Welcome to Eye on AI! In this edition…Scale AI cuts 14% of workforce after Meta investment, hiring of founder Wang…OpenAI to take cut of ChatGPT shopping sales in hunt for revenues…Former top Google researchers have built a new kind of AI agent\u2014and they think it could be a step toward superintelligence.<\/p>\n
I am reporting Eye on AI this week from Vancouver, where I\u2019ve been hanging out with thousands of PhD-level AI researchers at the International Conference for Machine Learning (ICML), one of the top annual gatherings for AI talent from elite universities, Big Tech labs, and AI startups.\u00a0<\/p>\n
I\u2019ll be honest: It\u2019s humbling to be here, surrounded by professors, postdocs, and industry researchers who casually drop references to mathematical proofs and thermodynamics metaphors into everyday conversation. There are thousands of posters, papers, and presentations\u2014far too many to meaningfully absorb, even if I fed them all into ChatGPT. My brain feels like it\u2019s running at max capacity as I try to make sense of talks titled \u201cControlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration\u201d and \u201cDiscrete Flow Matching for Graph Generation.\u201d<\/p>\n
Still, there\u2019s something electric about being in the room where the future of AI is being debated, defined, and maybe even redirected. I\u2019m a big believer in getting out of my comfort zone\u2014and into a beginner\u2019s mindset\u2014especially in a space where today\u2019s theories might become tomorrow\u2019s technologies. As I wrap up my time at ICML, here\u2019s what\u2019s sticking with me:\u00a0<\/p>\n
The AI talent wars are in full swing. Meta\u2019s extraordinary, ongoing hiring spree, which has thrown tens and even hundreds of millions of dollars at elite AI researchers lured from OpenAI, Anthropic, Google DeepMind and others, is the talk of ICML. Some clearly see it as over-the-top, with one London-based researcher telling me it is creating \u201ca bubble.\u201d Others envision Meta as a dream gig\u2014one Swedish PhD student, showing off an armful of swag from various exhibition hall booths, including a pair of blue IBM socks\u2014said he could only hope to land an interview there one day. Either way, Big Tech had recruiters working overtime, with private after-hour events for candidates sprinkled out at venues near the Vancouver Convention Center.\u00a0<\/p>\n
There\u2019s no better place to ask questions. One of the best things about hanging out with really smart people is picking the brains of really smart people. It helps that AI researchers are typically incredibly kind about explaining their work to a curious journalist. In a vast expo hall filled with seemingly-endless rows of poster presentations, you never know when you\u2019ll happen upon a well-known Stanford University professor perfectly happy to spend 20 minutes chatting about AI model behavior and ethical guardrails. How valuable are one-on-one meetings here? How about a machine learning pioneer waxing philosophically about the old days (which are only 10-15 years ago)? Or a former Google Brain researcher patiently explaining the ins and outs of Transformer models? Priceless.\u00a0<\/p>\n
Scaling up reinforcement learning (RL) is all the rage. That\u2019s not my line\u2014it\u2019s from former Tesla AI chief Andrej Karpathy on X<\/a>\u2014but RL was everywhere at ICML. (RL, or reinforcement learning, is a training method where AI learns by trial and error, to maximize some reward. That could be points in a game, or the number of \u201cthumbs up\u201d grades an AI model\u2019s outputs receive from a human evaluator.) Now, researchers are taking reinforcement learning techniques and pushing them to much larger scales to train or fine-tune today\u2019s big language and multimodal models. With more data, more compute, and harder tasks, you (hopefully) get models that work to reason better, follow instructions more reliably, and behave more safely in messy, real-world, enterprise settings.\u00a0<\/p>\n Lots of researchers are ready to live their founder dream. There is the startlingly young duo out of Princeton building multimodal medical foundation models. The PhD-level intern at Waymo using Pokemon games to stress-test large language models and AI agents on strategy. The ex-Google and ex-OpenAI researchers aiming to leapfrog current AI tech. With VCs walking the halls during the day and offering open bar events at night, it was easy to view this research conference as partly a hotbed of current and potential founders.\u00a0<\/p>\n I\u2019m ready to head back to New Jersey, with plenty of new story ideas and sources in tow. With that, here\u2019s the rest of the AI news. <\/p>\n Sharon Goldman AI IN THE NEWS<\/p>\n Scale AI cuts 14% of workforce after Meta investment, hiring of founder Wang. Just weeks after Meta invested $14.3 billion in Scale AI and hired founder Alexandr Wang, the AI startup is laying off 200 full-time employees\u2014about 14% of its workforce, according to<\/a> CNBC. In a memo to staff on Wednesday, interim CEO Jason Droege, who recently took over for Wang, said the company had scaled its generative AI efforts \u201ctoo quickly\u201d and had built up \u201cexcessive bureaucracy.\u201d Despite the cuts, Droege emphasized that Scale remains well-funded and well-resourced. \u201cThese changes will make us more nimble\u2014enabling us to react more quickly to shifts in the market and customer needs,\u201d he wrote in the memo viewed by CNBC. \u201cThis structure will allow us to better serve the customers we have today and win back customers that have slowed down work with us.\u201d<\/p>\n OpenAI to take cut of ChatGPT shopping sales in hunt for revenues. According to the Financial Times<\/a>, OpenAI is planning to take a cut of product sales made directly through ChatGPT as it ramps up efforts to turn the chatbot into an ecommerce platform. Currently, ChatGPT surfaces product listings with links to external retailers. But according to multiple sources familiar with the plans, OpenAI now aims to integrate a full checkout system\u2014allowing users to complete purchases within ChatGPT. Merchants who fulfill orders through this system would pay OpenAI a commission. The company also announced a partnership with Shopify in April as part of its broader push into AI-driven shopping.<\/p>\n Former top Google researchers have built a new kind of AI agent\u2014and they think it could be a step toward superintelligence. Their startup, Reflection, just unveiled Asimov, an agent that learns how software is built not just by reading code, but by digesting everything around it: emails, Slack messages, documentation, and project updates. According to Wired<\/a>, the goal is to create a more capable AI assistant\u2014and to teach models how humans actually build things, one decision at a time.<\/p>\n FORTUNE ON AI<\/p>\n Elon Musk released xAI\u2019s Grok 4 without any safety reports\u2014despite calling AI more \u2018dangerous than nukes\u2019<\/a> \u2014by Beatrice Nolan<\/p>\n Commentary: The companies laying off staff for AI today will regret it in five years<\/a> \u2014by Alexandra Ebert<\/p>\n Delta moves toward eliminating set prices in favor of AI that determines how much you personally will pay for a ticket<\/a> \u2014by Irina Ivanova<\/p>\n CEO of $14 billion AI firm Perplexity says the secret to success is \u2018sleeping with that fear\u2019 that your competitor will steal your idea<\/a> \u2014by Preston Fore<\/p>\n AI CALENDAR<\/p>\n July 22-23:\u00a0Fortune Brainstorm\u00a0AI Singapore. Apply to attend\u00a0here<\/a>.\n<\/p>\n July 26-28:\u00a0World\u00a0Artificial\u00a0Intelligence\u00a0Conference (WAIC), Shanghai.\u00a0\n<\/p>\n Sept. 8-10: Fortune Brainstorm Tech, Park City, Utah. Apply to attend\u00a0here<\/a>.<\/p>\n Oct. 6-10:\u00a0World\u00a0AI\u00a0Week, Amsterdam\n<\/p>\n Dec. 2-7:\u00a0NeurIPS, San Diego\n<\/p>\n Dec. 8-9:\u00a0Fortune Brainstorm\u00a0AI\u00a0San Francisco. Apply to attend\u00a0here<\/a>.\n<\/p>\n EYE ON AI NUMBERS75.6%<\/p>\n That\u2019s how much startup funding surged in the first half of 2025, thanks to the continued AI boom, putting this year on track to become the second-strongest for venture capital investment in history. U.S. startups raised a total of $162.8 billion in the first six months of the year\u2014the most since the record-setting first half of 2021, according to<\/a> new data from PitchBook.<\/p>\n While that earlier surge was fueled by ultra-low interest rates during the COVID-19 era, this time it\u2019s AI driving the momentum. Massive investments from Big Tech and AI-native firms have supercharged the market, even as many venture funds continue to struggle with fundraising. In just the past three months, startups brought in $69.9 billion.<\/p>\n Notable deals included OpenAI\u2019s $40 billion round, Meta\u2019s $14.3 billion stake in Scale AI, and billion-dollar-plus raises for Safe Superintelligence, Thinking Machines, Anduril, and Grammarly. AI accounted for 64.1% of total deal value and 35.6% of deal volume in the first half\u2014clear evidence of where the money (and conviction) is flowing.<\/p>\n
sharon.goldman@fortune.com<\/a>
@sharongoldman<\/a><\/p>\n