{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreiebt3ngw5rosrxyb22uknox4vc4sacviprvydkpjqkavvxym2eriu",
    "uri": "at://did:plc:7hphn7susiyrxhin6aewkmmi/app.bsky.feed.post/3mkokqbapk272"
  },
  "path": "/RBFEATURES17/",
  "publishedAt": "2026-04-29T04:24:47.000Z",
  "site": "https://risky.biz",
  "textContent": "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.\n\nJames covers:\n\n\n  High-level concept of distillation\n  Why it matters including close/open-weight/open-source explanation\n  Types of distillation and the prompts used\n  The distillation pipeline end to end\n  Distillation at scale and mitigation techniques\n  Hardware resource constraints for distillation",
  "title": "A deep dive on AI model distillation attacks"
}