Episode
A deep dive on AI model distillation attacks
- Podcast
- Risky Business Features
- Published
- Apr 29, 2026
- Duration seconds
- 4328
- Processing state
not_requested- Canonical source
- https://risky.biz/RBFEATURES17/
Actions
POST https://stenobird.com/v1/public/podcasts/risky-business-features-7716365/episodes/a-deep-dive-on-ai-model-distillation-attacks/transcription-requests
Idempotently request low-priority transcript generation for this episode.GET https://stenobird.com/podcast/risky-business-features-7716365/a-deep-dive-on-ai-model-distillation-attacks.md
Read the agent-friendly Markdown representation of this episode resource.
Summary
In this solo episode of Risky Business Features James Wilson explores how distillation techniques are both a legitimate way to train smaller models, as well as a way to steal model capabilities. It’s not just a problem for frontier labs! Any LLM-based product could have its competitive advantage stolen through these attacks. James covers: High-level concept of distillation Why it matters including close/open-weight/open-source explanation Types of distillation and the prompts used The distillation pipeline end to end Distillation at scale and mitigation techniques Hardware resource constraints for distillation