[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fbLZxnms4SeOr-4p3cE3CFsc1ckq95yvvyuQU2m7peuk":3},{"articles":4,"pagination":79},[5,16,27,37,48,59,69],{"id":6,"slug":7,"title":8,"seo_title":8,"description":9,"keywords":10,"category":11,"image_url":12,"source_guid":13,"published_at":14,"created_at":15},1327,"caterpillar-brings-mining-automation-expertise-to-ai-deployment","Caterpillar puts AI into repairs, plans $100M in training","Caterpillar described AI tools for field repairs and a $100 million workforce training plan. Its experience raises concrete questions about workflow changes.","[\"Caterpillar\",\"Cat AI Assistant\",\"mining automation\",\"workforce training\",\"industrial AI\"]","AI & Machine Learning","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1788134450538-0nzykxlt0lp.png","a95d146367fb970b0dcc4f2bae9dbcc7afa81d7f9c235e15a5acf01267e425f4","2026-08-30T15:00:00.000Z","2026-08-31T00:00:51.574Z",{"id":17,"slug":18,"title":19,"seo_title":19,"description":20,"keywords":21,"category":22,"image_url":23,"source_guid":24,"published_at":25,"created_at":26},1326,"nvidia-expands-ai-advantage-beyond-gpus","Nvidia’s Vera Rubin Push Extends to Data Movement","Nvidia’s Vera Rubin rollout pairs GPUs with supporting hardware, raising a practical question for AI buyers: which gains carry through to real workloads?","[\"Nvidia\",\"Vera Rubin\",\"AI infrastructure\",\"data centers\",\"GPU competition\",\"data orchestration\"]","Enterprise Tech","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1788048048873-uqi8em9u828.png","384ec9f64f15638616fead0b99d68d94f90ef6f38f3507e5c445979f69376933","2026-08-29T13:00:00.000Z","2026-08-30T00:00:50.954Z",{"id":28,"slug":29,"title":30,"seo_title":30,"description":31,"keywords":32,"category":22,"image_url":33,"source_guid":34,"published_at":35,"created_at":36},1325,"anthropic-researcher-shares-insights-on-self-improving-ai","Anthropic paper reports automated alignment benchmark gains","An Anthropic paper reported gains on 10 alignment benchmarks. The findings suggest a research tool, but leave benchmark quality and full costs unresolved.","[\"Anthropic\",\"automated alignment\",\"AI research\",\"alignment benchmarks\",\"recursive self-improvement\"]","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1787961730562-26zw15cglbb.png","decbef16660c414e999fa88c3646fa030f71ce11b4b6225201ecca27c43fe876","2026-08-28T19:30:38.000Z","2026-08-29T00:02:12.299Z",{"id":38,"slug":39,"title":40,"seo_title":40,"description":41,"keywords":42,"category":43,"image_url":44,"source_guid":45,"published_at":46,"created_at":47},1322,"openais-jalapeo-chip-shows-fast-inference-at-scale","OpenAI reports Jalapeño inference gains, with rollout to follow","OpenAI reported faster, more power-efficient inference with Jalapeño. Its deployment timeline and missing benchmark detail limit what AI buyers can conclude.","[\"OpenAI\",\"Jalapeño\",\"inference chips\",\"Broadcom\",\"InferenceX\",\"AI hardware\"]","Gadgets & Hardware","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1787702487045-retumd9ylw.png","4ad5712beaaf675fd4ec3094a31992bf8107fd5adc7164846ba6b51ac294653f","2026-08-25T14:22:04.000Z","2026-08-26T00:01:28.537Z",{"id":49,"slug":50,"title":51,"seo_title":51,"description":52,"keywords":53,"category":54,"image_url":55,"source_guid":56,"published_at":57,"created_at":58},1321,"instinct-ai-raises-privacy-concerns","Instinct testers flagged email retention and approval gaps","Instinct testers reported retained emails and an unapproved send during private access. A reported deletion fix left broader questions about user control.","[\"Instinct\",\"AI assistants\",\"email privacy\",\"data retention\",\"agent permissions\"]","Cybersecurity","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1787616063348-8l06mq1u9nl.png","e0143f35293dbf1c69dc94cc8d238a70cb6408ff643e9c62ae1630da5ebe4979","2026-08-24T18:03:55.000Z","2026-08-25T00:01:04.566Z",{"id":60,"slug":61,"title":62,"seo_title":62,"description":63,"keywords":64,"category":11,"image_url":65,"source_guid":66,"published_at":67,"created_at":68},1323,"mit-introduces-seal-framework-for-self-improving-ai","MIT’s SEAL learns to generate training data for model updates","MIT’s SEAL uses reinforcement learning to improve model-generated training data. Reported gains raise practical questions about evaluation and retained skills.","[\"MIT\",\"SEAL\",\"reinforcement learning\",\"model adaptation\",\"synthetic training data\"]","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1787788871268-0ywl6o81a2b.png","a275a0122cdbda6f28141dd3fa33b5d74b98bad9f62703a94ea9e5b1675ea78e","2025-06-16T12:58:37.000Z","2026-08-27T00:01:12.124Z",{"id":70,"slug":71,"title":72,"seo_title":72,"description":73,"keywords":74,"category":11,"image_url":75,"source_guid":76,"published_at":77,"created_at":78},1324,"psu-duke-researchers-introduce-automated-failure-attribution-for-multi-agent-systems","Who&When benchmark tests AI agents’ ability to diagnose failure","Researchers introduced a benchmark for diagnosing multi-agent AI failures. Reported accuracy exposes limits for teams considering automated debugging tools.","[\"multi-agent systems\",\"Who&When\",\"failure attribution\",\"AI debugging\",\"Penn State\",\"Duke\"]","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1787875560634-d7yulfyjl7.png","f275f83487eab0ff1cd108a30e751f814aae79a4b8eaf6fb2b4d59d5bf226c37","2025-06-16T07:39:46.000Z","2026-08-28T00:06:01.354Z",{"limit":80,"hasMore":81,"nextCursor":82,"page":83},24,false,"2025-06-16T07:39:46.000Z_1324",3]