[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-google-research":3},{"tag":4,"articles":11,"peer_article_count":57},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"096cc99c-29af-47c1-b451-7d7f10424d2d","Google Research","google-research",4,"Google Research 聚焦模型推論、提示設計與系統效率等基礎問題，從記憶體壓縮到輸入策略都會影響成本與準確率。這類研究常直接改變 AI 服務的部署方式與評估方法。","Google Research covers the core engineering behind modern AI: inference efficiency, memory compression, prompt behavior, and benchmark reliability. Its work often shapes how models are deployed, measured, and optimized in production.",[12,21,29,36,43,50],{"id":13,"slug":14,"title":15,"summary":16,"category":17,"image_url":18,"cover_image":18,"language":19,"created_at":20},"f3edd37b-2524-4d6d-b411-7ca0cce9eff0","google-deepmind-turns-science-into-tools-en","Google DeepMind turns science into tools","Google DeepMind’s science tools show how Google is packaging AI for researchers who want precision, not hype.","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782721105101-d4rm.png","en","2026-06-29T08:17:58.280652+00:00",{"id":22,"slug":23,"title":24,"summary":25,"category":26,"image_url":27,"cover_image":27,"language":19,"created_at":28},"0ac121b9-de23-42b9-94f7-fac9ea703e18","turboquant-makes-long-context-ai-cheaper-en","TurboQuant makes long-context AI much cheaper","4 ways TurboQuant’s 100x KV cache cut could lower long-context AI costs, ease GPU needs, and change model serving.","industry","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781272983524-0j31.png","2026-06-12T14:02:27.64087+00:00",{"id":30,"slug":31,"title":32,"summary":33,"category":17,"image_url":34,"cover_image":34,"language":19,"created_at":35},"9f0c9505-6d75-411c-ba46-2382e8f295a5","turboquant-cuts-kv-cache-memory-6x-google-tests-en","TurboQuant cuts KV cache memory 6x in Google tests","Google Research says TurboQuant compresses KV caches by over 4x, with up to 6x less memory and no loss on long-context tests.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780906679116-fqdo.png","2026-06-08T08:17:22.276769+00:00",{"id":37,"slug":38,"title":39,"summary":40,"category":26,"image_url":41,"cover_image":41,"language":19,"created_at":42},"bfbd028b-4704-4de5-8f54-55625836952f","5-kv-cache-takeaways-for-llamacpp-users-en","5 KV cache takeaways for llama.cpp users","5 takeaways from TurboQuant: under-3-bit KV cache compression, memory savings, and the tradeoffs llama.cpp users should watch.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779285258553-domr.png","2026-05-20T13:53:43.522918+00:00",{"id":44,"slug":45,"title":46,"summary":47,"category":17,"image_url":48,"cover_image":48,"language":19,"created_at":49},"6c80feee-7f7d-4518-bd06-3c04b8c46054","turboquant-cuts-memory-use-without-accuracy-loss-en","TurboQuant cuts memory use 6x without accuracy loss","Google Research’s TurboQuant claims 6x less memory and 8x faster inference with no accuracy loss, jolting AI inference economics.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775161136573-e0cb.png","2026-04-02T20:18:39.999171+00:00",{"id":51,"slug":52,"title":53,"summary":54,"category":17,"image_url":55,"cover_image":55,"language":19,"created_at":56},"ea6494a5-5f7a-4896-8fe8-c26737159834","duplicate-prompts-can-lift-accuracy-fast-en","Duplicate Prompts Can Lift Accuracy Fast","A Google study found repeating prompts once improved 47 of 70 model-benchmark pairs, with one task jumping from 21% to 97%.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775122510439-jn67.png","2026-04-02T08:39:34.706953+00:00",3]