Molly O’Shea@MollySOSheaOct 2

BREAKING: The future of AI isn't open vs. closed. We need a TON of both. Turing CEO on why frontier AI & open-weight models are increasingly serving different parts of the AI stack. “There's absolutely a place in the world for Ferraris & Koenigseggs. But there's also a place in the world for Model Ys.” Frontier models continue pushing the limits of intelligence. Jonathan's point isn't that one replaces the other. We need frontier AI to keep advancing capabilities & open models to diffuse those capabilities across the economy. BTW "Only 2% of US households pay for AI" It's still early. At the same time, AI training is moving beyond benchmarks into simulated environments built for real work, as agents move from completing tasks to operating autonomously for days, & eventually weeks, months & years. @turingcom CEO Jonathan Siddharth (@Jonsid) We break down what this shift means for frontier labs, enterprises & the AI stack: › Frontier AI vs. sovereign AI › Distillation & the shrinking model gap › Why enterprises are moving to open models › What AI safety & alignment teams actually do › Reward hacking & why “if the model can figure out a way to cheat & get the reward, it will” › Super Intelligence, recursive self-improvement & slow takeoff 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Jonathan Siddharth, Co-Founder & CEO at Turing (01:03) The biggest shift in AI data this year (04:10) Why AI won't replace jobs, but uplevel them (08:31) The arms race inside cybersecurity (11:22) Why train AI on what it shouldn't do? (15:45) The Hugging Face hacking incident (22:33) How AI models cheat to win (27:40) The AI playbook (32:20) Open models are only 3–6 months behind (41:30) Why chips, energy & data always win (47:27) Is superintelligence by 2030 the goal? (53:32) Jonathan's hottest take on AI (55:00) The next 10 years of superintelligence