[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-ai":3},{"tag":4,"articles":11},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"e2cd42e5-835a-4847-b351-8f5b3f5ea059","AI","ai",5,"AI 不只是模型能力的競賽，也牽涉到企業治理、裝置端推論、資料可信度與評測透明度。從內部工具失控、Siri 重啟到連續學習與測試造假，這個標籤聚焦 AI 如何進入產品、流程與基礎設施。","AI here is treated as a systems problem, not just a model benchmark race: governance, on-device inference, data provenance, and evaluation integrity all matter. Topics include tool sprawl inside enterprises, Siri and other product integrations, continuous learning, and disputed test results.",[12,21],{"id":13,"slug":14,"title":15,"summary":16,"category":17,"image_url":18,"cover_image":18,"language":19,"created_at":20},"1e430f5b-88ba-4469-bcb5-a06dd17cf2af","ai-continuous-learning-2026-en","AI's Leap to Continuous Learning by 2026","Google DeepMind predicts AI will achieve continuous learning by 2026, marking a major milestone in AI's evolution and potential for automation.","industry","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1774499608764-9y41.png","en","2026-03-26T01:30:58.279383+00:00",{"id":22,"slug":23,"title":24,"summary":25,"category":17,"image_url":26,"cover_image":26,"language":19,"created_at":27},"6e18bc65-42ae-4ad0-b564-67d7f66b979e","meta-llama4-fabricated-results-scandal-en","Meta's Llama 4 Scandal: Fabricated AI Test Results Unveiled","Meta's latest AI model, Llama 4, faced backlash after it was revealed test results were fabricated, casting doubt on the company's AI integrity.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1774497697541-3yx0.png","2026-03-25T16:29:15.482836+00:00"]