Coercing LLMs to Do and Reveal (Almost) Anything with Jonas Geiping - #678

Coercing LLMs to Do and Reveal (Almost) Anything with Jonas Geiping - #678

Today we're joined by Jonas Geiping, a research group leader at the ELLIS Institute, to explore his paper: "Coercing LLMs to Do and Reveal (Almost) Anything". Jonas explains how neural networks can be exploited, highlighting the risk of deploying LLM agents that interact with the real world. We discuss the role of open models in enabling security research, the challenges of optimizing over certain constraints, and the ongoing difficulties in achieving robustness in neural networks. Finally, we delve into the future of AI security, and the need for a better approach to mitigate the risks posed by optimized adversarial attacks. The complete show notes for this episode can be found at twimlai.com/go/678.

Episoder(779)

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...

7 Okt 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...

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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 Sep 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 Sep 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 Sep 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 Aug 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 Aug 202459min

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