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Person: "yusuf_i_mehdi"
Microsoft Build: MAI-Thinking-1 and MAI Family models, Surface RTX Spark Dev Box, and OpenClaw in Windows
mai-thinking-1 mai-code-1-flash holo-3.1 qwen-35b sonnet-4.6 claude-code codex microsoft openrouter fal baseten hcompany_ai teksedge nous-research teknim cognition windsurf perplexity-ai mixture-of-experts context-windows benchmarking reinforcement-learning prompt-optimization agentic-ai local-inference model-family-expansion model-reporting agent-native-devices software-development model-optimization hybrid-inference desktop-agents model-quantization mustafasuleyman eliebakouch hannahajishirzi asadovsky bj2rn lateinteraction lakshyaaagrawal theturingpost kimmonismus yusuf_i_mehdi pierceboggan lukehoban nielsrogge russelljkaplan
Microsoft introduced MAI-Thinking-1, a 35B parameter MoE model with 256K context, achieving 97% on AIME 2025 and outperforming Sonnet 4.6 in human preference tests. The broader 7-model MAI family spans reasoning, code, image, speech, and voice, with third-party availability on OpenRouter, fal, and Baseten. The detailed 109-page technical report revealed insights on scaling, MFU, RL/post-training, and data curation, highlighting no third-party distillation and advanced prompt optimization techniques. Microsoft emphasized agent-native devices and local inference with projects like Project Solara / Scout and the Surface RTX Spark Dev Box, alongside software innovations such as the Copilot desktop app and MAI-Code-1-Flash integration. Meanwhile, local-first computer-use agents like Holo 3.1 (Qwen-based, 0.8B to 35B parameters) support laptops and small workstations with optimized formats and strong benchmark results. Desktop shells for agents, including Hermes Desktop, Devin Desktop, and agent-neutral approaches compatible with Devin, Claude Code, and Codex, are proliferating, with hybrid local/cloud execution becoming the default architecture as seen in Perplexity Computer's hybrid agentic inference.
Nano Banana 2 aka Gemini 3.1 Flash Image Preview: the new SOTA Imagegen model
gemini-3.1-flash gpt-5.2 gpt-5.3-codex opus-4.6 claude google google-deepmind microsoft anthropic perplexity-ai image-generation text-rendering 3d-imaging real-time-information agentic-ai persistent-memory multi-agent-systems tooling coding-agents task-delegation sundarpichai demishassabis mustafasuleyman yusuf_i_mehdi borisdayma aravsrinivas
Google and DeepMind launched Nano Banana 2 (aka Gemini 3.1 Flash Image Preview), a leading image generation and editing model integrated across multiple Google products with features like 4K upscaling, multi-subject consistency, and real-time search-conditioned generation. Evaluations rank it #1 in text-to-image tasks with competitive pricing. Additionally, advances in agentic coding are noted with models like GPT-5.2, GPT-5.3 Codex, Opus 4.6, and Gemini 3.1, alongside Microsoft's Copilot Tasks introducing task delegation. Persistent memory features are rolling out in Claude models, though interoperability challenges remain.
not much happened today
gemini-1.5-pro claude-3 chatgpt langchain meta-ai-fair hugging-face openrouter google-ai microsoft openai anthropic agent-ops observability multi-turn-evaluation reinforcement-learning distributed-training api model-stability user-intent-clustering software-development project-management code-generation hwchase17 ankush_gola11 whinthorn koylanai _lewtun bhutanisanyam1 thom_wolf danielhanchen cline canvrno pashmerepat mustafasuleyman yusuf_i_mehdi jordirib1 fidjissimo bradlightcap mikeyk alexalbert__
LangSmith launched the Insights Agent with multi-turn evaluation for agent ops and observability, improving failure detection and user intent clustering. Meta PyTorch and Hugging Face introduced OpenEnv, a Gymnasium-style API and hub for reproducible agentic environments supporting distributed training. Discussions highlighted the importance of provider fidelity in agent coding, with OpenRouter's exacto filter improving stability. Builder UX updates include Google AI Studio's Annotation mode for Gemini code changes, Microsoft's Copilot Mode enhancements in Edge, and OpenAI's Shared Projects and Company Knowledge features for ChatGPT Business. Claude added project-scoped Memory. In reinforcement learning, Meta's ScaleRL proposes a methodology to predict RL scaling outcomes for LLMs with improved efficiency and stability.
Claude Agent Skills - glorified AGENTS.md? or MCP killer?
claude-4.5-haiku claude chatgpt huggingchat-omni anthropic openai microsoft perplexity-ai huggingface groq cerebras togethercompute agent-skills document-processing long-context reasoning multi-model-routing memory-management voice vision simonwillison alexalbert__ mustafasuleyman yusuf_i_mehdi aravsrinivas
Anthropic achieves a rare feat with back-to-back AI news headlines featuring Claude's new Skills—a novel way to build specialized agents using Markdown files, scripts, and metadata to handle tasks like creating and reading PDFs, Docs, and PPTs. Simon Willison calls this a "bigger deal than MCP," predicting a "Cambrian explosion in Skills." Meanwhile, Anthropic launches Claude 4.5 Haiku with strong reasoning and long-context capabilities, priced competitively. Other updates include OpenAI's ChatGPT memory management improvements, Windows 11 Copilot voice and vision features, and HuggingChat Omni routing across 115 open-source models from 15 providers. These developments highlight advances in agent skills, document processing, long-context reasoning, and multi-model routing.