V-JEPA, AI Reasoning from a Non-Generative Architecture with Mido Assran - #677

V-JEPA, AI Reasoning from a Non-Generative Architecture with Mido Assran - #677

Today we’re joined by Mido Assran, a research scientist at Meta’s Fundamental AI Research (FAIR). In this conversation, we discuss V-JEPA, a new model being billed as “the next step in Yann LeCun's vision” for true artificial reasoning. V-JEPA, the video version of Meta’s Joint Embedding Predictive Architecture, aims to bridge the gap between human and machine intelligence by training models to learn abstract concepts in a more efficient predictive manner than generative models. V-JEPA uses a novel self-supervised training approach that allows it to learn from unlabeled video data without being distracted by pixel-level detail. Mido walks us through the process of developing the architecture and explains why it has the potential to revolutionize AI. The complete show notes for this episode can be found at twimlai.com/go/677.

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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...

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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...

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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 ...

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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

The EU AI Act and Mitigating Bias in Automated Decisioning with Peter van der Putten - #699

The EU AI Act and Mitigating Bias in Automated Decisioning with Peter van der Putten - #699

Today, we're joined by Peter van der Putten, director of the AI Lab at Pega and assistant professor of AI at Leiden University. We discuss the newly adopted European AI Act and the challenges of apply...

27 Elo 202445min

The Building Blocks of Agentic Systems with Harrison Chase - #698

The Building Blocks of Agentic Systems with Harrison Chase - #698

Today, we're joined by Harrison Chase, co-founder and CEO of LangChain to discuss LLM frameworks, agentic systems, RAG, evaluation, and more. We dig into the elements of a modern LLM framework, includ...

19 Elo 202459min

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