[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-random-puzzle-data-helps-ai-predict-molecule-properties":10,"sections":40},{"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":30,"tags":31,"sources":35,"feedback":39,"feedback_at":22,"cost_usd":39,"total_tokens":39},6580,"random-puzzle-data-helps-ai-predict-molecule-properties","Random Puzzle Data Helps AI Predict Molecule Properties","A new arXiv paper finds pretraining models on abstract procedural tasks before molecular data cuts prediction error on lipophilicity by 4.8 percent.","A new arXiv paper finds that AI models learn to predict molecule properties better when they first practice on data that has nothing to do with chemistry.\n\nIn arXiv:2609.17831, researchers built a three-stage pipeline: procedural pretraining on abstract tasks like sequence reversal, cellular automata, and graph reasoning, followed by standard molecular pretraining on SMILES strings, then fine-tuning on a specific property-prediction task. Testing on the Lipophilicity benchmark, which measures how well a molecule dissolves in fat versus water, a reverse-sequence procedural task cut test error by 4.8% compared to skipping that step. The paper's authors note that gain equals roughly 90% of the entire performance gap between their 250,000-molecule baseline and MoLFormer, a public checkpoint pretrained on about 100 million molecules. The effect was not open-ended: gains peaked at a middling amount of procedural training and shrank once the model fully converged on the procedural task.\n\nLabeled molecular data is the bottleneck in drug discovery and materials science, and most fixes just throw more unlabeled molecules at the problem. This paper suggests some of that missing structure can come from generic puzzles that cost nothing to generate, which matters most for labs with small, expensive datasets rather than millions of spare compounds.\n\nIt is not a replacement for MoLFormer-scale pretraining, more a cheap patch for labs that cannot afford one.","[\"ai\",\"machine-learning\",\"drug-discovery\",\"research\"]","2026-09-17T04:00:00.000Z","2026-09-18T01:07:09.731Z","2026-09-18T01:07:21.628Z","published",null,[24],{"id":25,"reviewer":26,"round":27,"reason":28,"status":29},"editor-r1","editor",1,"Attribute the findings to the actual source — cite the arXiv paper (e.g. arXiv:2609.17831) instead of vague 'researchers' with no institution, publication, or link given.","resolved","ai",[30,32,33,34],"machine-learning","drug-discovery","research",[36],{"name":37,"url":38},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.17831",0,{"sections":41},[42,46,50,55,60,64,68,73,78,82,87,92,97,102],{"name":43,"slug":30,"count":44,"latest_published_at":45},"AI",3852,"2026-09-17T08:27:09.000Z",{"name":47,"slug":48,"count":49,"latest_published_at":18},"Security","security",648,{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",338,"2026-09-11T04:00:00.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":18},"Hardware","hardware",154,{"name":65,"slug":66,"count":67,"latest_published_at":18},"Science","science",114,{"name":69,"slug":70,"count":71,"latest_published_at":72},"Consumer Tech","consumer-tech",99,"2026-09-09T17:27:33.000Z",{"name":74,"slug":75,"count":76,"latest_published_at":77},"Software","software",75,"2026-09-10T20:41:21.000Z",{"name":79,"slug":80,"count":81,"latest_published_at":18},"Dev Tools","dev-tools",73,{"name":83,"slug":84,"count":85,"latest_published_at":86},"Startups","startups",55,"2026-09-09T23:14:29.000Z",{"name":88,"slug":89,"count":90,"latest_published_at":91},"Gaming","gaming",43,"2026-09-10T12:18:06.000Z",{"name":93,"slug":94,"count":95,"latest_published_at":96},"General","general",41,"2026-09-08T01:57:23.000Z",{"name":98,"slug":99,"count":100,"latest_published_at":101},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":103,"slug":104,"count":105,"latest_published_at":106},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]