{"schema":"postcutoff/event@1","as_of":"2026-11-13T13:49:00+01:00","url":"https://postcutoff.com/e/2026-09-03-pppl-pacman-fusion-ai-control/","md":"https://postcutoff.com/e/2026-09-03-pppl-pacman-fusion-ai-control/index.md","disclosure":{"written_by":"AI agents (Claude Opus 5.5 in Claude Code)","editor":"human editor","policy":"https://postcutoff.com/about/"},"license":null,"id":"2026-09-03-pppl-pacman-fusion-ai-control","date":"2026-09-03","date_precision":"day","short_title":"PPPL's PACMAN framework lets multiple AI models control a tokamak in ~20 ms, preventing a tearing mode","deck":null,"takeaway":"PPPL reported PACMAN, a modular framework that plugs several ML models directly into a tokamak's control system, reading plasma data and issuing commands in about 20 ms.","category":"science","category_label":"Science & math","importance":2,"confidence":"medium","status":{"key":"confirmed","labels":["Result confirmed"]},"sources":[{"n":1,"title":"PPPL: PACMAN AI framework makes key fusion decisions in milliseconds","url":"https://www.pppl.gov/news/2026/pacman-ai-framework-controlling-fusion-systems-safely-makes-key-decisions-milliseconds","type":"official","group":"primary","domain":"pppl.gov"},{"n":2,"title":"ScienceDaily: PACMAN AI framework for fusion","url":"https://www.sciencedaily.com/releases/2026/09/260903064215.htm","type":"press","group":"press","domain":"sciencedaily.com"},{"n":3,"title":"Phys.org: PACMAN AI framework controls fusion systems safely","url":"https://phys.org/news/2026-09-pacman-ai-framework-fusion-safely.html","type":"press","group":"press","domain":"phys.org"}],"official":1,"filed":"2026-09-29","updated":"2026-09-29","orgs":["Princeton Plasma Physics Laboratory","General Atomics"],"title":"PPPL's PACMAN framework lets multiple AI models control a tokamak in ~20 ms, preventing a tearing mode","summary":"PPPL reported PACMAN, a modular framework that plugs several ML models directly into a tokamak's control system, reading plasma data and issuing commands in about 20 ms. In five DIII-D experiments an RL model took full control of the heating systems, and the framework predicted edge bursts (ELMs), controlled fast-particle-driven waves, and predicted and prevented a tearing mode.","key_facts":["~20 ms decision loop; multiple ML models run simultaneously","5 DIII-D demonstrations incl. full RL control of heating and pre-emptive tearing-mode suppression","Humans set goals and safety limits; published in Nuclear Fusion"],"key_numbers":[],"tags":["physics","fusion","control","machine-learning"],"science":{"field":"physics","subfield":"nuclear fusion / plasma control","problem":"Integrating multiple AI predictors and controllers safely into real-time fusion operation","result":"Modular real-time AI control framework demonstrated on DIII-D across several control tasks.","open_since":"","ai_system":["PACMAN framework (RL and predictive models)"],"human_role":"Human-designed; humans set goals and safety limits","verification":{"key":"peer-review","label":"Peer-reviewed","text":"Peer-reviewed in Nuclear Fusion; hardware demonstrations"},"status":"confirmed","shock":""},"body_md":"## What happened\n\nPPPL moved from single-purpose AI controllers to a framework where several models share control of one machine in real time.\n\n## Why it matters\n\nIt is a step toward the AI-supervised operation that future power-plant tokamaks such as SPARC and ITER are expected to need.","disputed":[],"related":[{"id":"2024-02-21-ai-avoids-tokamak-tearing-instabilities","url":"https://postcutoff.com/e/2024-02-21-ai-avoids-tokamak-tearing-instabilities/","date":"2024-02-21","date_precision":"day","short_title":"AI controller predicts and avoids tearing instabilities in the DIII-D fusion reactor","deck":null,"takeaway":"Instabilities that can damage reactors are a key obstacle to fusion power.","category":"science","category_label":"Science & math","importance":3,"confidence":"high","status":{"key":"confirmed","labels":["Result confirmed"]},"sources":2,"official":1,"filed":"2026-09-29","updated":"2026-09-29","orgs":["Princeton University","Princeton Plasma Physics Laboratory","General Atomics"]},{"id":"2022-02-16-deepmind-tokamak-plasma-control","url":"https://postcutoff.com/e/2022-02-16-deepmind-tokamak-plasma-control/","date":"2022-02-16","date_precision":"day","short_title":"Deep reinforcement learning controls fusion plasma in the TCV tokamak","deck":null,"takeaway":"It showed that RL could replace complex hand-engineered control in fusion devices and opened the way to AI-designed plasma scenarios.","category":"science","category_label":"Science & math","importance":4,"confidence":"high","status":{"key":"confirmed","labels":["Result confirmed"]},"sources":2,"official":2,"filed":"2026-09-29","updated":"2026-09-29","orgs":["DeepMind","EPFL Swiss Plasma Center"]}],"people":[],"posts":[],"videos":[],"models":[],"changes":[{"date":"2026-09-29","type":"filed","text":"Created"}],"provenance":{"agents":[{"model":"Claude Opus 5.5","maker":"Anthropic","tool":"Claude Code"}],"filed":"2026-09-29","run":null,"sources_read":null,"updated":"2026-09-29","human_review":null,"version":{"date":"2026-10-04"}},"gaps":[{"model_id":"gpt-6-astra","name":"GPT-6 Astra","cutoff":"2026-04","days_after":126,"in_training_data":false},{"model_id":"claude-opus-5-5","name":"Claude Opus 5.5","cutoff":"2026-06","days_after":65,"in_training_data":false},{"model_id":"gemini-4-hydrogen","name":"Gemini 4 Hydrogen","cutoff":"2026-03","days_after":156,"in_training_data":false},{"model_id":"grok-4-7","name":"Grok 4.7","cutoff":"2026-05","days_after":95,"in_training_data":false}],"short_url":null}