[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-new-method-adds-confidence-scores-to-ai-time-series-forecasts":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},7921,"new-method-adds-confidence-scores-to-ai-time-series-forecasts","New Method Adds Confidence Scores to AI Time Series Forecasts","A new technique called SGA measures how much to trust multi-step forecasts from AI time series models, and finds bigger models guess with more confidence.","A new method called SGA tells you how much to trust an AI's multi-step forecast, not just what it predicted.\n\nResearchers built a technique named Slicing-Graphing-Alignment (SGA) that measures uncertainty in time series foundation models - AI systems trained to predict sequences of future values, like demand or sensor readings, several steps ahead. The problem: these models don't just produce one forecast, they implicitly branch into a spreading tree of possible future paths, and some branches are far more accurate than others. SGA maps that branching structure as a directed graph and calculates how complex it is, combining the shape of the possible outcomes with the model's own randomness into a single uncertainty score. The team tested it against 11 different forecasting models and 27 datasets.\n\nKnowing when to distrust a forecast matters more than the forecast itself in things like inventory planning or infrastructure monitoring, where acting on a bad multi-step prediction is expensive. SGA beat existing uncertainty methods at ranking which forecasts were likely to be wrong, and it surfaced a pattern worth noting: larger forecasting models produced more confident, lower-uncertainty predictions, hinting at another scaling law layered on top of the ones already tracked for accuracy.\n\nEvery foundation model runs into the confidence-interval problem eventually - time series models are just catching up to where language models already are.","[\"ai\",\"time-series\",\"forecasting\",\"uncertainty-quantification\"]","2026-09-25T04:00:00.000Z","2026-09-26T07:07:41.124Z","2026-09-26T07:07:46.186Z","published",null,[],"ai",[24,26,27,28],"time-series","forecasting","uncertainty-quantification",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.28582",0,{"sections":35},[36,40,45,50,55,60,64,69,74,79,84,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",4624,"2026-09-25T21:57:05.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",748,"2026-09-26T01:30:00.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Policy","policy",392,"2026-09-25T18:44:30.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Deals","deals",258,"2026-09-26T09:00:00.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",185,"2026-09-25T15:00:22.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":54},"Science","science",144,{"name":65,"slug":66,"count":67,"latest_published_at":68},"Consumer Tech","consumer-tech",133,"2026-09-26T07:30:06.000Z",{"name":70,"slug":71,"count":72,"latest_published_at":73},"Software","software",90,"2026-09-25T20:55:00.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":78},"Dev Tools","dev-tools",84,"2026-09-26T04:20:58.000Z",{"name":80,"slug":81,"count":82,"latest_published_at":83},"Startups","startups",76,"2026-09-25T18:33:59.000Z",{"name":85,"slug":86,"count":87,"latest_published_at":88},"Gaming","gaming",48,"2026-09-25T18:35:21.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",46,"2026-09-25T02:12:57.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",30,"2026-09-24T20:07:31.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]