Opus 4.6 and ChatGPT 5.3-Codex Are Here and the Labs Are at War

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, we've got not one but two new models that show exactly where the leading model labs priorities lie. And before that in the headlines, looks like we're going to spend a cool two-thirds of a trillion dollars on AI infrastructure this year. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in around five minutes. We kick off today with Google and Amazon rounding out big tech earnings with a very unified message, AI CapEx is accelerating faster than ever. Both companies lifted CapEx forecast significantly. Google guided AI spending between 175 and 185 billion for this year, vastly outstripping estimates of 115 billion. This level would double Google's already high 91 billion in CapEx for 2025 Amazon, though, came in over the top the following evening guiding 200 billion in CapEx for 2026 for a 60% jump. With Google, Amazon, Microsoft and Meta all lifting expectations, we now have 650 billion in projected AI CapEx for 2026 from just these four. That's now more than the inflation-adjusted cost of the multi-decade US interstate highway project anticipated to be spent in a single year. It's about 2.5 Apollo Moon missions or 4.5 International Space Stations. Now, on the actual earnings, there was a slight divergence in performance. Google reported annual revenue of 400 billion for the first time. They saw an 18% increase in overall revenue year over year, and a 48% jump for their cloud division. Still, Google Cloud was a $17.7 billion business for the quarter, which puts them firmly in third place behind Microsoft, Azure and AWS. At the same time, they recorded by far the fastest growth rate and were the only hyperscaler that increased their pace of growth. Amazon's story was slightly less positive. Net profit was $21.2 billion right in line with expectations. Top line revenue growth was 13.6% for a slight beat, reaching $213.4 billion for the quarter. AWS revenue growth was 24%, their fastest growth rate in three years, bringing division revenue to $35.6 billion for the quarter. While the numbers were fine, they didn't necessarily speak to massive monetization of AI bets, and CEO Andy Jassy spent much of the earnings call justifying the massive ramp up in CapEx. He told investors, I think this is an extraordinarily unusual opportunity to forever change the size of AWS and Amazon as a whole. We see this as an unusual opportunity and we're going to invest aggressively to be the leader. Later in the Q&A section, he pushed back against an analyst who questioned the conviction. Jassy commented, This isn't some sort of quixotic top line grab. We have confidence that these investments will yield strong returns on invested capital. We've done that with our core AWS business. I think that will very much be true here as well. Similar to Microsoft, both Amazon and Google said they were capacity constrained in their cloud businesses. They claim that stronger growth would have been possible if they had more GPUs on racks in 2025 Still, both companies saw a big drop in share price following their earnings calls, with Google falling 6% on Wednesday night and Amazon losing 11% on Thursday night. Now, one interpretation of this is investors being uncomfortable with spending at these levels regardless of AI-derived revenue. But there is also something more going on here that is worth exploring. For decades, hyperscalers have been doing hundreds of billions of dollars in stock buybacks each year, peaking at over a trillion dollars in 2023 Most analysts expect the hyperscalers to reduce or even end buybacks this year. CapEx plans also seem likely to require debt funding across the board for the first time. Steve Goldstein, the Euro Bureau Chief of Market Watch, wrote, It's funny that we had a decade of no stock buybacks are evil, and now that companies are actually ramping up CapEx, it's no, not like that. Quantian summed it up, Investors have officially remembered that doing CapEx means you can't spend money on buybacks and decided they don't like it anymore. Architect pointed out that Stanley Druckenmiller has argued in the past that high corporate CapEx such as spending on factories, inventory and equipment acts on a drag on financial assets because it drains liquidity from the financial system. Now this is a super important point. We tend to think of these investors as sending signals about what they find to be a reasonable amount to spend on AI. But what they really might be saying is not that they necessarily think it's wrong to spend that on AI. They just don't like that it's not there to spend on them. I think we're going to see a lot more of this debate play out. But keep that in mind as you try to interpret markets' reactions to the hyperscalers over time. Speaking of Amazon, the company is considering a deep partnership with OpenAI, including using their models to power Alexa. As previously reported, Amazon is in talks to take part in OpenAI's latest funding round. They are in fact rumored to be considering an investment as large as $50 billion, which would be about half the money that OpenAI is seeking to raise. The information now reports that Amazon isn't just interested in an equity stake or a compute partnership but is looking to get privileged access to OpenAI's tech. Sources said that OpenAI's models could bolster Amazon's AI products, including the Alexa voice assistant, under a proposed deal. The process would require post-training OpenAI models to tune them for Amazon's use cases and would also require OpenAI to supply dedicated researchers and engineers to the process. That could be the hitch as that would obviously divert resources to some extent away from their own ambitions. At this point, I'm not sure how much to make of it, with a spokesperson for OpenAI saying we are focused on our strong existing compute partnership with Amazon. One other little nugget from the earnings report, Gemini has, according to Google, hit 750 million monthly active users. In December, Google said that Gemini's user base had surged from 450 million to 650 million in the final quarter, making this another substantial jump for January. The latest figure we have for OpenAI came from Sensor Tower, with their data showing that ChatGPT had 110 monthly million active users as of November. Now, there is a little bit of a question mark around how some of these companies are measuring user numbers. Meta, for example, claims 500 million monthly users for MetaAI, but that's presumably including quite a few people who stumble across the assistant in Instagram or WhatsApp. Google, however, was clear that these numbers are only counted using the Gemini app. CEO Sundar Pichai said in a statement, the launch of Gemini 3 was a major milestone and we have great momentum. One quick nugget of fundraising news, 11Labs has secured a half billion dollars in new funding at an $11 billion valuation. The round triples 11Labs' previous valuation from their last funding round, which closed in January of last year. In terms of what comes next, it sounds like they're interested in moving into video. Co-founder Matty Stanuszewski said, the intersection of models and products is critical and our team has proven time and again how to translate research into real world experiences. We plan to expand our creative offering, helping creators combine our best in class audio with video and agents, enabling businesses to build agents that can type and take action. Finally, speaking of taking action, a story that deserves way more time than it gets in these headlines, but which I'm sure we will come back to. In addition to the news, which will be the subject of our main episode today, OpenAI also announced a new platform called Frontier. The goal is basically to help businesses deploy AI coworkers. OpenAI writes that it is a new platform that helps businesses build, deploy and manage AI agents that can do real work. Frontier gives agents the same skills people need to succeed at work, shared context, onboarding, hands-on learning with feedback, and clear permissions and boundaries. That's how teams move beyond isolated use cases to AI coworkers that work across the business. Basically, Frontier is a combined orchestration, governance, and optimization platform for OpenAI's agents. It allows users to manage the skills that each agent has access to, share context between agents, and set permissions and boundaries. OpenAI noted that AI leaders across every industry are rapidly rolling out agendic deployments, adding that what's slowing them down isn't model intelligence, but how agents are built and run in their organizations. They noted that the capability gap between leading performance and live deployments is actually growing due to increased complexity around agent governance. Frontier is designed to give a unified platform to control all the things around the AI model that goes into a successful agendic deployment. Context, data access, skills management. Now this is something that we are going to necessarily talk a lot more about, but I just wanted to flag a little bit of commentary around this chart that was flying around Twitter and in particular financial circles. For those of you who are listening, not watching, it's a chart that shows at the bottom your enterprise system of record and then five layers above it. Business context, agent execution and evaluation and optimization right above it, then agents above that and interfaces above that. Investor Gokul Rajaram writes, Check out where systems of records sit in this diagram from OpenAI frontier. At least three, if not four, layers of context and intelligence sit between them and the end business application. It's one of the clearest representations of how AI companies plan to build next-gen systems of action on top of existing systems of record and why the markets are so worried about the future of software companies. Buko Capital put it even more simply, Quite a visual from OpenAI. Your system of record is a dumb pipe and we will layer five rows of value on top of it to steal the relationship and all the economics along with it. No wonder SaaS is in the gutter. Like I said, there is so much more to explore about Frontier, but we have not one but two model releases to talk about, so we are going to close the headlines there and move on into our main episode.