Microsoft Launches 7 In-House AI Models at Build 2026 to Cut OpenAI Reliance
Microsoft unveiled 7 in-house MAI models at Build 2026: MAI-Thinking-1 (35B active params, no OpenAI data) and MAI-Code-1-Flash now live in GitHub Copilot and VS Code.
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Microsoft unveiled 7 in-house MAI models at Build 2026: MAI-Thinking-1 (35B active params, no OpenAI data) and MAI-Code-1-Flash now live in GitHub Copilot and VS Code.
Google's Gemini 3 Deep Think scored 84.6% on ARC-AGI-2, 48.4% on Humanity's Last Exam, and 3455 Elo on Codeforces. Gemini 3.1 Pro is now in preview. Here is what the benchmarks actually mean.
On March 11 a mystery 1-trillion-parameter model appeared on OpenRouter. The AI community burned 500 billion tokens assuming it was DeepSeek V4. On March 19 Xiaomi revealed it was theirs.
Most RAG tutorials show you how to build a demo. This post covers what breaks in production: chunking at 512 tokens beats semantic splitting, embedding costs range from $0.02 to $0.18 per million tokens, re-ranking boosts precision by 18–42%, and agentic RAG is now the 2026 standard. A practical guide for developers shipping RAG to real users.