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Get notified as soon as The Sovereign Professional launches. The first 10 buyers get 50% off: https://www.brendandell.com/signup ______ SOURCES The announcement and the proof OpenAI, "On the Navier-Stokes Millennium Prize Problem" (Sept 8, 2026): https://openai.com/index/navier-stokes-solution/ OpenAI, the full proof (PDF): https://cdn.openai.com/pdf/32d9f210-8b73-45e0-91bc-82a30aef8a9a/navier-stokes.pdf The mathematicians Tristan Buckmaster, statement (NYU): https://cims.nyu.edu/~tristanb/statement.pdf Numberphile, "The Buckmaster Interview" (Sept 29, 2026): https://www.youtube.com/watch?v=Mzbtj5nkMXI Terence Tao, on the Alpöge-Buckmaster blow-up results (Sept 7, 2026): https://terrytao.wordpress.com/2026/09/07/finite-time-blowup-with-smooth-forcing-term-for-the-incompressible-porous-medium-boussinesq-and-incompressible-euler-equations/ Terence Tao, his collected views on AI: https://teorth.github.io/tao-web/ai-views.html "A Severe Misalignment of AI in Mathematics," declaration signed by 28 Fields Medalists: https://mathandai.org/ The Millennium Prize Clay Mathematics Institute, the Millennium Prize Problems: https://www.claymath.org/millennium-problems/ Clay Mathematics Institute, the Navier-Stokes problem: https://www.claymath.org/millennium/navier-stokes-equation/ Charles Fefferman, official Clay problem statement (PDF): https://www.claymath.org/wp-content/uploads/2022/06/navierstokes.pdf Wikipedia, Millennium Prize Problems: https://en.wikipedia.org/wiki/Millennium_Prize_Problems Reporting and commentary NPR via KPBS, "AI solved one of math's hardest problems. Humanity learned nothing (so far)" (Sept 22, 2026): https://www.kpbs.org/news/science-technology/2026/09/22/ai-solved-one-of-maths-hardest-problems-humanity-learned-nothing-so-far Scientific American, "Did OpenAI Solve the Wrong Navier-Stokes Problem?" (Sept 21, 2026): https://www.scientificamerican.com/article/did-openai-solve-the-wrong-navier-stokes-problem/ IBM Think, "Will AI solve math too fast?" (Sept 10, 2026): https://www.ibm.com/think/news/will-ai-solve-math-too-fast-navier-stokes-terence-tao Understanding AI, "OpenAI spent millions to solve this" (Sept 10, 2026): https://www.understandingai.org/p/openai-spent-millions-to-solve-this Stand-up Maths, "Has a Millennium Prize Problem been solved by AI?" (Sept 21, 2026): https://www.youtube.com/watch?v=c79PsbkHw4A Research and background Chen, Wang & Qu, "Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops" (2026): https://arxiv.org/abs/2607.07663 House of El, "Like Sabine Hossenfelder, I Was Offered Money to Tell You AI Will Kill Us" (Sept 22, 2026): https://www.youtube.com/watch?v=claxN4oxDuY Lean, the proof assistant: https://lean-lang.org/ Stanford Encyclopedia of Philosophy, "Alan Turing": https://plato.stanford.edu/entries/turing/ Clips Richard Feynman, "Names Don't Constitute Knowledge" (Yorkshire Television, 1973): https://www.youtube.com/watch?v=lFIYKmos3-s A Beautiful Mind (2001), "It's their problem": https://www.youtube.com/watch?v=voqjl5yDsyk Watch next Princeton Just Proved AI Can't Take Your Job: https://www.youtube.com/watch?v=FqFqWxGQltg Billionaires Spent $1 Trillion on AI. Nobody Has Anything to Show for It: https://www.youtube.com/watch?v=UR3F3N9K-xw This Is the Last AI Video You EVER Need to Watch: https://www.youtube.com/watch?v=tfv4Rd1JvEo 0:00 The Million-Dollar Math Mystery 1:48 Navier-Stokes and the PR Machine 3:23 The Race to the Breakthrough 7:15 Why Mathematicians Value the Journey 13:13 How Lean Verifies the Impossible 17:55 Intelligence vs. Calculation

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