OpenAI's AI Wrote 700 Math Papers. Engineers Still Won't Trust AI With Their Code.

OpenAI just released more than 700 math research papers from a model it hasn't released. I think that's narrow superintelligence. And the reason many engineers still keep coding agents away from production tells you more about your job than the papers do. Full post: https://natesnewsletter.substack.com/p/narrow-superintelligence-ai?utm_source=youtube&utm_medium=video&utm_campaign=narrow-superintelligence-ai-launch&utm_content=description Nate's Library MCP, every article, prompt kit and guide I've ever published inside the AI you already use: https://unlock-ai.natebjones.com/guides/how-to-connect-nates-library?utm_source=youtube&utm_medium=video&utm_campaign=narrow-superintelligence-ai-launch&utm_content=description My Links 🔗 👉🏻 Newsletter: https://natesnewsletter.substack.com/?utm_source=youtube&utm_medium=video&utm_campaign=narrow-superintelligence-ai-launch&utm_content=description 👉🏻 X: https://x.com/natebjones 👉🏻 TikTok: https://www.tiktok.com/@nate.b.jones 👉🏻 Instagram: https://www.instagram.com/nate.b.jones What's really happening inside OpenAI's math release? The common story is that superhuman math means AI is coming for your job, but the real question is why that ability hasn't shown up in coding, where every lab is pouring money and the answers are easy to check. In this video, I share the inside scoop on narrow superintelligence and your work: - What the math papers contain and how the results could reach you - Why math suits AI training better than engineering or business work - How a search feature can pass every test and still create a privacy problem - Where to spend your skill points when AI ability is this uneven AI can now produce new results in mathematics, but finding the right question, designing systems that last, and following through on a decision are still human work worth getting better at. Chapters: 00:00 More than 700 math papers and the engineers who still don't trust AI code 01:43 What the math papers actually contain 04:13 The unreleased model and OpenAI's three-hour figure 04:43 What narrow superintelligence means 06:33 Why coding is the real test of transfer 08:00 A search feature that passes every test 10:38 Why gains in math don't transfer one-to-one 11:11 When the fixed feature exposes a business problem 14:06 Not every problem is a function of intelligence 15:56 Where to spend your skill points 17:01 We have more agency over AI than you think 19:15 Execution, focus, and the fire in the belly Listen to this video as a podcast. Spotify: https://open.spotify.com/show/0gkFdjd1wptEKJKLu9LbZ4 Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-news-strategy-daily-with-nate-b-jones/id1877109372