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Hello and welcome to Eye on AI. In this edition:<\/em><\/p>\n I\u2019m just back from three weeks of vacation. Thanks to my <\/em>colleagues Bea Nolan and Emily Forlini for holding down the fort here while I was away.<\/p>\n For much of that time, I was engaged in outdoor activities\u2014camping, hiking, kayaking, fishing, running, and swimming\u2014or indoor ones that are not digitally-mediated, such as dining out with family or listening to live entertainment. Sure, my family and I did sometimes use Google Search to look stuff up, and the AI-summarized answers it provided were often impressively detailed and accurate. It was definitely a lot more convenient than having to hunt for information across multiple web pages. But that\u2019s about where my interaction with AI started and stopped. Overall, my three week break was a refreshing reminder of all the ways in which AI has not <\/em>transformed society and, hopefully, never will.<\/p>\n The big AI news over the weekend was the debate over Dario Amodei\u2019s lengthy post on X defending the company\u2019s approach to both regulation and talking about AI\u2019s many risks. Amodei, who rarely appears on the Elon Musk-controlled social media platform, made the post in response to comments investor Gavin Baker made on the \u201cAll In\u201d podcast, which is cohosted by former Trump AI czar David Sacks, himself no fan of Anthropic.<\/p>\n Baker said that he\u2019d been told \u201cby multiple people I trust\u201d that Amodei had said that Anthropic was so confident of both AI\u2019s potential and his company\u2019s position at the forefront of AI development that \u201cAnthropic might be the only private company in the world at some point.\u201d Baker described this as evidence of Anthropic\u2019s \u201cmaximalist\u201d vision, in which only it and the U.S. government decided who could access super powerful AI. Meanwhile, Sacks called it \u201chubristic\u201d and repeated his claims that Amodei\u2019s strategy is \u201cregulatory capture\u201d\u2014where Anthropic uses fear of AI\u2019s risks to persuade the government to enact stringent regulation on the technology that only Anthropic can easily comply with, eliminating competition from other AI startups or open-source models.<\/p>\n Baker went on to criticize Amodei for fueling the public\u2019s overwhelmingly negative perception of AI, a factor that has played into opposition to data center construction around the U.S. Baker worries this negativity is making business difficult for AI companies and also fears it will imperil American leadership in the technology. He called on Amodei to present a more positive image of AI.<\/p>\n Anthropic denies Amodei ever said anything like what Baker claims. \u201cComplete and utter nonsense,\u201d Sasha de Marigny, Anthropic\u2019s chief brand and communications officer, replied on X. (Sacks later pointed out that Amodei himself did not directly address Baker\u2019s claim.) Meanwhile, Amodei posted on X that he thinks Silicon Valley libertarians such as Baker tend to see all regulation as slowing technology down and resulting in regulatory capture, whereas others \u201coutside of this bubble\u201d see regulation as constraining corporate power and benefitting \u201cordinary people.\u201d Amodei said he thought both positions oversimplified things and that \u201cit\u2019s complicated and really depends on what the \u2018regulation\u2019 consists of.\u201d<\/p>\n Amodei said Anthropic tries \u201cvery hard to make proposals that disadvantage (slow down) frontier AI companies while *advantaging* smaller competitors.\u201d He noted that many of the regulations it has favored either contained specific exemptions for companies below a certain revenue threshold or that spent less than a certain amount on model training, or were designed only to apply to cutting-edge models, while exempting less-capable ones.<\/p>\n He said he did believe AI naturally tended to concentrate economic power, because of the compute requirements to train and serve powerful AI models, but that this was very different from saying that only one or a few companies would exist in the future. And he said open source models only partly addressed this concentration of power, since they still required compute to train and run. He said he favored \u201crules of the road\u201d that would \u201cleave room for open-weights models while also addressing the specific risks that they bring.\u201d<\/p>\n As for Baker\u2019s criticism that his own statements were responsible for turning the public against AI, Amodei said \u201cI don\u2019t think [the public\u2019s negative view of AI] is primarily caused by me or any other AI leader warning about AI\u2019s risks. I think it is fundamentally a crisis of trust.\u201d He said he didn\u2019t think the AI industry could win back that trust with \u201ca glitzy marketing campaign with a positive spin.\u201d Instead, he said AI companies actually had to deliver on the positive benefits of AI\u2014such as actually curing cancer. \u201cI think by far the most accurate criticism of AI companies including Anthropic is that we haven\u2019t yet delivered on our big promises to benefit the world,\u201d he wrote. \u201cThat is totally on us, and I think it\u2019s the criticism you should be making, instead of all this stuff about messaging and marketing.\u201d<\/p>\n Amodei\u2019s post resulted in lots more back-and-forth between critics and defenders on X. On the regulation point, Sacks wrote that creating any kind of regulatory agency for AI\u2013he called it \u201ca DMV for AI\u201d\u2014would hobble the U.S. tech sector, \u201ccreate long queues as AI models wait for testing and approval\u201d and \u201chandicap the U.S. relative to China, which will not adopt the same constraints.\u201d Sacks also wrote that \u201cDario believes frontier AI is too powerful to distribute; we believe it is too powerful to centralize.\u201d<\/p>\n My own take is that Dario is right to call out the false dichotomy in Sacks\u2019 AI regulation narrative. As Stuart Russell, the UC Berkeley computer scientist, frequently quips, a sandwich shop in San Francisco has to comply with more regulation than OpenAI or Anthropic (that\u2019s less true after the passage of California\u2019s state level law on frontier AI last year but it\u2019s still true at the federal level). Does regulation somewhat limit the number of restaurants? Sure. But there\u2019s still plenty of competition. There\u2019s more than 3,000 restaurants in San Francisco.<\/p>\n Now, do larger restaurant chains have an easier time complying with the rules? Probably\u2014there are some economies of scale to compliance and, yes, the big chains have lobbying muscle and political connections that most mom-and-pop shops don\u2019t. But is the public better served from having some food safety regulations and labor regulation and product liability laws rather than none? Of course it is. And I would argue the same goes for the auto industry. For all of Sacks\u2019 maligning of the DMV, most people support the idea of licensing drivers and periodically inspecting vehicles to make sure they are road-worthy. Is there some concentration in the auto industry? Sure, but regulation is not the primary reason.<\/p>\n As for the idea that regulation sets the U.S. back in a technological race with China, it is important to remember that China already has some AI laws, around data labeling and identifying AI-generated content, that are stricter than those in the U.S. It is also the case that if what the U.S. cares about is the national security implications of powerful AI, then it could exempt models developed specifically for national security purposes from the rules. (Although this is probably a bad idea\u2014see WarGames <\/em>or Terminator<\/em>. It\u2019s useful to remember we managed to win the Cold War while also having fairly strict regulation around the manufacture and transport of nuclear material. I am not sure having safety rules around the development of frontier AI should be any different.)<\/p>\n With that, here\u2019s more AI news.<\/p>\n Jeremy Kahn<\/strong> Before we get to the news, just a reminder to check out our new vodcast, <\/em>Fortune AI Weekly. This week, Bea Nolan and Emily Forlini discuss Meta CEO Mark Zuckerberg\u2019s 6,000-word manifesto<\/em>, leadership changes at OpenAI, and talk to Lovable co-founder and CEO Anton Osika about he startup\u2019s $13.3 billion valuation and $400 million Series C funding. Y<\/em>ou can check out the vod here on YouTube.<\/em><\/p>\n OpenAI data center deal with Nvidia comes in $145 billion lower than reported\u2014signaling concerns of artificial demand for chips\u2014by Joshua Hong<\/p>\n The finance skills that are becoming more and more critical in the AI age\u2014by Sheryl Estrada<\/p>\n \u2018Godfather of AI\u2019 says billionaires like Elon Musk are right about the future of work\u2014but he predicts mass unemployment is on its way\u2014by Preston Fore<\/p>\n Fortune Archives: The end of an era at Google DeepMind\u2014by Indrani Sen<\/p>\n OpenAI details pause in AI training, new safety controls following Hugging Face attack. <\/b>The AI company said it paused some portions of its AI training for two weeks following the incident in July in which its AI models broke out of a controlled research environment and hacked the AI company Hugging Face. It said some of its largest AI training runs remain on hold as it implements new safety controls that include more comprehensive monitoring of its AI models\u2019 \u201cchain of thought\u201d during training and evaluation, more restrictive testing \u201csandboxes\u201d that make sure it\u2019s harder for AI models to gain access to the internet, and closer scrutiny of its models\u2019 actions. The company said the new protocols were prompted in part by the Hugging Face incident but also because its unreleased \u201cAstra\u201d AI model, which it said was not involved in that cyberattack, posed \u201ccritical\u201d cybersecurity risks under the company\u2019s own safety framework. You can read more from Fortune\u2019s Emily Forlini <\/span>here<\/span>.<\/span> OpenAI rolls out ChatGPT for teens. <\/b>The company has debuted a long-awaited version of its popular ChatGPT chatbot tailored specifically for teenagers. The teen version includes stronger safety protections, parental controls and features designed to emphasize learning and tutoring rather than simply helping kids cheat on their homework. The teen ChatGPT restricts romantic or overly human-like interactions and adds new safeguards around self-harm, eating disorders and explicit content. It will also remind teens more frequently to take breaks from interacting with the AI. Users who identify as 13 to 17\u2014or whom OpenAI\u2019s age-prediction technology estimates are under 18\u2014will automatically receive the teen experience. The launch comes as OpenAI faces legal scrutiny over ChatGPT\u2019s interactions with young people and a broader debate over whether adolescents should be forming relationships with AI chatbots at all. You can read more from Axios <\/span>here<\/span>.<\/span><\/p>\n Anthropic hits $65 billion annual revenue run rate ahead of IPO.<\/b> That\u2019s according to a Bloomberg <\/span>story<\/span> that cites unnamed sources familiar with the company\u2019s financial figures. Ther $65 billion number is more than seven times Anthropic\u2019s revenue pace at the end of 2025 and up from $47 billion in May, according to Bloomberg. The rapid growth, driven in part by strong demand for its AI coding tools, comes as Anthropic prepares for a potential IPO as soon as this fall. Anthropic, valued at $965 billion in a May funding round, also reportedly generated more than $11.5 billion in preliminary quarterly revenue and positive adjusted operating income in its latest completed quarter.<\/span><\/p>\n U.K. examines economic hit if it loses access to top AI models. <\/b>The U.K. government is assessing the economic and security risks to British consumers and businesses if the country were to be denied access to frontier AI models from companies such as OpenAI and Anthropic, according to a <\/span>story<\/span> in the <\/span>Financial Times<\/span><\/i> that cites unnamed sources familiar with the government effort. The review was prompted in part by the Trump administration\u2019s temporary move to restrict foreign access to Anthropic\u2019s Fable 5 model in June, raising concerns that even brief delays in accessing cutting-edge models could hurt U.K. productivity and leave British companies more vulnerable to AI-enabled cyberattacks. The episode has also intensified debate over Britain\u2019s dependence on U.S. technology and whether the government needs greater sovereign AI capabilities. The UK says it is addressing that vulnerability through a \u00a31.1 billion AI hardware plan and a \u00a3500 million sovereign AI fund.<\/span> How good are frontier AI models at intuiting the rules? <\/b>That\u2019s essentially what a new benchmark created by a group of AI researchers from several different universities aims to test. AI models are asked to play 70 different novel text-based games, but in each case the rules of the games and the objective of the game is hidden. The models have to suss them out by taking actions in the game, seeing what happens, forming hypotheses, and then taking more actions to test those theories. The idea is that doing this has some real-world parallels, both in scientific discovery but also in lots of other real world settings (think office politics or cocktail parties) where the rules of how to operate are not written down. Twenty-one games have been made public while the remainder are kept private to reduce the risk of models being trained on them.<\/span><\/p>\n The games were grouped into seven tiers of difficulty. All 70 games were solved by at least one human on the first attempt, according to the researchers. Anthropic\u2019s Claude Opus 5 did the best, solving 100% of the Tier 1 games, while other models from the likes of OpenAI, Google DeepMind, and various Chinese AI labs, were more in the 70% to 80% range. But by the time the models got to the most difficult Tier 7 games, Opus 5 could only solve 20% of them while the other models solved less than 5%.<\/span> Nov. 16-17: <\/strong>Fortune 500 Innovation Forum, Detroit. Apply here to attend.<\/p>\n Dec. 6-12:\u00a0<\/strong>Neural Information Processing Systems (Neurips) conference. Sydney, Australia.<\/p>\n Dec. 7-8:\u00a0<\/strong>Fortune Brainstorm AI, San Francisco. Apply here to attend.<\/p>\n Think you can run a frontier AI lab? <\/b>Well, a new simulation game allows you to put that idea to the test. Crypto firm Paradigm has built a game called RSI\u2014short for recursive self-improvement (when AI models are used to create newer, more powerful AI models in an accelerating loop)\u2014that challenges players to juggle the money spent on AI research talent against compute costs, venture capital rounds, and time pressure, to get to RSI. The simulator is simple, but it gives players some idea of the complex trade offs in the AI race. You can play it <\/span>here<\/span>.<\/span><\/p>\n<\/div>\n #Anthropic #CEO #Dario #Amodei #defends #approach #regulation #discussion #risk<\/p>\n","protected":false},"excerpt":{"rendered":" Hello and welcome to Eye on AI… <\/p>\n","protected":false},"author":1,"featured_media":2588,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[1902,428,4951,283,4731,1717,4950,911,4952,809,810,3599,752,1304],"class_list":["post-2587","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-finance-news","tag-amodei","tag-anthropic","tag-approach","tag-ceo","tag-dario","tag-dario-amodei","tag-david-sacks","tag-defends","tag-discussion","tag-eye-on-ai","tag-machine-learning","tag-regulation","tag-risk","tag-tech-regulation"],"yoast_head":"\n\n\n
Amodei hits back<\/strong><\/h2>\n
A DMV for AI? What\u2019s wrong with that?<\/h2>\n
jeremy.kahn@fortune.com
@jeremyakahn<\/p>\nFORTUNE ON AI<\/h3>\n
AI IN THE NEWS<\/h3>\n
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<\/span>Alibaba launches music generation AI model. <\/b>Called HappyShrimp 1.0, the model can turn a text prompt into a fully produced song, generating melodies, arrangements, lyrics and vocals across genres including pop, rock, electronic and jazz. The launch, which includes a partnership with China\u2019s Taihe Music Group, is part of Alibaba\u2019s broader AI push as it seeks to quintuple annual cloud and AI revenue to $100 billion within five years. You can read more <\/span>here<\/span> from Bloomberg.<\/span><\/p>\nEYE ON AI RESEARCH<\/h3>\n
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<\/span>You can read more about the research on its Github page <\/span>here<\/span>.<\/span><\/p>\nAI CALENDAR<\/h3>\n
BRAIN FOOD<\/h3>\n