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- OpenAI says it’s turned off app suggestions that look like ads
OpenAI says it’s turned off app suggestions that look like ads
The Math Legend Who Just Left Academia—for an AI Startup Run by a 24-Year-Old
In today’s email:
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Key Takeaway: OpenAI has temporarily turned off ChatGPT app suggestions that felt like ads after paid users complained, while insisting it isn’t actually running or testing advertising yet.
More Insights:
Paying ChatGPT users reported seeing promotional-style messages for brands like Peloton and Target, sparking anger and confusion.
OpenAI claims these were app recommendations from its new app platform, with “no financial component” and no real ad program behind them.
Chief research officer Mark Chen admitted the company “fell short,” saying anything that feels like an ad must be handled carefully.
OpenAI says it has turned off this kind of suggestion while it improves targeting and plans better user controls to dial suggestions down or off.
A recent “code red” memo from Sam Altman reportedly shifts focus to improving ChatGPT quality, delaying ad-focused products despite hiring ad-savvy execs like Fidji Simo.
Why it matters: This showdown over “not-ads” is really about trust—if users feel their AI assistant is quietly shifting from helpful guide to stealth salesperson, they’ll question every answer, and once that trust erodes, no amount of new features or revenue streams can easily win it back.
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Key Takeaway: At 57, famed number theorist Ken Ono is leaving a tenured professorship at UVA to join his former student’s AI startup, Axiom Math, betting that AI-powered “mathematical superintelligence” will transform how deep mathematics is done.
More Insights:
Ono went from AI skeptic to daily power user after seeing cutting-edge models solve advanced math problems in areas outside his expertise.
He’s joining Axiom Math, founded by his 24-year-old former student and prodigy Carina Hong, which has raised $64 million and hired leading AI researchers from Meta.
Axiom’s goal is to build an “AI mathematician” that can reason about open problems, generate new ones, and verify proofs with formal rigor.
Ono’s role as “founding mathematician” is to design hard, representative problems and benchmarks that stretch the models and map their true capabilities.
Disillusioned by politics and funding pressures in academia, Ono sees startups like Axiom as a place where pure math can directly shape real-world systems—from chip design to finance.
Why it matters: This move signals a deeper shift: when top, established mathematicians leave secure academic posts to help build AI that might one day outperform them, it suggests we’re not just automating routine tasks—we’re beginning to rewire who does fundamental discovery itself, and what a “career in thinking” will look like in the age of machines that think with us.

Key Takeaway: Yann LeCun is leaving Meta to build a Paris-based “world model” AI startup, without Meta’s investment, aiming at systems that understand and predict the physical world rather than just generate text.
More Insights:
LeCun confirmed Meta will not be an investor in his new, still-unnamed company.
The startup focuses on “advanced machine intelligence” trained on visual and sensory data to predict real-world outcomes.
He criticizes Silicon Valley’s obsession with generative models and LLMs, saying that real-world prediction needs to be built “outside the Valley, in Paris.”
World models target physical systems—robots, autonomous vehicles, industrial processes—rather than just word prediction.
Mark Zuckerberg supports the project, but both concluded its applications go far beyond Meta’s core interests.
Why it matters: This marks a clear split between today’s LLM-centric AI and a possible “next wave” focused on embodied, real-world intelligence—hinting that the future of AI may be decided not just by bigger text models, but by whoever can give machines common sense about the physical world.
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