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56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabHost Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
59:41ENThe GPT moment for video hasn’t arrived, but AGI may already be hereHost Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
58:46ENTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Host Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGIHost Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
1:02:05EN$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the MathHost Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
57:31ENThe New Ruler for Models Is How Long They Can WorkHost Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.
44:34ENThe Cheaper Intelligence Gets, the More of It We'll BuyHost Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.









