RAG Risks: Why Retrieval-Augmented LLMs are Not Safer with Sebastian Gehrmann - #732

RAG Risks: Why Retrieval-Augmented LLMs are Not Safer with Sebastian Gehrmann - #732

Today, we're joined by Sebastian Gehrmann, head of responsible AI in the Office of the CTO at Bloomberg, to discuss AI safety in retrieval-augmented generation (RAG) systems and generative AI in high-stakes domains like financial services. We explore how RAG, contrary to some expectations, can inadvertently degrade model safety. We cover examples of unsafe outputs that can emerge from these systems, different approaches to evaluating these safety risks, and the potential reasons behind this counterintuitive behavior. Shifting to the application of generative AI in financial services, Sebastian outlines a domain-specific safety taxonomy designed for the industry's unique needs. We also explore the critical role of governance and regulatory frameworks in addressing these concerns, the role of prompt engineering in bolstering safety, Bloomberg’s multi-layered mitigation strategies, and vital areas for further work in improving AI safety within specialized domains. The complete show notes for this episode can be found at https://twimlai.com/go/732.

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Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724

Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724

Today, we're joined by Julie Kallini, PhD student at Stanford University to discuss her recent papers, “MrT5: Dynamic Token Merging for Efficient Byte-level Language Models” and “Mission: Impossible L...

24 Mars 202550min

Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723

Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723

Today, we're joined by Jonas Geiping, research group leader at Ellis Institute and the Max Planck Institute for Intelligent Systems to discuss his recent paper, “Scaling up Test-Time Compute with Late...

17 Mars 202558min

Imagine while Reasoning in Space: Multimodal Visualization-of-Thought with Chengzu Li - #722

Imagine while Reasoning in Space: Multimodal Visualization-of-Thought with Chengzu Li - #722

Today, we're joined by Chengzu Li, PhD student at the University of Cambridge to discuss his recent paper, “Imagine while Reasoning in Space: Multimodal Visualization-of-Thought.” We explore the motiv...

10 Mars 202542min

Inside s1: An o1-Style Reasoning Model That Cost Under $50 to Train with Niklas Muennighoff - #721

Inside s1: An o1-Style Reasoning Model That Cost Under $50 to Train with Niklas Muennighoff - #721

Today, we're joined by Niklas Muennighoff, a PhD student at Stanford University, to discuss his paper, “S1: Simple Test-Time Scaling.” We explore the motivations behind S1, as well as how it compares ...

3 Mars 202549min

Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720

Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720

Today, we're joined by Ron Diamant, chief architect for Trainium at Amazon Web Services, to discuss hardware acceleration for generative AI and the design and role of the recently released Trainium2 c...

24 Feb 20251h 7min

π0: A Foundation Model for Robotics with Sergey Levine - #719

π0: A Foundation Model for Robotics with Sergey Levine - #719

Today, we're joined by Sergey Levine, associate professor at UC Berkeley and co-founder of Physical Intelligence, to discuss π0 (pi-zero), a general-purpose robotic foundation model. We dig into the m...

18 Feb 202552min

AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718

AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718

Today we’re joined by Victor Dibia, principal research software engineer at Microsoft Research, to explore the key trends and advancements in AI agents and multi-agent systems shaping 2025 and beyond....

10 Feb 20251h 44min

Speculative Decoding and Efficient LLM Inference with Chris Lott - #717

Speculative Decoding and Efficient LLM Inference with Chris Lott - #717

Today, we're joined by Chris Lott, senior director of engineering at Qualcomm AI Research to discuss accelerating large language model inference. We explore the challenges presented by the LLM encodin...

4 Feb 20251h 16min

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