[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-chaos-makes-ai-better-at-finding-physics-equations":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},4150,"chaos-makes-ai-better-at-finding-physics-equations","Chaos Makes AI Better at Finding Physics Equations","A new paper argues that chaotic systems are actually easier for AI to reverse-engineer from data — and stable, predictable ones may be nearly impossible.","The systems hardest to predict turn out to be the easiest for AI to learn from scratch.\n\nResearchers publishing on arXiv have worked out a formal answer to a question that has nagged data-driven science for years: when can an AI actually recover a system's governing equations from observations alone? The answer hinges on chaos. Systems that exhibit chaotic behavior across their entire domain can, in principle, be uniquely identified from a single observed trajectory. The classical Lorenz system — a textbook example of chaos — is proven here to be analytically discoverable for the first time. Systems that are merely chaotic on a strange attractor can also be recovered, provided a specific geometric condition holds.\n\nThe flip side is the harder news. Stable, predictable systems — the kind engineers rely on for digital twins, robotics, and structural modeling — are often not discoverable from trajectory data alone. If a system has conserved quantities called first integrals, unique identification from data is mathematically impossible without additional prior knowledge baked in. That quietly undermines a lot of the confidence placed in purely data-driven modeling for engineering applications.\n\nThe finding reframes why weather forecasting has been such a productive target for machine learning: the atmosphere is chaotic, which turns out to be a feature for discoverability, not just a bug for prediction. For the tidy, well-behaved systems engineers actually want to simulate, more data is not the answer — the approach itself needs to change.","[\"ai\",\"science\",\"machine-learning\",\"data-driven-modeling\"]","2026-07-07T04:00:00.000Z","2026-07-07T18:20:28.250Z","2026-07-07T18:20:31.248Z","published",null,[],"science",[26,24,27,28],"ai","machine-learning","data-driven-modeling",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2511.08860",0,{"sections":35},[36,40,45,50,55,60,65,70,74,78,83,87,92,97],{"name":37,"slug":26,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":24,"count":72,"latest_published_at":73},"Science",66,"2026-07-10T10:29:37.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":18},"Dev Tools","dev-tools",59,{"name":79,"slug":80,"count":81,"latest_published_at":82},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":84,"slug":85,"count":81,"latest_published_at":86},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":88,"slug":89,"count":90,"latest_published_at":91},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":93,"slug":94,"count":95,"latest_published_at":96},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":98,"slug":99,"count":100,"latest_published_at":101},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]