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56:31EN
Unsupervised Learning: With Jacob Effron· 2026년 10월 6일팟캐스트Post-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 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.모델과 학습Post-trainingReinforcement Learning+3
59:41EN
Unsupervised Learning: With Jacob Effron· 2026년 5월 22일팟캐스트The GPT moment for video hasn’t arrived, but AGI may already be here진행자 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.모델과 학습World modelsReinforcement Learning+3
47:00EN
Unsupervised Learning: With Jacob Effron· 2025년 5월 8일팟캐스트An Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a Decade진행자 Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.모델과 학습평가(Evals)Post-training+3
57:25EN
Unsupervised Learning: With Jacob Effron팟캐스트From RAG to Reasoning: Why the Future of AI Is a System, Not a Model진행자 Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.모델과 학습Reasoning & test-time computePost-training+3