The AI "Copied My Homework" Scandal, Why the Strait of Hormuz Is Spiraling Out of Control, and Other Global News| Weekly Recap

What's up, everybody? It's Tom Bilyeu here:Want my help starting a business? Join me here inside Zero To FounderSign up for my AI Masterclass:  AI MasterclassFOLLOW TOM:Instagram: https://www.instagram.com/tombilyeu/Tik Tok: https://www.tiktok.com/@tombilyeu?lang=enTwitter: https://twitter.com/tombilyeuYouTube: https://www.youtube.com/@TomBilyeuTailor Brands: Check out Tailor Brands to get started with your business today: https://bit.ly/TailorBrandsSeptQuince: Free shipping and 365-day returns at https://quince.com/impactpodElevenLabs: Book your demo at https://elevenlabs.io/impactpodIncogni: Take your personal data back with Incogni! Use code IMPACT at the link below and get 60% off an annual plan: https://incogni.com/impact Ketone IQ: Visit https://ketone.com/IMPACT for 30% OFF your subscription order.Horizon.ai: Go to https://horizon3.ai/IMPACTTHEORY and request your free NodeZero demo. No commitment required. Results in hours, not weeks.Butcherbox: Go to https://ButcherBox.com/IMPACT to get $20 off your first box, plus your choice of free ribeye, new york strip, or filet mignon in every box for a year — with free shipping alwaysQuo: ​​Try for free PLUS get 20% off your first 6 months at https://quo.com/impactThe team digs into a strange and revealing controversy at the frontier of AI: a potential mathematics breakthrough where humans and AI are now fighting over who deserves the credit. For about a year, NYU mathematician Tristan Buckmaster and a researcher at Anthropic had been working on an obscure approach to one of the famous Clay Institute "millennium prize" problems (with $1 million on the line)—running their drafts through private OpenAI Codex sessions hosted on OpenAI's servers. When a step forward emerged (a result related to "blow-up" in the Euler equations of fluid dynamics), accusations flew that OpenAI's model had essentially "copied their homework"—learning from their private work and then producing the result itself. The host uses it to open up what he thinks is the defining debate of the era: when you collaborate with an AI, and it helps you reach an insight you genuinely pushed it toward, who owns the result? He walks through the emerging solutions—Alex Karp of Palantir's "put something in the middle" approach, versus self-hosting an open-source model behind your own servers with your own tuned "weights" so your inputs stay proprietary even as the world uses your outputs. He's candid that he's genuinely torn: as someone building his own project (Kaizen), he admits feeling the impulse to keep some paths secret for a six-month lead, while also arguing that since AI was trained on all of humanity, there's an obligation to keep letting it aggregate humanity's breakthroughs—especially in a field like medicine, where he shares a personal story about a family member's cancer and how siloed, firewalled medical data made coordination nearly impossible. His most provocative point is psychological: that the reason people a