Should Americans Get Shares in AI Companies?

Today on the AI Daily Brief: As OpenAI and Anthropic race towards IPO, should AI be a public good? Before that, in the headlines: a new NVIDIA chip means the Mac M Series has some competition. 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 KPMG, Scrunch, Section, and OutSystems. To get an ad-free version of the show, go to patreon.com/aidailybrief, or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors@aidailybrief.ai. And honestly, if you want to find out anything else about the show, you can probably find it at aidailybrief.ai as well. Today we kick off some news from NVIDIA, and honestly, it's another reminder of just how much the company is doing, even though the context in which we talk about them is mostly just their core product of chips. On Monday, the company held their GTC Taipei event, with the headline reveal being a new chip called the RTX Spark. While Nvidia billed it as a superchip, the RTX Spark is the first of their standalone prosumer-grade CPUs. The chip will feature 20 CPU cores married to over 6,000 integrated GPU cores, supporting up to 128GB of unified memory. The chip is capable of delivering 1 petaflop of AI compute, which by comparison, an H100 outputs around 4 petaflops. Nvidia said that the chip will be available in Windows PCs and laptops by the fall, with models available from Asus, Dell, HP, Lenovo, and Microsoft at launch. Pricing was not announced, but these will be premium devices designed to compete with high-end Mac products and gaming computers that pull double duty as inference workhorses. I saw a lot of people basically saying that this is their competition to the M5 series of Mac computers. Now, in some ways, this is part of a trend and a shift in the compute workload as we prioritize inference. GPUs, of course, have been the core piece of AI hardware for almost a decade, but the CPU is now now having a resurgence. GPUs are increasingly seen as hardware for AI training, while powerful CPUs are better for executing agentic tool calls. Kara Brisky, NVIDIA's VP for GenAI software, said of GPU-powered chatbots, "That era is ending. Agents are the new workload. They will run everywhere from the data center to the edge." Now, in addition to those new machines, NVIDIA CEO Jensen Huang also announced that Vera Rubin had entered full production. OpenAI and Anthropic have already taken delivery of their first units, with plans to scale up into full data center buildouts this year. The VERA-RUMEN nomenclature refers to the CPU-GPU pairing in the chip. VERA is the CPU while RUMEN is the GPU architecture. For the first time for an NVIDIA data center chip, the focus is on the CPU and its ability to supercharge AGENTIC AI. Said Huang: AI agents will be the largest users of computing. VERA is the first CPU designed for that future, built to run AGENTIC AI at hyperscale with extraordinary performance, efficiency, and programmability. Making that comparison that I just mentioned, The Verge argued that the RTX Spark could be the M1 moment for Windows. I.e., until now, Apple's M-series chips have been the go-to for running AI models locally, and now in its 5th generation, the M-series architecture has been utterly dominant. Apple has been the only choice for local inference, and many of us have the Mac Minis to prove it. NVIDIA is looking to replicate that breakout moment and capture a new slice of the market, going head-to-head with Apple for what Huang is calling the personal AI computer. Now this idea of personal AI computing feels to me like it's very likely to be on display throughout the week as Microsoft Build kicks off. Microsoft CEO Satya Nadella used the RTX Spark announcement as a kickoff, tweeting that their goal at Microsoft was to deliver, quote, "unmetered intelligence to every home and every desk with Windows." Now staying on hardware for a minute, Meta is apparently joining the AI hardware competition with a new pendant. The Information reports that Meta plans to begin testing the pendant over the next year as part of a broader AI hardware strategy. A leaked memo described a push into business-focused devices, which they are calling Wearables for Work. The core strategy, however, is to use wearables as the hook to increase use of Meta's AI models and drive consumer agent subscriptions. Now, it is worth noting that Meta is coming at this competition from a slightly different place, considering that the Meta Ray-Bans are the most popular AI device on the market at this point. Obviously, AI pendants are not a going concern for most people, but it appears that Meta wants to ensure that they have a product available just in case, preempting new devices from Google and OpenAI and forming something of a natural conclusion of Meta acquiring AI pendant startup Limitless at the end of last year. This also could just mark a shift in revenue strategy for Meta's beleaguered Reality Labs division. The division behind their metaverse efforts continues to bleed money even with the success of the Meta Ray bands. Last quarter, the division produced $4 billion in operating losses on revenue of $402 million, but Meta hopes the combination of useful consumer agents and new devices will drive new AI subscription revenue. In the memo, VP of Wearables Alex Himmel wrote, "To build a sustainable business beyond hardware margins, we need to monetize the software experiences that differentiate our devices." It has actually been some time since we talked about AI wearables, and one of the things that I'm watching most closely for on that front is whether all those efforts fall for OpenAI specifically in the category of SideQuest that they are now trying to avoid, or whether that's still an area that they really plan on competing. Now, one more story on the Meta front. The company also just suffered a massive exploit, which many are blaming on AI. On Monday, numerous Instagram accounts were hijacked, including the Obama White House and Sephora. Users who had their account stolen said that they were unable to reach a human tech support worker. Back in March, Meta announced that they would be rolling out AI support to all accounts across Facebook and Instagram to carry out routine tasks like password requests. However, the system appears to have some pretty significant flaws, and over recent days, videos have been circulating on Telegram exploiting the exploit. An attacker can simply ask Meta's AI to link any arbitrary account to a new email address when requesting a password reset. For verified accounts, the AI bot will ask for a video of the person to prove liveness, but hackers found that an AI-generated video of the account owner would pass the checks. Hackers also needed to use a VPN to spoof the correct location, which became trivial when Meta added location data to Instagram profiles. Two-factor authentication was completely bypassed, and many didn't notice anything was amiss until their account was gone. Commentators are fairly baffled by the misstep. In a series of tweets, Gurgliorose writes, "It's wild how Meta, a company going all in on AI, somehow missed the memo on how AI can generate images and videos that renders take-a-selfie verifications utterly useless," seemingly confirming everyone's fears about over-reliance on AI and under-reliance on real humans. He later added, "I'm hearing Instagram's trust and safety org was absolutely gutted over the last few weeks, with 60% of or gone between layoffs and forced reassignments to data labeling, all while AI maxing pushed a bunch of bugs to production. Apparently this was not a sophisticated hack, but engineers at Instagram going overboard to use AI for everything and having no incentives for stuff like security. You get what you incentivize. A warning for any company wanting to copy Meta, added Jeffrey Emanuel. If Meta can't manage agents in an acceptable way in their own infrastructure, how could they possibly expect anyone else to want to use any of their stuff? Next up, we have the latest story in our summer slowdown series. Management consulting firm Bain Company has warned that a lack of AI ROI should be making executives nervous. That's their framing, by the way. In a new survey of large companies conducted in April, Bain found that cost savings from AI automation are falling short of projections. Almost 40% of companies reported that measured AI cost savings were below 10%, despite targeting between 11% and 20%. The survey found a big disconnect between the use cases management were targeting and the realities on the ground. And one of the interesting wrinkles Bain found is that 44% of companies were cash flowing the next leg of AI investment on the basis of assumed cost savings, meaning that if those cost savings weren't materializing, that was going to create problems downstream. They wrote, self-funding the next wave from past returns sounds like discipline. In reality, it's a circular bet with a structural leak. Now, some of the big issues that Bain found in terms of what was going wrong for AI deployments included 41% of companies saying that there were issues around data access or data integration, with more than 25% of respondents also flagging concerns including compliance issues, competing business priorities, and skills gaps. Meanwhile, over at Walmart, the company is limiting their employees' use of AI tools after surging demand. In the latest story showing the shift to the token shortage era, excess demand from employees has caused Walmart to end their unlimited token policy for their core agentic tool called Code Puppy. Code Puppy is a cowork-style agent useful for tasks beyond coding, including preparing presentations and working with spreadsheets. Workers now have a token budget, although sources didn't indicate what the new token limit is. Now, a Walmart spokesperson told Bloomberg that the company still wants its employees to use AI, but is now providing additional training to help help people be more efficient in the way they use AI, but expect to see a lot more of this end of unlimited token policy as Agendix-style use cases come online. That's a story that we will continue to watch. However, for now, that's going to do it for the headlines. Next up, the main episode. One of the most important AI questions right now isn't who's using AI, it's who's using it well. KPMG and the University of Texas at Austin just analyzed 1.4 million real workplace AI interactions and found something surprising. The highest impact users aren't better prompt engineers. They treat AI like a reasoning partner. They frame problems, guide thinking, iterate, and push for better answers. And the good news? These behaviors are teachable at scale. If you're trying to move from AI access to real capability, KPMG's research on sophisticated AI collaboration is worth your time. Learn more at kpmg.com/us/sophisticated. That's kpmg.com/us/sophisticated. Quick question: when was the last time you actually visited a website to research something? If you're like me, AI pretty much does that work for you now. That of course raises a new question for brands: if AI is doing the discovering, researching, and deciding, who or what is your website really for? That shift in user behavior—the rise of AI bots becoming your most important new visitors—is what my sponsor Scrunch is taking head on. Scrunch is the AI customer experience platform that helps marketing teams understand how AI agents experience their site. Where they show up in AI answers, where they don't, and what's preventing them from being retrieved, trusted, or recommended. And it's not just visibility. Scrunch shows you the content gaps, citation gaps, and technical blockers that matter, and helps you fix them so your brand is found and chosen in AI answers. Now for our listeners, Scrunch is providing a free website audit that uncovers how AI sees your site, where there's gaps, and how you're showing up in AI versus the competition. Run your site through it at scrunch.com/aidaily. Here's a harsh truth: your company is probably spending thousands or millions of dollars on AI tools that are being massively underutilized. Half of companies have AI tools, but only 12% use them for business value. Most employees are still using AI to summarize meeting notes. If you're the one responsible for AI adoption at your company, you need Section. Section is a platform that helps you manage AI transformation across your entire organization. It coaches employees on real use cases, Tracks who's using AI for business impact and shows you exactly where AI is and isn't creating value. The result? You go from rolling out tools to driving measurable AI value. Your employees move from meeting summaries to solving actual business problems. And you can prove the ROI. Stop guessing if your AI investment is working. Check out Section at sectionai.com. That's S-E-C-T-I-O-N-A-I.com. This episode of the AI Daily Brief is brought to you by OutSystems, a leading agentic systems platform built for the enterprise. Organizations all over the world are building, orchestrating, and governing agentic systems on the OutSystems platform, and with good reason. OutSystems' open and unified platform allows teams to architect, deliver, and scale governed agentic systems with agility. Teams of any size and technical depth can use OutSystems to build, deploy, and manage AI apps and agents quickly and cost-effectively without compromising reliability and security. With OutSystems, you can rapidly launch ideas from concept to completion. It's the leading agentic systems platform that is unified, agile, and enterprise-proven, allowing you to accelerate growth, reduce operational friction, and deliver real enterprise impact with AI. OutSystems. Build your agentic future. Welcome back to the AI Daily Brief. The question we're exploring today is, in short, the right way to cut the public into the spoils of AI. Now, the broader theme going on is the market stakes and implications of AI going up and up and up. And the resulting jockeying for opinion when it comes to the right policy and discussions of how people can participate. Now, of course, AI's role in the markets is not a new theme. In fact, basically since the launch of ChatGPT, AI has been the recurring theme that has kept markets afloat throughout every other chaotic thing that has happened. And now, with a raft of very high-profile IPOs coming up, the discussion of AI in markets is reaching its loudest point ever. To kick off this week, we got an announcement that Anthropic had officially joined the IPO race, filing their paperwork with the SEC on Monday. Like SpaceX before them, Anthropic filed their draft prospectus confidentially, meaning we won't get a look at the company's audited financials until much later in the process. Now, much was made about the choice to keep the filing confidential, but this has at this point been the standard playbook for IPOs for over a decade. At this stage, we don't know things like how the company will be valued, how much stock they plan to sell, and in terms of timeline, the SpaceX IPO is the only real comparison for a company of this size. SpaceX is expecting to list next Friday, which is a little over 10 weeks from their initial filing and is quite fast for an IPO to go off. Reports suggest that Anthropic is seeking a similarly speedy launch, with some even speculating that the company might try to go out this summer. Axios business editor Dan Primack writes, Anthropic filing confidentially now seems to put it on a path to go public well before Labor Day, or at least gives it the optionality. Big companies rarely price into summer vacations, but this is already an outlier for so many reasons. Now, for market commentators, the specific date is less of a question than whether Anthropic gets out ahead of OpenAI or whether Altman can go public first. The Wall Street Journal previously reported that OpenAI's filing was expected within days, but that was 2 weeks ago and we haven't heard anything since. During an interview on Monday, Sam Altman didn't seem to be in any particular rush. Asked if there was a race to go public, he responded, I don't think— no, not for that. I think there is a race to deliver the best technology and build the best business. Going public is a financing event, and I don't think that's one we're focused on the timing of. We'll do it when we think it makes sense. Now that has not stopped the financial press from painting this as a high-stakes race between the two companies. Senior IPO strategist at Renaissance Capital, Matthew Kennedy, said, "The bankers are telling them that the time is right. Whoever goes first will be able to set the tone, and whoever goes second could look like an also-ran and be ultimately forced to compare itself with the other one in the marketing discussions." Others had a different view, however, with Harrison Rolfs of PitchBook commenting, "For OpenAI, the conventional read is that Anthropic just seized the narrative advantage by filing first. The unconventional read is that OpenAI got the better end of this. Anthropic just volunteered to absorb all the Closure risk first, and OpenAI now has a free option to watch how institutional investors react to audited Frontier AI financials before committing to its own price. Look, I've said this before and I will continue to beat this drum. I think that the IPO raceness of all of this is largely for the sake of financial headline writers. In pretty much the same way that I think that every token that either of these companies makes available is going to be bought for the foreseeable future, I also think that every stock share that either of these companies gives people access to will be bought in just as short order. And while there may be nominal narrative advantages or disadvantages to going first or second, I do not think that the market is going to pick a winner here. I think both of these companies are going to see just absolutely staggering demand. Dan Ives of Wedbush, by the way, had a similar take, writing in his Monday note, we believe this represents an opening of the floodgate for the IPO market, which has been relatively dormant for a few years. Now, also in the AI markets, Google has announced plans to raise $80 billion in equity to fund their continued AI buildout. This will be the first time that Google has issued new stock in more than two decades. Meaning that they will be one of the first hyperscalers to force investors to stomach stock dilution in order to continue their CapEx spend. In the press release, Google confirmed that they plan to spend $190 billion this year and anticipate a significant increase for 2027. Now, over the past year, we've seen a transition as hyperscalers move from spending cash on hand, i.e., ending buybacks and diverting profits into the infrastructure buildout, to start to begin to tap the debt markets, with both Google and Meta issuing corporate bonds in record numbers last year, to now moving into this equity phase. Now, at this point, Google still has plenty of borrowing capacity, but they presumably want to take advantage of recent increases in their stock price. Their stock is up 18% year-to-date, with most of the gains coming in the past 2 months. Sources said that executives see a protracted period of AI investment and want to diversify funding sources while keeping balance sheet flexibility. The market, for their part, seemed pretty ambivalent about the news, with Google falling then recovering to basically flat in overnight markets. One market participant that was enthusiastic about the plans was Berkshire Hathaway, who signed up for a $10 billion allocation from the new issuance. Warren Buffett has been notoriously slow on tech, failing to make any meaningful allocation until purchasing Apple stock in 2016. But this tranche of Google stock would take Berkshire's holdings to $32 billion. That would make Google a top 5 holding, representing around a tenth of their portfolio. Sources said that the deal was hashed out over a 24-hour period and will be the largest bet so far from new CEO Greg Abel after he took over from Buffett in January. Now, while most of the market may so far be in wait-and-see mode when it comes to this Google deal, the AI trade overall is heading into overdrive. According to the Wall Street Journal, the S&P 500 S&P 500 has just delivered one of the strongest 2-month stretches in modern history. The index is up 16% since the beginning of April, which is the 5th strongest 2-month run since the 1950s. Now, this moment of strength is not like many of the previous recoveries coming out of a market crash, but instead is almost entirely about semiconductors going on an absolute tear. The US Semiconductor Index is on pace for its strongest quarter in history, gaining 69% over the first 2 months of the quarter. Unsurprisingly, this has resurfaced the bubble question. Skeptics point out that semiconductors are notoriously cyclical, But others like Citrini Research point to structural shortages in the entire AI supply chain as reasons for people to be less skeptical of this rally than they might otherwise be. What's clear from all of this is that the financial stakes of AI are extremely high, and that realization seems to be finding its way into the policy discourse as well. Last week, we discussed Elizabeth Warren's op-ed in Time magazine about taxing AI, and I specifically drew a contrast between the data center moratorium, shut it all down type of policy, and the cut everyone in through taxation type of policy. Well, apparently data center moratorium leader Bernie Sanders has decided that if we can't shut it down, he wants a stake, or more specifically, he wants the federal government to have a stake. In an opinion piece for the New York Times, Sanders has basically begun advocating for partial nationalization of the AI industry. In the piece, he writes, the question is not whether AI will change the world. The question is who will own and control that future, who will benefit from it, and who will be hurt by it. Will AI be used to make life better for working families, or will the future of humanity be determined by a handful of billionaires who have promoted and developed AI with virtually no democratic input, who stand to become even richer and more powerful than they are today? That is the choice before us. Now, in advocating that the government take a 50% stake in the Foundation Labs, Sanders is basically arguing that AI models are built on data theft. He wrote, the creative work of millions of people has essentially been stolen by some of the wealthiest people in the world. It's time for us to reclaim it. Since AI is built on the collective knowledge of humanity, the wealth it generates must benefit humanity. Sanders said that he will soon introduce the policy in Congress through the AI Sovereign Wealth Fund Act, which, according to Sanders, will give the public a direct ownership stake in major U.S. companies. In fact, he wrote, it would create a sovereign wealth fund through a one-time 50% tax, not on the profits of OpenAI, Anthropic, XAI, and other companies, but paid with something far more valuable than that— the stock. Sanders argues the bill would achieve two crucial things. One, giving the public a direct role in determining the future of AI via the government's voting shares and 50% control of the board, and also two, quote, guaranteeing that the trillions of dollars potentially generated by AI are used to improve the lives of all of us, not simply make the richest people in the world even richer. Referencing the Alaska Oil Fund, Sanders suggested that the fund should begin by making direct dividend payments to U.S. citizens and then later be used to fund a, quote, decent and dignified standard of living, including healthcare, education, and housing. Now, I think when it comes to this type of policy, you have to look at it in a few ways. First of all, I don't think that Bernie Sanders is particularly in the business of the Trumpian art of the deal where he's just trying to start the negotiations really high so that he can get a compromise at a lower part. In other words, I think that this 50% number is the number that he thinks is fair. I also think that while the government expropriating 50% of the stock of a set of extremely important private companies might have been anathema in previous periods, right now in our times, with discontent where it is, all bets are off on what the public will tolerate. Still, I think that practically, the idea of AI as a public good is one that might find some political resonance. For one thing, this is part of the discourse coming out of the labs. OpenAI's April white paper on industrial policy called for a, quote, public wealth fund that provides every citizen with a stake in AI-driven economic growth. Last October, Anthropic wrote, sovereign wealth funds could enable states to acquire positions in AI-related assets, In scenarios where the AI sector captures an outsized share of economic wealth, government investment could both shape the sector's behavior and AI-derived wealth more equitably. I think there's also an emerging strand of the discourse that's going to be a lot more politically palatable for folks that's still exploring some similar themes. That idea, as captured in a recent Ezra Klein op-ed, is about how to distribute AI itself, not just the financial benefits from AI, but AI itself as a public good. Klein writes, AI's benefits will not emerge automatically or inevitably. It will take work to identify the problems AI can help the public solve and create the data, financing, and compute needed to actually solve them. A public agenda for AI needs to be more than a vague intention to toss AI at public problems. It starts with access, but it does not end there. He concludes, if we want an AI that serves the public good, we need to define the public goods that AI can serve and create the conditions under which AI can be useful. We know we fear what AI will do to us, but what do we hope it will do for us? I don't think it's an accident that the market discourse and IPO questions are happening at the same time as this growing public policy discourse. And frankly, while I'm not particularly keen on the specifics of any of these policies that have been put forward so far, I like the trajectory at least of the questions that Ezra is asking here about what type of positive benefits we want from AI and what's the best way to achieve that. I'm even seeing Bernie's extremely socialistic proposal generating some interesting counter responses that retain the principle of a broader cross-section of society having a financial upside in the success of AI without all of a sudden the government being in the business of administrating the most important companies in the world. Look, ultimately we are in uncharted territory, and the discussion is going to do nothing but get weirder before it lands. For now, however, that is going to do it for today's AI Daily Brief. Appreciate you listening or watching as always, and until next time, peace!