Use RAG when the model’s problem is not knowing something. Use fine-tuning when the model’s problem is knowing something but not doing anything consistent with it. Most teams frame this as a single either-or decision, and that framing is the first mistake. RAG and fine-tuning fix different failure modes, and
AI model selection should not start with a leaderboard. It should start with a small evaluation set built from your own production data, because public benchmark rank rarely predicts how a model performs on your specific task distribution, and the real cost of picking wrong shows up months later as
Google may have finally shown its hand. Over the past few days, a mysterious model labeled gemini-3.8-flash quietly appeared in Arena. That name should not have caused much excitement: the real Gemini 3.8 Flash had already launched earlier in September. But once developers began testing the new Arena variant, it became
An LLM is a foundation model, but not every foundation model is an LLM. That sounds like a definitional footnote until you’re the architect who assumed a single serving stack, a single evaluation harness, or a single governance checklist would cover every model your organization deploys. It won’t, and the
人工智慧正快速重塑影片創作，使創作者與企業能以前所未有的速度製作高品質內容。隨著對 AI 驅動影片的需求持續成長，字節跳動正準備正式發布 Seedance 2.5 API，這是其下一代 AI 影片生成模型，預計於 7 月 16 日推出。
台灣台北－2026 年 7 月，SIRAYA 今日宣布正式加入 AISO（AI for Sovereignty，主權 AI）聯盟，透過加入台灣成長最快的主權 AI 生態系之一，強化其對企業 AI 基礎架構的承諾。隨著企業加速採用 AI，金融、醫療保健、政府及其他受監管產業的組織正面臨
