The AI Daily Brief: Artificial Intelligence News and Analysis - What Should the Government’s Role in AI Be?

Starting point is 00:00:00 Today on the AI Daily Brief, what should the government's role in AI be? Before that, in the headlines, some previews of Nana Banana 2 and a question of whether it's all a part of Gemini 3. The AI Daily Brief has 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, robots and pencils, blitzie, area, and super intelligent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe at Apple Podcasts. And to learn more about sponsoring the show, shoot us a note at sponsors at AIDilybrief.A.I. Lastly, as I have been telling you guys, we are in the midst of our AI ROI benchmarking

Starting point is 00:00:47 study, and we have just hit a major milestone. We have now had people contribute more than a thousand use cases articulating the ROI that they're getting from them. We're starting to see patterns around which categories of ROI are most common, from time savings to new capabilities to new revenue. We're getting a good distribution of small, medium, and large-sized companies. We're going to have the study open for another couple weeks to really try to build the most comprehensive database of ROI rated use cases that exists. And if you want to contribute and get the full report that comes out of that, go to ROISurvey.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 one for all the new

Starting point is 00:01:28 model enjoyers out there. Nanobanana 2 seems to be going through testing at the moment. Now, you I remember how earlier this year, towards the end of the summer, Nanobanana really took over the image generation world. It wasn't necessarily that it was better at raw image generation than other models, but at the fact that it was so much more steerable and that it gave people the ability to edit in a fine grain kind of way. This opened up all sorts of new practical possibilities and made it a really beloved model. While Nanobanana 2 appeared to have been available for a few hours on Media I.O. over the weekend and is giving some very impressive results. A user called Singularity on Reddit showed their testing of generating the solution to a math problem written on

Starting point is 00:02:09 a whiteboard. The text rendering is significantly improved, and the new model was able to generate the correct answer where Nanobanana 1 failed. Singularity wrote, The model is extremely powerful, a huge step up from Nanobanana 1, and this output was extremely impressive to me. Leo on X managed to generate a very convincing Windows 11 desktop, showing a Mr. B's thumbnail on YouTube. Also on X, Roberto Nixon showed that the testing was completely without guardrails, generating a photo of Diddy hanging out with Elon Musk, and a CNN splash screen discussing a Trump third-term prediction. From those outputs, the image model appears to be now photorealistic to the point of being absolutely indistinguishable from reality. SRK Dan showed

Starting point is 00:02:49 the model passing the impossible clock and full wine glass tests, as well as generating a pink ocean and a glass Big Mac with perfect reflections. Gaga from Media I.O. said, on Discord that the model was taken down by Google and that it was only intended for internal testing. However, they noted it performed amazingly well in testing. According to Testing Catalog, the model is slated for release on November 11th, which if true, means we won't have to wait long. They wrote that the new model is notable for its, quote, improved ability to process complex tasks, such as precise coloring, advanced control over viewer angle, and correction of textual elements within generated images. Now, the model seems to draw in elements of Google's reasoning models

Starting point is 00:03:26 as part of an advanced workflow. It spends time planning the output, reviews the initial generation, and iterates to correct errors before presenting a final result. Adding visual reasoning into the workflow seems to allow the model to generate plausible text and accurate math without needing to spell everything out in the prompt. Now, reports were mixed on whether the workflow was based on Gemini 2.5 Flash, or if this will be our first glimpse of Gemini 3.0. The rumor mill is swirling once again that we are finally going to be getting Gemini

Starting point is 00:03:51 3.0 this week. Although some speculate that with the release of Kimi K2-Think, which is the topic that we'll be coming back to a little bit later this week, that we might get a bit of a delay. Next up, a check-in on where markets are as we head into the week. And at least at the moment, it appears the AI trade may be falling out of favor, at least slightly, on Wall Street. A series of tumultuous headlines sent AI stocks tumbling last week. The NASDAQ index overall fell by 3%, which was its worst week since the first set of tariff announcements back in April. The high flyers were particularly hard hit. Palantir was down 13% for the week, Oracle dropped 9.7%

Starting point is 00:04:26 and InVideo was down by 9.6%. The drawdown bottomed out on Friday, but still raised many questions about the sustainability of the AI bet. Jack Ablin, the chief investment strategist at Crescent Capital, said valuations are stretched. Just the slightest bit of bad news gets exaggerated, and good news is just not enough to move the needle

Starting point is 00:04:42 because expectations are already pretty high. Now, we certainly had abundant bad news last week. Open AI executives talking about a backstop, which got translated to a bailout, which we'll talk about a little bit in the main episode, plus Michael Burry of big short fame pounding the table about going short once again. Still, the story was clearly not just about AI itself, but also about the broader economy. David Miller, the CIO at Catalyst Fund, said,

Starting point is 00:05:05 You've had these macro factors that were effectively making some noise for a while, but nobody really wanted to listen. The consumer sentiment numbers and the employment numbers weakening, it's forcing people to look at the bigger picture. Of course, for many on Wall Street, the bigger picture is that they've already had a fantastic year and it's time to start booking profits. The NASDAQ is up 19% year-to-date and an AI-centric portfolio has vastly outperformed. Many portfolio managers will be tempted to cut risk, secure their bonus and book a ski trip, rather than hold out for a few more percentage points to end the year. Stephen Colano, the CIO at Integrated Partners commented,

Starting point is 00:05:36 investors are on edge. Seems like the profit-taking is coming from the things that have run the most since early April, which is AI and anything connected with it. Legendary investor and Professor of Behavioral Economics, Peter Atwater, said, If you watch this week, there's been a decided negative bias to what people are saying about AI. If we see the mood deteriorate, the skepticism should rise, the scrutiny should intensify. And those would be behaviors that ultimately limit the potential of the market to bounce. Now, this is not a macro or a finance show, but I think it's pretty important when we do cover these topics

Starting point is 00:06:04 to also note when there are things going on that are outside of the narrative factors. And the reality is that there have been a lot of things, both narrative-wise and structurally, that have been depressing markets as well. We've been mired in the longest government shutdown for a long time, and there has also been just a ton of macro liquidity receding. For example, there was a ton of stress in repo markets last week that seems to be lifting going into this week, making it pretty interesting that macro factors are being read as AI bubble burst when it's really just a broader correlation. Certainly some don't seem to care. At an event for Goldman Sach's young wealth management clients last month, AI was very clearly on everyone's mind.

Starting point is 00:06:40 Brittany Bowles-Muller, the regional head of Goldman Sachs wealth division for San Francisco, explain the bank's view that AI is not a bubble. Speaking with Fortune after the event, she said, will there be some winners and losers from AI? Absolutely. There will definitely be some places where valuations are overblown, and time will tell where those spaces are. But we do not think we're in a bubble,

Starting point is 00:06:57 and we pay very close attention to that. Now, one big takeaway from surveying the group of wealthy millennial founders and inheritors was that they are already looking beyond the core theme to opportunities for AI-adjacent investments. Energy was a big focus, as the AI infrastructure boom will require a generational investment in U.S. energy production, and clients also apparently want to invest in AI-enhanced health care, including breakthroughs and

Starting point is 00:07:18 diagnostics. Lastly today, whatever's going on with markets, the compute buildout continues. NVIDIA CEO Jensen Huang is asking TSM to boost production to satisfy demand. In comments to the press in Taiwan at a TSM event on Saturday, he said, the business is very strong and it's growing month by month stronger and stronger. He noted that NVIDIA's three suppliers of memory chips have already, quote, scaled up tremendous capacity to support us. TSM, which produces the central GPU chip, seems to be the limiting factor in a supply chain running at full capacity.

Starting point is 00:07:47 Not diplomatic as always, Huang wasn't at all critical about TSM's efforts as a partner. He acknowledged no TSMC, no Nvidia. Still, Jensen said his company is working through a record half a trillion dollar order book over the next year, and they need as much capacity from TSMC as they can get. By all accounts, though, TSMC is already operating at full capacity. CEO, C.C. Way, told employees at a Saturday event that he expects to see record sales every year for the foreseeable future. He acknowledged that Jensen had, quote, asked for wafers, but said the number was confidential. Taiwanese media reported that TSM would be increasing their production of three nanometer

Starting point is 00:08:19 chips by around 50% to reach 160,000 wafers per month. InVedia reportedly will take more than half of that additional capacity as they scale up the delivery of Blackwell chips. So as we kick off this Monday, we've got new models, market mayhem, and the never-ending search for compute. All in all, sounds like a pretty AI start to the week. However, that's going to do it for the headlines. Next up, the main episode. AI isn't a one-off project. It's a partnership that has to evolve as the technology does. Robots and pencils work side by side with clients to bring practical AI into every phase, automation, personalization, decision support, and optimization. They prove what works

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Starting point is 00:11:34 All customized for you. Instead of shopping for hype, you get to deploy with confidence. Visit besupor.ai and book your AI planning demo today. Welcome back to the AI Daily Brief. Today we're following up on the dust-up at hullabaloo surrounding the backstop comments from OpenAI last week and expanding the discussion out to ask what the government's role with AI should actually be. It's pretty clear to me observing this field every day that we are moving into a more intensely political era for AI. Now, part of that is just where we are in the U.S. election cycle.

Starting point is 00:12:12 We have the midterms coming up. And right now in particular, there is a moment of exploration among many politicians to figure out what it is they think potential. voters are going to want to hear, and there are certainly early indications that a more populist economic message is going to be popular. Still, even if it weren't for that, the politics of AI were always inevitably going to come into focus as the technology got more powerful and as we started to see its impacts play out in the world. At the end of last week, OpenAI published a blog post about the next phase of AI, but to properly contextualize it, I actually want to go back to those comments from OpenAI CFO Sarah Fryer and Sam Altman himself that kicked off such a storm last

Starting point is 00:12:48 week. Now, for those of you who weren't paying attention last week, in a conversation at a Wall Street Journal conference, opening eye CFO Sarah Fryer was having a conversation about what she thought the role of government should be in this broader compute buildout with regard also to how it related to geopolitics vis-à-vis China, and she unfortunately reached for the word backstop as a way to describe the government's role. Now, it wasn't just an errant word. She also talked about the U.S. government guaranteeing loans to bring down the cost of capital. And all of this, and all of this, this dovetailed with comments from Sam Altman on a podcast with Tyler Cowan from earlier in the week, where he also talked about the government as the insurer of last resort when it came to

Starting point is 00:13:27 things as big as AI. And as you might imagine, given how contentious a lot of this open AI dealmaking is already and how much skepticism there is in markets that they'll be able to pull off these lofty ambitions, anything that hinted that the company might already be looking for a bailout, even though that was not a term that they used, was enough to send the news editors into overdrive. And as sometimes happens, what was initially a very short statement led to a ton of follow-up words to try to clarify. On Thursday afternoon of last week, Sam Altman tweeted, I would like to clarify a few things, which ended up being a thousand word tweet.

Starting point is 00:14:04 Altman started, first the obvious one. We do not have or want government guarantees for OpenAI data centers. We believe that government should not pick winners or losers, and that taxpayers should not bail out companies that make bad business decisions or otherwise lose in the market. If one company fails, other companies will do good work. He continued, though, what we do think might make sense is government's building and owning their own AI infrastructure. But then the upside of that should flow to the government as well.

Starting point is 00:14:30 We can imagine a world where governments decide to offtake a lot of computing power and get to decide how to use it, and it may make sense to provide lower cost of capital to do so. Building a strategic national reserve of computing power makes a lot of sense. But this should be for the government's benefit, not for the benefit of private companies. Now, just a couple hours before this, White House AIs are David Sacks, made the position of the administration pretty clear. There will be no federal bailout for AI. The U.S. has at least five major frontier model

Starting point is 00:14:57 companies. If one fails, others will take its place. Sacks continued, that said, we do want to make permitting and power generation easier. The goal is rapid infrastructure buildout without increasing residential rates for electricity. Now, Sacks also added, finally, to give the benefit of the doubt, I don't think anyone was actually asking for a bailout that would be ridiculous. But company executives can clarify their own comments. Now, one area where Altman got a little bit more specific, as part of his clarification, was around U.S. infrastructure buildout. He wrote, The one area where we have discussed loan guarantees is as part of supporting the buildout of semiconductor fabs in the U.S., where we and other companies have responded to the government's

Starting point is 00:15:33 call and where we would be happy to help, though we did not formally apply. The basic idea there has been ensuring that the sourcing of the chip supply chain is as American as possible in order to bring jobs and industrialization back to the U.S. and to enhance the strategic position of the U.S. with an independent supply chain for the benefit of all American companies. This is, of course, different from government's guaranteeing private benefit data center buildouts. Now, this is something we've heard from Open AI before.

Starting point is 00:15:59 In a letter last month to the White House Office of Science and Technology Policy, they asked the government to extend CHIPS act subsidies into other necessary infrastructure like Transformers for the Grid, AI server production, and AI data centers. Now, cutting to the heart of the discussion, Altman flagged that there are three questions behind the question that were causing concerns around this idea of a backstop or a bailout. The first question was how OpenAI will pay for $1.4 trillion in infrastructure over the next eight years. Altman said that revenue for the company is now at a $20 billion run rate, and he expects hundreds of billions of ARR by 2030. Now, this is a big update and is basically 50% more than

Starting point is 00:16:36 previously reported numbers when it comes to OpenAI's ARR. Altman covered a range of new products they are looking to build out, including their enterprise offering, robotics, and consumer devices. He said that they also might consider selling compute to other companies along the way if they overbuild. But ultimately, he said, everything we currently see suggests that the world is going to need a great deal more computing power than what we are already planning for. The second question was whether Open AI was intentionally becoming too big to fail, ergo forcing the government to stand behind them. Altman wrote, Our answer on this is an unequivocal no. If we screw up and can't fix it, we should fail,

Starting point is 00:17:08 and other companies will continue on doing good work and servicing customers. That's how capitalism works and the ecosystem and economy would be fine. We plan to be a wildly successful company, but if we get it wrong, that's on us. Altman referenced that interview with Tyler Cowen, the one in which he had said that he thinks that the government ends up as the insurer of last resort. In this clarification post, Alman claimed that this wasn't supposed to be about the infrastructure buildout, but rather the catastrophic risk of rogue AI or bad actors sabotaging AI infrastructure. In that context, Alman said that he does believe that the government, quote, should

Starting point is 00:17:38 be writing insurance policies for AI companies. The third and finally, Alman addressed the question of why OpenAI needs to spend so much now and can't grow more slowly. He wrote, We're trying to build the infrastructure for a future economy powered by AI, and given everything we see on the horizon in our research program, this is the time to invest to be really scaling up our technology. Massive infrastructure projects take quite a while to build, so we have to start now. Alman noted that even now OpenAI needs to rate limit their products and are facing a severe compute constraint. Echoing comments that we've heard over and over from Mark Zuckerberg, Alman wrote,

Starting point is 00:18:12 Based on the trends we are seeing of how people are using AI and how much of it they would like to use, we believe the risk to open AI of not having enough computing power is more significant and more likely than the risk of having too much. Finally, previewing some of the themes from that blog post that was released a little bit later, Altman wrote, In a world where AI can make important scientific breakthroughs, but at the cost of tremendous amounts of computing power, we want to be ready to meet that moment,

Starting point is 00:18:35 and we no longer think it's in the distant future. So how did the market respond? Former Trump White House policy advisor, Dean Ball, who had jumped all over the comments when they were initially released, posted a long and thoughtful response, touching on numerous points. He reinforced why the government shouldn't get involved in loan guarantees, taking equity stakes or picking winners,

Starting point is 00:18:54 partially because the failure of a major company becomes a big liability for the government, but also because it limits the ability for new and better competition to emerge. On the point of government insurance for catastrophic risk, Ball noted that the nuclear industry is the canonical example, and that insurance of meltdown risk is guaranteed in exchange for strict safety regulations. He wrote, there are merits and demerits to this idea, but it's not a crazy one to consider for advanced AI. Ball also covered the policy maze of the government reducing the cost of capital for strategic industries, noting that this is already happening for semiconductor fabs. He gave the example of gas turbines where the government doesn't provide

Starting point is 00:19:29 loan guarantees or subsidies. Instead, to smooth over the notoriously boom and bust industry, the government serves as the buyer of last resort. That allows companies to expand with confidence that a buyer will be there in the worst case scenario, but doesn't tax the government's resources in the interim. Ball said that he had advocated for this approach during his time in the Trump White House, and he could see this approach moving forward. He wrote, this idea involves the government taking limited predefined risk. The political economy problems with this are non-zero, but they are far smaller than the regulatory capture that would ensue from the U.S. government guaranteeing untold billions of open-AI debt. Summing up, Ball noted that in the public interest proposals written by policy folks rather

Starting point is 00:20:06 than live comments from executives, open-aI seems to be thinking along the same lines. Rather than an open-ended bailout, they're proposing things that look more like industrial policy. He concluded, I absolutely do not support open-ended guarantees of frontier AI lab debt. I absolutely do support targeted industrial strategy to lower manufacturer cost of capital if a, exposes the government only to narrow predefined financial risk, and B, seems likely to yield tangible and durable beneficial assets for the American people. In the case of my example, he wrote, natural gas turbines to make electricity which is useful beyond AI, and which we need much more of regardless of AI. Alman seemed to agree with the premise, responding via quote tweet,

Starting point is 00:20:45 the government has played a role in critical infrastructure builds. Our public submission posted that on our blog shares our thinking and suggests ideas for how the U.S. government can support domestic supply chain and manufacturing. This is very in line with everything we've heard from the government about their priorities. We think U.S. reindustrialization across the entire stack, fabs, turbines, transformers, steel, and much more, will help everyone in our industry and other industries, including us. To the degree, the government wants to do something to help ensure a domestic supply chain, great. This is part of a national policy that makes sense to me. But that's super different than loan guarantees to Open AI, and we hope that's clear. It would be good for

Starting point is 00:21:19 the whole country, many industries, and all players in those industries. This all led up to the blog post, which was published on November 6th, called AI Progress and Recommendations. Now, notably, this post is from the company, not from Sam Altman personally, so presumably represents a broader official view for OpenAI. The post opened up by discussing the perception gap around AI. Most of the world they wrote still thinks about AI as chatbots and better search, but today we have systems that can outperform the smartest humans at some of our most challenging intellectual competitions. Open AI discussed how in just a couple of years, We've gone from AI that can only complete tasks that take humans a few seconds to tasks that take over an hour. They anticipate that very soon, AI will be able to complete tasks that take days or even

Starting point is 00:21:58 weeks. The other side of the equation is that cost has collapsed. They suggested that 40x decreases per year are a reasonable estimate for several years in the future. They also gave an update about what they think this progress translates to. In 26, we expect AI to be capable of making very small discoveries. In 28 and beyond, we're pretty confident we will have systems that can make more significant discoveries. Fields like AI material science, drug discovery, and climate modeling are starting to really develop along with health and education applications. The net of all of this is that OpenAI believes we are moving rapidly towards superintelligent AI, and in that context, they have a handful of policy recommendations to ensure that the AI future is a positive one.

Starting point is 00:22:37 The first recommendation was that Frontier Labs should agree on shared safety principles and share safety research. The next suggestion was matching public oversight and regulations to the power of models. They presented two schools of thought, the first being that AI is a quote-unquote normal technology like the internet or the printing press, in that while it will change society, but the conventional tools of public policy should still work. Open AI believes that the current level of model sophistication is still in this space, therefore should be diffused everywhere with minimal regulatory burdens. They suggested the need to promote innovation, protect the privacy of AI conversations, and defend against misuse. They also call out the risk of a 50-state patchwork. Open AI also noted,

Starting point is 00:23:13 however, a second school of thought that superintelligence will develop and diffuse in ways and at a speed humanity has not seen before. When it comes to regulation, then, they write, if the premise is that something like this will be difficult for society to adapt to in the normal way, we should also not expect typical regulation to be able to do much either. In that scenario, OpenAI is calling for a multinational approach to safeguard against mitigating existential threats like bioterrorism, as well as dealing with the implications of self-improving AI. They wrote, the high order bit should be accountability to public institutions, but how we get there might have to differ from the past. Along those lines, they said that the development of an AI resilience ecosystem will be required.

Starting point is 00:23:51 They liken this to the way that the internet developed, not tamed by a single policy or company, but instead a myriad of initiatives created the field of cybersecurity that helped ensure the internet could turn into the useful tool that it is today. OpenAI noted that this didn't eliminate the risk, it simply reduced it to something society could live with and improved trust enough to make the internet useful. They wrote, we will need something analogous for AI, and there is a powerful role for national governments to play in promoting industrial policy to encourage this. OpenAI also urged better reporting and measurement around AI changes in society. They wrote, prediction is hard. For example, the impact of AI on jobs has been hard to anticipate,

Starting point is 00:24:25 in part because today's AI's strength and weaknesses are very different from those of humans. Measuring what's happening in practice is likely to be very informative. Finally, they noted a moral imperative to build for individual empowerment writing, we believe that adults should be able to use AI on their own terms within broad bounds defined by society. We expect access to advanced AI to be a foundational utility in the coming years, on par with electricity, clean water, or food. Ultimately, we think society should support making these tools widely available, and that the North Star should be helping empower people to achieve their goals. So what does this all add up to? In my estimation, this is Open AI also reading the room

Starting point is 00:24:59 and seeing the rising tide of political discourse surrounding their industry and wanting to be even more assertive about having a hand in shaping the narrative. Because by any stretch of the imagination, right now, the AI narrative is very much outside of AI company's hands, except when they screw up. Politicians on both sides of the aisle have been getting louder and louder. Bernie Sanders has been tweeting about AI almost every week. One of his most recent reads, A major transformation of the economy is happening now. Billionaires aren't investing huge amounts of money in AI and robotics to make your life better. They're investing to replace you. Technology must work for all, not just the people who own it.

Starting point is 00:25:34 On the other side of the aisle, Florida Governor Ron DeSantis has dropped a half dozen tweets or more being extremely critical towards the tech companies. He shared an ad from meta promoting job creation as a part of data centers. With DeSantis adding, that meta would feel the need to run this ad is definitely a data point about the unpopularity of hyper-scale data centers. White House AIs are David Sacks writes, if judged based on consumer adoption AI chatbots are the most popular technology ever. If judged based on poll numbers, they are the least popular. Even the Pope is weighing in. Over the weekend, Pope Leo tweeted, Technological innovation can be a form of participation in the divine act of creation.

Starting point is 00:26:10 It carries an ethical and spiritual weight for every design choice expresses a vision of humanity. The church therefore calls all builders of AI to cultivate moral discernment as a fundamental part of their work, to develop systems that reflect justice, solidarity, and a genuine reverence for life. The point here is that in my estimation, we are quickly ratcheting up into a much more political moment for AI, with every move, every deal, every errant public comment, wildly more scrutinized than anything we've seen from other technology fields in the past. That is the context in which AI companies are operating.

Starting point is 00:26:42 So when it comes to the politics of AI, it is very clearly not a normal technology. Anyways, this is something we'll be talking about a lot more, I'm sure, over the months and years to come. For now, that's going to do it for today's AI Daily Brief. Appreciate you listening and watching as always. Until next time, peace.

The AI Daily Brief: Artificial Intelligence News and Analysis - What Should the Government’s Role in AI Be?

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