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
Artificial intelligence is rapidly reshaping video creation, enabling creators and enterprises to produce high-quality content faster than ever before. As demand for AI-powered video continues to grow, ByteDance is preparing the official API release of Seedance 2.5, the next generation of its AI video generation model, expected on July 16.
Taipei, Taiwan – July 2026, SIRAYA today announced its official membership in the AISO (AI for Sovereignty) Alliance, strengthening its commitment to enterprise AI infrastructure by joining one of Taiwan’s fastest-growing sovereign AI ecosystems. As enterprises accelerate AI adoption, organizations across finance, healthcare, government, and other regulated industries are facing
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