The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Assessing the Risks of Open AI Models with Sayash Kapoor - #675
5 snips
Mar 11, 2024 
Sayash Kapoor, a Ph.D. student at Princeton University, discusses his research on the societal impact of open foundation models. He highlights the controversies surrounding AI safety and the potential risks of releasing model weights. The conversation delves into critical issues, such as biosecurity concerns linked to language models and the challenges of non-consensual imagery in AI. Kapoor advocates for a unified framework to evaluate these risks, emphasizing the need for transparency and legal protections in AI development.
AI Snips
Chapters
Transcript
Episode notes
Open Model Debate Evolution
- The debate around AI safety and open models has evolved since the GPT-2 release.
- Now, more powerful models are readily available, prompting discussions on openness.
Open vs. Open-Source
- Open-source implies open code, data, and documentation, distinct from open models with available weights.
- Model weight release is often irreversible and raises more concerns.
Common Ground in AI Risk Discussion
- Researchers sometimes struggle to find common ground when discussing AI risks due to differing interpretations.
- Clear definitions and frameworks are needed for constructive dialogue and risk mitigation strategies.