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Ep 44: Co-Founder of Together.AI Percy Liang on What’s Next in Research, Reaction to o1 and How AI will Change Simulation
Manage episode 443342863 series 3495253
Percy Liang is a Stanford professor and co-founder of Together AI, driving some of the most critical advances in AI research.
Percy is also a trained classical pianist, which clearly influences the way he thinks about technology. We explored the evolution of AI from simple token prediction to autonomous agents capable of long-term problem-solving, the problem of interpretability, and the future of AI safety in complex, real-world systems.
[0:00] Intro
[0:46] Discussing OpenAI's O1 Model
[2:21] The Evolution of AI Agents
[3:27] Challenges and Benchmarks in AI
[4:38] Compatibility and Integration Issues
[6:17] The Future of AI Scaffolding
[10:05] Academia's Role in AI Research
[15:17] AI Safety and Holistic Approaches
[18:32] Regulation and Transparency in AI
[21:42] Generative Agents and Social Simulations
[29:14] The State of AI Evaluations
[32:07] Exploring Evaluation in Language Models
[35:13] The Challenge of Interpretability
[39:31] Innovations in Model Architectures
[43:18] The Future of Inference and Customization
[46:46] Milestones in AI Research and Reasoning
[49:43] Robotics and AI: The Road Ahead
[52:24] AI in Music: A Harmonious Future
[55:52] AI's Role in Education and Beyond
[56:30] Quickfire
[59:16] Jacob and Pat Debrief
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint
52 つのエピソード
Manage episode 443342863 series 3495253
Percy Liang is a Stanford professor and co-founder of Together AI, driving some of the most critical advances in AI research.
Percy is also a trained classical pianist, which clearly influences the way he thinks about technology. We explored the evolution of AI from simple token prediction to autonomous agents capable of long-term problem-solving, the problem of interpretability, and the future of AI safety in complex, real-world systems.
[0:00] Intro
[0:46] Discussing OpenAI's O1 Model
[2:21] The Evolution of AI Agents
[3:27] Challenges and Benchmarks in AI
[4:38] Compatibility and Integration Issues
[6:17] The Future of AI Scaffolding
[10:05] Academia's Role in AI Research
[15:17] AI Safety and Holistic Approaches
[18:32] Regulation and Transparency in AI
[21:42] Generative Agents and Social Simulations
[29:14] The State of AI Evaluations
[32:07] Exploring Evaluation in Language Models
[35:13] The Challenge of Interpretability
[39:31] Innovations in Model Architectures
[43:18] The Future of Inference and Customization
[46:46] Milestones in AI Research and Reasoning
[49:43] Robotics and AI: The Road Ahead
[52:24] AI in Music: A Harmonious Future
[55:52] AI's Role in Education and Beyond
[56:30] Quickfire
[59:16] Jacob and Pat Debrief
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint
52 つのエピソード
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