Privacy and Security for Stable Diffusion and LLMs with Nicholas Carlini - #618

Privacy and Security for Stable Diffusion and LLMs with Nicholas Carlini - #618

Today we’re joined by Nicholas Carlini, a research scientist at Google Brain. Nicholas works at the intersection of machine learning and computer security, and his recent paper “Extracting Training Data from LLMs” has generated quite a buzz within the ML community. In our conversation, we discuss the current state of adversarial machine learning research, the dynamic of dealing with privacy issues in black box vs accessible models, what privacy attacks in vision models like diffusion models look like, and the scale of “memorization” within these models. We also explore Nicholas’ work on data poisoning, which looks to understand what happens if a bad actor can take control of a small fraction of the data that an ML model is trained on. The complete show notes for this episode can be found at twimlai.com/go/618.

Jaksot(779)

Building the Internet of Agents with Vijoy Pandey - #737

Building the Internet of Agents with Vijoy Pandey - #737

Today, we're joined by Vijoy Pandey, SVP and general manager at Outshift by Cisco to discuss a foundational challenge for the enterprise: how do we make specialized agents from different vendors colla...

24 Kesä 202556min

LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736

LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736

Today, we're joined by Ben Wellington, deputy head of feature forecasting at Two Sigma. We dig into the team’s end-to-end approach to leveraging AI in equities feature forecasting, covering how they i...

17 Kesä 202559min

Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735

Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735

Today, we're joined by Jason Corso, co-founder of Voxel51 and professor at the University of Michigan, to explore automated labeling in computer vision. Jason introduces FiftyOne, an open-source platf...

10 Kesä 202556min

Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734

Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734

Today, we're joined by Charles Martin, founder of Calculation Consulting, to discuss Weight Watcher, an open-source tool for analyzing and improving Deep Neural Networks (DNNs) based on principles fro...

5 Kesä 20251h 25min

Google I/O 2025 Special Edition - #733

Google I/O 2025 Special Edition - #733

Today, I’m excited to share a special crossover edition of the podcast recorded live from Google I/O 2025! In this episode, I join Shawn Wang aka Swyx from the Latent Space Podcast, to interview Logan...

28 Touko 202526min

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-...

21 Touko 202557min

From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731

From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731

Today, we're joined by Mahesh Sathiamoorthy, co-founder and CEO of Bespoke Labs, to discuss how reinforcement learning (RL) is reshaping the way we build custom agents on top of foundation models. Mah...

13 Touko 20251h 1min

How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730

How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730

Today, we're joined by Josh Tobin, member of technical staff at OpenAI, to discuss the company’s approach to building AI agents. We cover OpenAI's three agentic offerings—Deep Research for comprehensi...

6 Touko 20251h 7min

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