The Race to Put AI Agents Everywhere

**Nathaniel Whittemore** (0:01)
Today on The AI Daily Brief, the race to productize agents and make them enterprise grade is on. Before that, in the headlines, Nvidia CEO says the company is on track for a trillion dollars in revenue. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, we're going to dive right in. But one quick reminder, Agent Madness submissions are live right now. This is our bracket voting competition to find the coolest agents that people in this community have built. If you want a chance to have your agent featured on the show, go to agentmadness.ai. Submissions close very soon, so I encourage you to check it out. Now with that out of the way, let's talk about a trillion bucks in revenue. I'm old enough to remember when a trillion dollar market cap was a big deal. And now here we are, AI is booming, and Nvidia CEO Jensen Huang has kicked off the company's annual GTC conference with a massive prediction that the company will see a trillion dollars in revenue between now and 2027 At every GTC, Jensen's keynote, which is planned but not fully scripted, is the big event. This one was no exception. It was two and a half hours long, totally jam-packed with big announcements. We got confirmation of the new Grok-powered server focused on inference. The new rack-mounted system will combine 256 Grok chips with 72 Nvidia Rubin GPUs, delivering 35 times the inference efficiency of current-generation Blackwell chips, with the system expected to ship in the second half of this year. Jensen also unveiled a new GENAI system that can enhance video game graphics on the fly. Called DLSS5, the technology combines traditional graphics with an AI filter to create stable photorealistic graphics. Being able to produce this effect at runtime on consumer hardware is a big breakthrough that could significantly change the way video games are made. For my Claw fans out there, there is a new entrant into the Open Claw category, which we'll cover in the main episode. But ultimately, while the keynote had many big moments, none grabbed headlines like Jensen's massive revenue forecast. Late last year, Huang said that he expects 500 billion in sales in 2026 On Monday, he doubled the forecast to a trillion, stating, I believe that computing demand has increased by 1 million times in the last two years. It's the feeling that we all have. It's the feeling every startup has. Now, some tried to downplay the forecast, noting that it merely combines two financial years at 500 billion apiece, meaning it's not so much a material change. Bloomberg analyst Kunjan Sobhani wrote, The update should ease fears of a pullback in 2027 as Rubin enters the cycle, although it may also reset market expectations higher and raise the bar again. This feels to me to be slightly missing the bigger picture. Jensen has now signaled that Nvidia can see enough demand to drive 500 billion in annual sales. This would more than double revenue from the past year. In fact, the list of companies with a half a trillion in annual sales is just Walmart and Amazon, with Saudi Aramco falling slightly short. If Huang's forecast is correct, it will be completely unparalleled growth for a company of anywhere near Nvidia's size. Remarking on the event, Josh Cale wrote, Demand doubled his demand forecast to a trillion dollars, announced data centers in space, and closed the show with a robot singing country music. This is Nvidia's world. Everyone else is just renting compute in it. Next up, if it is Nvidia's world, one of the new players in it is of course the Neo Clouds. On that front, Meta has signed a $27 billion deal with Nebius. Nebius, which is similar to Coreweave and NScale, operates smaller AI data centers than their hyperscalar counterparts. This often includes differentiated chips or full-stack support for model training or specialized inference. Nebius's new deal with Meta spans five years, and this is in addition to a $3 billion deal signed by Meta in November. Nebius plans to deploy Nvidia's new Verorubin chips on Meta's behalf. The chips are expected to be available in the second half of this year, with Nebius powering on the new cluster early next year. Now, while it's possible that Meta is turning to Nebius for specialized datacenter management, the simpler explanation is just that the entire industry is capacity constrained right now, and that Meta, like all the other AI labs, is gobbling up all the available datacenters they can get their hands on. That includes partnering with the neoclouds to take any capacity they can offer. The deal, though, also represents a phase shift for the smaller end of the datacenter industry. Nebius is one of the larger neoclouds, yet they only had a little over a billion dollars in revenue last year. Meaning for my math friends out there, this is an order of magnitude larger than all the business they've done so far. AI infrastructure continues to scale up at a massive pace, and the neoclouds seem to be getting their slice of the action. One area of infrastructure buildout that has been a little bit, shall we say, beleaguered is the OpenAI Stargate effort. The company has now appointed new leaders to oversee their revamped and restructured Stargate. Now, over the last couple of months, we've heard all sorts of things about Stargate. We learned that the joint venture with Oracle and Softbank never really got off the ground, and more recently that OpenAI was walking away from expansion plans at the flagship site in Avalene, Texas. That reporting also suggested that the Stargate name would be attached to all data centers operated by OpenAI, rather than only their own site developments. Now the information reports that the structure of the new-look Stargate division has been put in place. Former Intel executive Sachin Khati will oversee the division, which consists of three distinct teams. One team will work on technical data center design, another on commercial partnerships with various cloud providers and chip manufacturers, and the third will be responsible for on-the-ground management of facilities. Previously, OpenAI's infrastructure teams were organized by project rather than role and reported up to President Greg Brockman, meaning this restructuring could represent a more specialized and dedicated in-house team being put in place. Reporting also confirms that OpenAI is less concerned about ownership of data centers and more willing to lease in order to scale up compute. This would comport with basically everything else we're seeing in the industry, where all of the fancy and fiddly efforts are kind of flowing by the wayside in order to just get access to as much compute as possible. Less fun for OpenAI is that they just got sued by a dictionary. Encyclopedia Britannica and their subsidiary Merriam-Webster have sued OpenAI for use of their dictionaries and encyclopedias and training data. Further, Britannica claims that ChatGPT has cannibalized their web traffic by producing content that substitutes or competes. Responding to the lawsuit, an OpenAI spokesperson said, Our models empower innovation and are trained on publicly available data and grounded in fair use. Now for our last topic today, it's actually two stories that both seem to point in a similar direction, which is a change in how open source AI gets developed. The first story is that Alibaba has restructured their AI organization in a shift it seems to maximize profits. Rumors were swirling earlier this month that a big move was in the works as three senior researchers left the Quen team. The departures included technical lead Justin Lin, who is credited with shepherding Quen from its first training run to becoming one of the most popular open source models. Speculation at the time was that Alibaba was shifting focus from pure research to driving AI-related revenue through their first-party API. Some wondered if this shift would herald the end of open source Quen models. According to a memo cited by Bloomberg, the restructuring is now complete. The Quen research team has been folded into a new division that also includes consumer-facing apps and AI-related products like the Quark smart glasses. The new division is called the Alibaba Token Hub and will be directly led by CEO Eddie Wu. Wu wrote in the memo, ATH is built around a single organizing mission. Create tokens, deliver tokens, and apply tokens. I will lead ATH directly with a mandate to drive strategic coordination across our AI businesses, embed AI deeply into how we work, and preserve the agility that lets us move fast. Bloomberg writes that the restructuring, Signals the company's clear emphasis on monetizing AI. The division's name is a direct reference to the units of computing that companies charge users. Meanwhile, another Chinese startup, ZAI, has released a faster, cheaper version of their leading model, but they are keeping it closed source. The new model is called GLM5 Turbo and offers similar performance to GPT 5.2 at a cost that's closer to Gemini 3 Flash. The speed boost is arguably a bigger deal, with the model optimized for running open-claw style tasks like tool use and long-chain execution. ZAI said the model would be released as closed source, but that its capabilities would be folded into future open-source releases. VentureBeat wrote that the decision is emblematic of a broader shift in the Chinese market. They suggest the Chinese labs are adopting an approach where lightweight open-source models are used to boost distribution and generate goodwill among developers, while more powerful models are delivered as proprietary systems aimed at generating enterprise sales.