Why you should write your own LLM benchmarks — with Nicholas Carlini, Google DeepMind

Latent Space: The AI Engineer Podcast

This podcast episode features Nick Carlini, a research scientist at DeepMind, who delves into the complexities of adversarial AI security and the balanced use of large language models (LLMs). Carlini combines a playful exploratory approach with rigorous analysis, promoting the understanding of AI's dual capabilities and pitfalls. He advocates for a grounded outlook on LLMs, encouraging their utilization as practical tools while remaining vigilant about their limitations, particularly in terms of security vulnerabilities. Throughout the discussion, Carlini underscores the critical need for tailored evaluation benchmarks and the exploration of AI's dark side to effectively navigate and enhance the safety of emerging technologies.

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