirror Morati as part of a mass exit as of talent. They were pivotal in the subsequent founding of Morati's Thinking Machines lab. Zof 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. CTO first joined OpenAI in 2022 to serve as their VP of research. Prior to that, he was at Google DeepMind for six years.

8:11At OpenAI, he built the post-training team from scratch with John Schullman, who also left a 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. Metz Twitter poster signal wrote, �So like Thinking Machines completely imploded today? Someone DM me the T please?� And yet at the same time, adding to the intrigue, Kylie Robinson of Core Memory reported the story with a different twist, writing, �Thinking Machines has terminated its CTO bear itself due to unethical conduct according to two sources familiar with the matter. CEO Miramarati announced the news that an all-hands with employees today. Max F. 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 told Thinking Machines CEO Miramarati on Monday he was considering leaving. He was then fired on Wednesday.

9:12Simo went on to write that OpenAI doesn�t share the same concerns about Zof as Miramarati. 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 got to think it was a good day for OpenAI. 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 cluely. 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. Its developer first, no contracts, pay only for what you use, and scales effortlessly. Go to assemblyai.com, slash brief, grab $50 in free credits, and start building your voice

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11:19It�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 features in fixed bugs simultaneously. We�ve seen teams accelerate delivery to x to 10x. Stop gambling with prompts. Start orchestrating your AI. Turn raw speed into reliable production-grade output at zenflow.free Today�s episode is brought to you by super intelligent. Super intelligent is a platform that very simply put is all about helping your company figure out how to use AI better. 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.

12:21This 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 super intelligent, but in a much more automated, self-managed 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 AIDailyBrief. Today we are 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, 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 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 Clawed Co-Work.

13:23It�s basically Clawed 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 Clawed Desktop app, and it allows you to do the types of things that people have been using Clawed Code for outside of coding. Now the big thing that has made Clawed Code and now Clawed 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 Clawed 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, Clawed 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 that, a lot of the issues that people have discussed when it comes to Clawed Code 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 Clawed Code and Clawed Code have access to what�s on your machine, if you live

14:25in the modern world, there�s going to be lots of other data sources in places where your data lives that are not just on your desktop. And for that, Clawed gives you access to things via what they call connectors. Connectors are ways to link things like Google Drive, obviously powered by the Model Context Protocol, and in the first couple of days after Clawed Code 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 Clawed Code work in Clawed 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, 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

15:28velocity 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 open AI, the biggest product that we�ve got in January is the introduction of chat GPT 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. And 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, and people are left to navigate a complex health care system on their own. Now as they point out, people are already using chat GPT to help navigate all this, but now they are 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 answered to that in their Cloud for Healthcare.

16:30A big part of that Cloud for Healthcare announcement 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 Grox 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 Grox has access to 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 are starting to see all of these different moves through the lens of personal context, but Google�s latest announcement isn�t in some ways the clearest yet. Yesterday�s CEO Sundar Bachai tweeted, answering a top request from our users were 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, e.g. from an email or photo to provide uniquely tailored answers.

17:32It�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. By referencing connected apps like Gmail and Photos, it can understand your car�s making 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, 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, �Gemin I will now be my daily driver AI for the next few weeks all because of personal intelligence. Google would have never allowed this kind of feature to release just 18 months ago. It would have been too nervous, too much red tape, but now they got out of their own

18:33way and allowed users to choose. Google is so well positioned to win AI. Apple, where you add. A gosh group to writes, Google just revealed the AI mode 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 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 note 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 if 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

19:36is at accessing other types of data, how good it is at analyzing types of data I give it access to, 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. While another path is to ask who else has access to that data, 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

20:38shipped 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. But for example, does not have your iMessages, and for iPhone users, iMessages tend to represent 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, open AI�s hardware decisions start to make a little more sense. Software 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, AirPods are something we already interact with.

21:38It�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 open AI 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 that a lot of battles yet to be fought, and a lot of personal context still needs to be organized. For now that is going to do it for today�s Aideally Brief, appreciate you listening or watching as always, and until next time, peace�