Crypto researcher Green: multiple scientists suspect AI models train on their inputs
matthew_d_green · x · 2026-09-09
Matthew Green, cryptographer at Johns Hopkins, said multiple researchers in his field have noticed models getting much better at solving their specific problems over short periods—even when asked in new contexts. Several have wondered whether the models are being trained on their inputs. The claim remains anecdotal and unconfirmed, but touches the sensitive question of whether user data flows into model training.
Related event: Researchers Suspect OpenAI Secretly Trains on Their Inputs(13 posts)→
More from Models
- ChatGPT Voice gets usage caps: 3h for Plus, 15h for Pro $100, $200 stays unlimited — testingcatalog · 2026-09-10
- VDiff-Bench: 1,756-question benchmark shows frontier models fail at spot-the-difference — yixin_wan_ · 2026-09-10
- OpenAI team points users to official usage limit update details — athyuttamre · 2026-09-10
- MiniCPM5-2B: 2B-parameter open model runs agents offline on 2GB RAM, tops sub-4B open models — solyarisoftware · 2026-09-10
- ChatGPT Voice gains GPT-5.6 Sol and GPT-6 Astra, Plus/Pro usage limits raised — athyuttamre · 2026-09-10
- Rumor: DeepSeek V4.1 Flash to launch ~Sept 10, V4 Pro requests rerouted at Flash pricing — solyarisoftware · 2026-09-10