Rethinking Pre-Training for Agentic AI with Aakanksha Chowdhery - #759

Rethinking Pre-Training for Agentic AI with Aakanksha Chowdhery - #759

Today, we're joined by Aakanksha Chowdhery, member of technical staff at Reflection, to explore the fundamental shifts required to build true agentic AI. While the industry has largely focused on post-training techniques to improve reasoning, Aakanksha draws on her experience leading pre-training efforts for Google’s PaLM and early Gemini models to argue that pre-training itself must be rethought to move beyond static benchmarks. We explore the limitations of next-token prediction for multi-step workflows and examine how attention mechanisms, loss objectives, and training data must evolve to support long-form reasoning and planning. Aakanksha shares insights on the difference between context retrieval and actual reasoning, the importance of "trajectory" training data, and why scaling remains essential for discovering emergent agentic capabilities like error recovery and dynamic tool learning. The complete show notes for this episode can be found at https://twimlai.com/go/759.

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Building AI Voice Agents with Scott Stephenson - #707

Building AI Voice Agents with Scott Stephenson - #707

Today, we're joined by Scott Stephenson, co-founder and CEO of Deepgram to discuss voice AI agents. We explore the importance of perception, understanding, and interaction and how these key components...

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Is Artificial Superintelligence Imminent? with Tim Rocktäschel - #706

Is Artificial Superintelligence Imminent? with Tim Rocktäschel - #706

Today, we're joined by Tim Rocktäschel, senior staff research scientist at Google DeepMind, professor of Artificial Intelligence at University College London, and author of the recently published popu...

21 Loka 202455min

ML Models for Safety-Critical Systems with Lucas García - #705

ML Models for Safety-Critical Systems with Lucas García - #705

Today, we're joined by Lucas García, principal product manager for deep learning at MathWorks to discuss incorporating ML models into safety-critical systems. We begin by exploring the critical role o...

14 Loka 20241h 16min

AI Agents: Substance or Snake Oil with Arvind Narayanan - #704

AI Agents: Substance or Snake Oil with Arvind Narayanan - #704

Today, we're joined by Arvind Narayanan, professor of Computer Science at Princeton University to discuss his recent works, AI Agents That Matter and AI Snake Oil. In “AI Agents That Matter”, we explo...

7 Loka 202454min

AI Agents for Data Analysis with Shreya Shankar - #703

AI Agents for Data Analysis with Shreya Shankar - #703

Today, we're joined by Shreya Shankar, a PhD student at UC Berkeley to discuss DocETL, a declarative system for building and optimizing LLM-powered data processing pipelines for large-scale and comple...

30 Syys 202448min

Stealing Part of a Production Language Model with Nicholas Carlini - #702

Stealing Part of a Production Language Model with Nicholas Carlini - #702

Today, we're joined by Nicholas Carlini, research scientist at Google DeepMind to discuss adversarial machine learning and model security, focusing on his 2024 ICML best paper winner, “Stealing part o...

23 Syys 20241h 3min

Supercharging Developer Productivity with ChatGPT and Claude with Simon Willison - #701

Supercharging Developer Productivity with ChatGPT and Claude with Simon Willison - #701

Today, we're joined by Simon Willison, independent researcher and creator of Datasette to discuss the many ways software developers and engineers can take advantage of large language models (LLMs) to ...

16 Syys 20241h 14min

Automated Design of Agentic Systems with Shengran Hu - #700

Automated Design of Agentic Systems with Shengran Hu - #700

Today, we're joined by Shengran Hu, a PhD student at the University of British Columbia, to discuss Automated Design of Agentic Systems (ADAS), an approach focused on automatically creating agentic sy...

2 Syys 202459min

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