Topic

Prompt Engineering

Discover key takeaways from 4 podcast episodes about this topic.

Feb 6, 2026

We're All Addicted To Claude Code

AI coding agents like Claude Code are revolutionizing software development by enabling unprecedented speed and debugging capabilities, fundamentally shifting developer roles towards 'manager mode' and prioritizing bottoms-up distribution.

Y Combinator

Private Adaptations of Large Language Models

Large Language Models (LLMs)Differential Privacy (DP)Machine Learning Adaptation

Jan 27, 2026

Private Adaptations of Large Language Models

Private adaptations of open-source Large Language Models (LLMs) offer superior privacy, performance, and cost-effectiveness compared to adapting closed-source LLMs, especially for sensitive data.

Google TechTalks

Cascading Adversarial Bias from Injection to Distillation in Language Models

Large Language Models (LLMs)Retrieval Augmented Generation (RAG)Adversarial Attacks

Jan 27, 2026

Cascading Adversarial Bias from Injection to Distillation in Language Models

RAG systems, designed to enhance LLM accuracy and personalization, are vulnerable to 'Phantom' trigger attacks where a single poisoned document can manipulate outputs to deny service, express bias, exfiltrate data, or generate harmful content.

Google TechTalks

Evaluating Data Misuse in LLMs: Introducing Adversarial Compression Rate as a Metric of Memorization

Large Language Models (LLMs)Data MemorizationCopyright Infringement

Jan 27, 2026

Evaluating Data Misuse in LLMs: Introducing Adversarial Compression Rate as a Metric of Memorization

This presentation introduces Adversarial Compression Rate (ACR) as a robust metric to quantify LLM memorization, addressing copyright concerns by focusing on the shortest prompt needed to elicit exact verbatim output.

Google TechTalks