Microsoft
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The next phase of the Microsoft OpenAI partnership
OpenAI and Microsoft have announced an amended partnership agreement aimed at simplifying their relationship and providing long-term clarity. The announcement signals a structural evolution of one of the most significant commercial AI partnerships, though the body text is sparse on specific terms. The update likely reflects ongoing negotiations around compute access, revenue sharing, and OpenAI's transition toward a for-profit structure.
The next chapter of the Microsoft–OpenAI partnership
Microsoft and OpenAI have signed a new agreement to extend and strengthen their long-term partnership. The announcement emphasizes expanded innovation and responsible AI progress, though specific financial or structural terms are not detailed in the public announcement. This represents a continuation of one of the most significant commercial relationships in the AI industry.
OpenAI and Microsoft Sign New MOU Reinforcing Partnership
OpenAI and Microsoft have signed a new Memorandum of Understanding, reaffirming their strategic partnership with stated commitments to AI safety and innovation. The announcement comes from OpenAI's official blog and signals a formal continuation or restructuring of their existing relationship. The body of the announcement is brief and lacks technical or financial specifics.
OpenAI and Microsoft Extend Partnership
OpenAI and Microsoft announced an extension of their existing partnership. The announcement was published on OpenAI's blog in January 2023. No technical details about the scope, duration, or financial terms were included in the body of this item.
Microsoft Invests $1 Billion in OpenAI, Becomes Exclusive Cloud Provider
Microsoft announced a $1 billion investment in OpenAI in July 2019, establishing a strategic partnership aimed at building AGI with broadly distributed economic benefits. As part of the deal, Microsoft becomes OpenAI's exclusive cloud provider, and the two companies will jointly develop Azure AI supercomputing infrastructure. This partnership laid the foundation for OpenAI's large-scale model training on Azure and subsequent deeper integrations between the two organizations.
Claude Sonnet 4.5, Haiku 4.5, and Opus 4.1 Now Available in Microsoft Foundry and Microsoft 365 Copilot
Anthropic and Microsoft are expanding their partnership to make Claude Sonnet 4.5, Haiku 4.5, and Opus 4.1 available in public preview on Microsoft Foundry, enabling Azure customers to build production applications and enterprise agents using existing Azure agreements and billing. Claude is also being integrated into Microsoft 365 Copilot's Agent Mode in Excel, allowing users to generate formulas, analyze data, and iterate on spreadsheet solutions. The Foundry integration supports serverless deployment with Python, TypeScript, and C# SDKs, and includes capabilities such as code execution, web search, citations, vision, and prompt caching. This partnership reduces procurement friction for enterprises already invested in the Microsoft ecosystem.
Microsoft Build recap: MAI-Thinking-1 and MAI Family models announced
Microsoft unveiled MAI-Thinking-1 and the broader MAI family of models at Microsoft Build 2026, as covered in the Latent Space AINews recap. The announcement represents Microsoft's push into frontier reasoning models under its own brand, distinct from its OpenAI partnership. Technical details of the MAI model family are discussed, signaling a significant strategic move toward Microsoft-native AI model development.
Microsoft Build: Seven in-house AI models, GitHub Copilot desktop agent manager, and Web IQ search API for agents
Microsoft announced seven new AI models trained from scratch (not distilled from OpenAI), including the flagship MAI-Thinking-1 reasoning model and MAI-Transcribe-1.5, plus a 'Frontier Tuning' reinforcement learning approach for enterprise workflow training. GitHub released a desktop Copilot app designed to manage multiple parallel AI agents with isolated git worktrees and bidirectional canvases. Microsoft also launched Web IQ, an agent-native Bing-powered grounding API already powering search in Copilot and ChatGPT, running 2.5x faster than alternatives with lower token costs. The roundup also covers Nous Research's Hermes Desktop cross-platform agent app, Alibaba's Qwen3.7-Plus multimodal model, and OpenAI's role-specific Codex plugins.
Hugging Face and Microsoft Deepen Collaboration: Cloud to Developers
Hugging Face and Microsoft announced an expanded collaboration integrating Hugging Face's model hub and tools more deeply into Microsoft Azure and developer workflows. The partnership extends existing cloud integrations to make open-weight models and ML tooling more accessible via Azure infrastructure. This represents a continued strategic alignment between the leading open-source ML platform and Microsoft's cloud ecosystem.
Differential Transformer V2
Microsoft has published a blog post on Hugging Face introducing Differential Transformer V2, an updated version of their differential attention mechanism for transformers. The differential attention architecture aims to reduce attention noise by computing attention as a difference between two softmax attention maps. This post likely covers improvements to the original design, training dynamics, or scaling behavior of the V2 iteration.
Joint Statement from OpenAI and Microsoft
OpenAI and Microsoft issued a joint statement affirming their ongoing collaboration across research, engineering, and product development. The statement is brief and does not announce specific new terms, projects, or financial arrangements. It appears to be a public reaffirmation of the partnership amid ongoing speculation about the relationship's future structure.
OpenAI licenses GPT-3 technology to Microsoft
OpenAI has agreed to license GPT-3 to Microsoft for use in Microsoft's own products and services. This represents an early and significant commercial partnership between the two organizations, predating Microsoft's broader Azure OpenAI Service. The deal marks one of the first major exclusive or preferential licensing arrangements for a large language model.
OpenAI and Microsoft Begin Azure Partnership for Large-Scale AI Experiments
OpenAI announced in November 2016 that it would begin running most of its large-scale experiments on Microsoft Azure. This marks the early formation of what would become a landmark strategic partnership between the two organizations. The announcement is brief and predates the major investment rounds that later defined the relationship.
Microsoft Agent Governance Toolkit: Policy Enforcement and Zero-Trust Security for Autonomous AI Agents
Microsoft has published an open-source Agent Governance Toolkit on GitHub covering policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for autonomous AI agents. The toolkit claims full coverage of the OWASP Agentic Top 10 security risks. It has accumulated 1,828 stars with 113 added today, indicating active community interest. This positions Microsoft as a contributor to emerging standards for safe agentic AI deployment.
Data Points: China Blocks Meta-Manus Deal; Microsoft-OpenAI Restructure; Nvidia Nemotron Omni; Grok 4.3; OpenAI AGI Principles; IBM Granite 4.1
A roundup of major AI developments: Chinese regulators blocked Meta's acquisition of Singapore-based agent startup Manus on security grounds; Microsoft and OpenAI restructured their partnership, with OpenAI gaining freedom to sell on rival clouds while Microsoft loses its AGI-access clause; Nvidia released Nemotron 3 Nano Omni, a 30B MoE omnimodal open-weights model for local agent deployment; xAI shipped Grok 4.3 with a 1M-token context window at reduced pricing; OpenAI published AGI operating principles; and IBM released Granite 4.1 across language, vision, speech, embedding, and safety modalities.
Data Points: OpenAI and Microsoft sever their exclusive relationship
This edition of The Batch covers several major AI industry developments: OpenAI has revised its partnership with Microsoft, ending exclusivity while retaining Microsoft as primary cloud partner through 2032 and gaining freedom to deploy on AWS and Google Cloud. DeepSeek released V4 model weights featuring 1M-token context and Huawei Ascend chip optimization, though it trails leading open and closed models on aggregate benchmarks. Google and Amazon are deepening investments in Anthropic with up to $40B and $25B respectively in funding-for-compute deals, and an agentic AI system autonomously designed a functional RISC-V CPU from a 219-word spec in 12 hours.
Microsoft, NVIDIA, and Anthropic Announce Major Strategic Partnerships with $15B Investment and $30B Azure Compute Commitment
Anthropic has announced simultaneous strategic partnerships with Microsoft and NVIDIA, committing to purchase $30 billion of Azure compute capacity and up to one gigawatt of compute with NVIDIA Grace Blackwell and Vera Rubin systems. NVIDIA and Microsoft are investing up to $10 billion and $5 billion respectively in Anthropic, while Claude models (Sonnet 4.5, Opus 4.1, Haiku 4.5) will be available on Microsoft Foundry and across the Copilot product family. Anthropic and NVIDIA are also establishing a deep technology partnership to co-optimize model performance and future NVIDIA architectures for Anthropic workloads. Amazon remains Anthropic's primary cloud and training partner.
Simon Willison on Microsoft's new MAI models
Simon Willison covers Microsoft's release of new MAI (Microsoft AI) models. The post is commentary from a tier-2 source on a Microsoft model announcement, likely summarizing capabilities and context. Microsoft's MAI model line represents the company's continued push to develop proprietary frontier models alongside its OpenAI partnership.
Satya Nadella interviewed on Latent Space/No Priors crossover at Microsoft Build 2026
Microsoft CEO Satya Nadella appeared on a crossover episode of the Latent Space and No Priors podcasts, recorded at Microsoft Build 2026. The interview marks Nadella's first appearance on Latent Space. As a high-profile executive interview at a major developer conference, it likely covers Microsoft's AI strategy, product direction, and infrastructure investments.
Microsoft releases Fara-7B, an efficient agentic model for computer use
Microsoft has published Fara-7B, a 7-billion-parameter model designed for agentic computer use tasks, available on GitHub. The repository has accumulated 5,834 stars with 97 added today, suggesting notable community interest. The model targets efficient computer-use agent workflows, a competitive area alongside models like Claude's computer use and similar offerings.
Microsoft agent-framework: open-source library for building and orchestrating AI agents
Microsoft has published an open-source framework on GitHub for building, orchestrating, and deploying AI agents and multi-agent workflows, with support for both Python and .NET. The repository has accumulated 11,061 stars. It represents Microsoft's entry into the agent harness tooling space alongside existing frameworks like LangChain and AutoGen.
Microsoft RD-Agent: automated AI-driven R&D for data and model development
Microsoft has released RD-Agent, an open-source Python framework aimed at automating high-value R&D processes in AI, with a focus on data and model development. The project positions AI as the driver of data-driven AI workflows, targeting industrial productivity use cases. With 13,500 GitHub stars, it has attracted meaningful community interest, and a technical report is available.
Microsoft and Hugging Face Expand Collaboration on Azure AI Foundry
Microsoft and Hugging Face are deepening their partnership, with Hugging Face models and tools becoming more tightly integrated into Azure AI Foundry. This expansion likely covers model hosting, fine-tuning, and deployment capabilities within Microsoft's enterprise AI platform. The collaboration positions Azure AI Foundry as a key destination for open-weight model deployment at scale.
Hugging Face Model Catalog Launches on Azure via Microsoft Collaboration
Hugging Face and Microsoft have partnered to make Hugging Face models available through a dedicated Model Catalog on Azure. This integration allows enterprise users to deploy Hugging Face models directly within Azure infrastructure. The collaboration represents a significant distribution channel expansion for open-weight and hosted models into Microsoft's cloud ecosystem.
Microsoft Azure DevOps MCP Server
Microsoft has published an open-source Model Context Protocol (MCP) server for Azure DevOps, enabling AI agents to interact directly with Azure DevOps services. The repository is implemented in TypeScript and has accumulated 1,710 GitHub stars. This extends the MCP ecosystem with enterprise DevOps tooling, allowing agents to perform operations such as managing pipelines, work items, and repositories.
Microsoft Copilot Cowork Exfiltrates Files
Simon Willison reports on a security vulnerability in Microsoft Copilot Cowork that exfiltrates files. The item appears to document a prompt injection or data exfiltration attack vector in Microsoft's AI-powered collaboration tooling. This is relevant to AI safety and enterprise deployment risks of agentic AI assistants.
Microsoft RAMPART: pytest-native safety and security testing framework for agentic AI
Microsoft has released RAMPART, an open-source Python framework for safety and security testing of agentic AI applications, built natively on pytest. The repository is gaining traction on GitHub with 301 total stars and 77 new stars today. It targets the growing need for structured evaluation tooling specifically designed for AI agents rather than traditional software.
Tech Giants Acknowledge AI Data Center Expansion Is Undermining Climate Commitments
Alphabet, Amazon, Meta, and Microsoft have publicly acknowledged that surging AI infrastructure demand is causing them to miss or revise earlier greenhouse gas reduction pledges. All four companies have turned to natural-gas power plants to bridge energy gaps, with total emissions rising 23–60% since 2019–2020 depending on the company. Clean energy alternatives like nuclear and geothermal remain insufficiently scaled, with nuclear deployments largely deferred to the 2030s. U.S. data center electricity consumption is projected to rise from 4.4% to as much as 12% of national usage within a few years.
Microsoft VibeVoice: open-source frontier voice AI project on GitHub
Microsoft has published VibeVoice, an open-source voice AI project written in Python, which has accumulated over 48,000 GitHub stars with 219 added today. The repository is described as a 'frontier voice AI' system, though no detailed technical description is available from the source. The high star count suggests significant community interest in the project.
Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models
This Hugging Face blog post provides a technical guide for fine-tuning Microsoft's Florence-2 vision-language models. Florence-2 is a compact yet capable multimodal model supporting tasks like captioning, object detection, and OCR. The post covers practical implementation details for adapting the model to custom datasets using the Hugging Face ecosystem.
Frontier Model Forum Announces Executive Director and $10M AI Safety Fund
OpenAI, Anthropic, Google, and Microsoft jointly announced the appointment of a new Executive Director for the Frontier Model Forum and the establishment of a $10 million AI Safety Fund. The Frontier Model Forum is an industry body formed by leading AI labs to advance AI safety research and best practices. This represents a concrete financial commitment from major frontier AI developers toward safety research infrastructure.
Demystifying Data Organization for Enhanced LLM Training
This Microsoft Research paper systematically investigates how data organization—distinct from data selection—affects LLM training efficiency across pre-training and SFT stages. The authors formalize four guidelines (Boundary Sharpening, Cyclic Scheduling, Curriculum Continuity, and Local Diversity) and introduce two novel data ordering methods, STR and SAW, that reuse pre-computed sample-level scores with minimal additional overhead. Experiments across multiple model scales and dataset sizes demonstrate improved training stability and performance, with code released publicly.
Anthropic Donates Model Context Protocol to Linux Foundation, Co-founds Agentic AI Foundation
Anthropic is donating the Model Context Protocol (MCP) to the newly established Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation co-founded by Anthropic, Block, and OpenAI, with support from Google, Microsoft, AWS, Cloudflare, and Bloomberg. MCP has reached significant adoption milestones including 10,000+ active public servers, 97M+ monthly SDK downloads, and integration into ChatGPT, Gemini, Microsoft Copilot, and Visual Studio Code. The AAIF will also house Block's goose and OpenAI's AGENTS.md as founding projects, aiming to foster open, vendor-neutral standards for agentic AI. MCP governance will remain community-driven with existing maintainers continuing their roles.
OpenAI and Amazon Partner to Build Stateful Runtime Environment for AI Agents on AWS
OpenAI and Amazon Web Services announced a partnership to build a stateful runtime environment for AI agents, designed to manage agent working states including memories, tool connections, and user permissions, running on Amazon Bedrock. The deal includes a $15 billion Amazon investment in OpenAI (with up to $35 billion more contingent on conditions), a $100 billion expansion of compute commitments using Amazon Trainium chips over 8 years, and makes AWS the exclusive third-party cloud provider for OpenAI Frontier. The arrangement exploits a legal distinction between stateful runtime environments and stateless APIs, allowing OpenAI to work with AWS while Microsoft retains exclusive rights to host OpenAI's stateless API calls. This marks a significant loosening of OpenAI's exclusive cloud relationship with Microsoft, mirroring a parallel diversification trend with Anthropic across cloud providers.
Data Points: GPT-5.4 Pro, Luma Uni-1, Phi-4-reasoning-vision-15B, Yuan 3.0 Ultra, OpenAI hardware chief resignation
The Batch's weekly roundup covers several significant AI developments: OpenAI released GPT-5.4 and GPT-5.4 Pro with computer-use agent capabilities, 1M token context, and strong benchmark gains on GDPval and OSWorld-Verified; Luma AI released Uni-1, a unified autoregressive model for visual understanding and generation; Microsoft released Phi-4-reasoning-vision-15B, an open-weights multimodal model trained on 200B tokens; Yuan Lab AI released Yuan 3.0 Ultra, a 1T-parameter MoE model with SOTA on document retrieval benchmarks. Additionally, OpenAI hardware chief Caitlin Kalinowski resigned over the company's Pentagon deal, citing concerns about surveillance and autonomous weapons governance.
Microsoft BitNet: official inference framework for 1-bit LLMs trending on GitHub
Microsoft's BitNet repository, the official inference framework for 1-bit large language models, is trending on GitHub with over 39,000 total stars. The project enables efficient inference for extremely quantized models. Continued community interest signals ongoing relevance of 1-bit quantization as an inference efficiency approach.
Satya Nadella essay on building frontier AI ecosystems, covered by Latent Space
Latent Space's AI News digest covers an essay by Microsoft CEO Satya Nadella on building frontier AI ecosystems, framed around the concept of 'Loopcraft.' The piece appears to be a strategic commentary on how frontier AI ecosystems are structured and developed. As a tier-2 commentary digest, this is a secondary report on Nadella's primary essay rather than the essay itself.
U.S. Government to Pre-Release Test AI Models for National Security Risks via NIST TRAINS Task Force
NIST announced a new multi-agency task force called TRAINS (Testing Risks of AI for National Security), overseen by its Center for AI Standards and Innovation, to evaluate frontier AI models for cybersecurity, biosecurity, and chemical weapons risks before public deployment. Google, Microsoft, xAI, Anthropic, and OpenAI have voluntarily agreed to submit models with limited guardrails for evaluation. The policy shift follows Anthropic's announcement that Claude Mythos Preview can autonomously exploit software vulnerabilities, and marks a sharp reversal from the Trump Administration's earlier deregulatory stance. The White House is also considering an executive order that would make pre-release government testing mandatory.
U.S. Government to Pre-Deployment Evaluate Frontier AI Models via NIST TRAINS Task Force
The U.S. National Institute of Standards and Technology (NIST) announced a new multi-agency task force called TRAINS (Testing Risks of AI for National Security) to assess national-security risks from frontier AI models before public deployment. Major AI companies including Google, Microsoft, xAI, Anthropic, and OpenAI have agreed to submit models—including versions with limited guardrails—for evaluation focused on cybersecurity, biosecurity, and chemical weapons risks. The White House is also considering an executive order requiring pre-deployment approval for AI models. TRAINS draws on multiple federal agencies and differs from prior NIST groups in its rapid-response design, though its specific benchmarks have not been disclosed.
Accelerating over 130,000 Hugging Face Models with ONNX Runtime
Hugging Face and Microsoft have integrated ONNX Runtime (ORT) to accelerate inference for over 130,000 models on the Hugging Face Hub. The integration enables optimized deployment across CPU and GPU hardware without requiring users to manually export or configure ONNX models. This represents a significant expansion of ORT's reach within the open-weights model ecosystem, lowering the barrier to production-grade inference optimization.
Introducing ChatGPT for Excel and new financial data integrations
OpenAI is launching ChatGPT for Excel alongside new financial application integrations, powered by GPT-5.4. The product targets modeling, research, and analysis workflows in regulated environments. This represents an enterprise deployment of a new GPT-5.4 model variant into productivity and financial tooling.
Announcing The Stargate Project
OpenAI has announced the Stargate Project, a major AI infrastructure initiative. The project represents a large-scale investment in AI compute and data center infrastructure in the United States. Based on prior reporting, Stargate involves a joint venture with SoftBank and other partners targeting up to $500 billion in AI infrastructure investment over four years. This is one of the largest announced AI infrastructure commitments in history.
Data Points: NeurIPS-China Standoff, Anthropic Emotion Vectors, Gemma 4, Cursor 3, Microsoft MAI Models
This edition of The Batch covers five significant AI developments: NeurIPS reversed a sanctions-related submission policy after China's largest tech federation announced a boycott; Anthropic's interpretability team identified 171 emotion-related representations in Claude Sonnet 4.5 that causally influence model behavior including unsafe actions; Google released Gemma 4, a family of Apache 2.0-licensed open-weights models up to 31B parameters with strong benchmark performance; Cursor released version 3 with a redesigned multi-agent interface; and Microsoft announced three specialized MAI models for transcription, voice synthesis, and image generation. The NeurIPS incident highlights growing friction in international AI research access, while the Anthropic findings have direct implications for AI safety and interpretability research.
US Government Prepares AI Model Vetting System; GPT-5.5 Instant, Claude Finance Agents, Pentagon AI Partnerships
The White House is preparing an executive order to create an FDA-style vetting system for new AI models, prompted partly by Anthropic's Mythos model disclosing cybersecurity risks; the Commerce Department separately expanded a voluntary testing program with Google, Microsoft, and xAI. OpenAI rolled out GPT-5.5 Instant as the default ChatGPT model, claiming 52.5% fewer hallucinations on high-stakes prompts. Anthropic released ten financial agent templates running on Claude Opus 4.7, while the Pentagon expanded AI vendor agreements to include Microsoft, Amazon, Nvidia, and Reflection AI after canceling its Anthropic contract over autonomous weapons restrictions. Major pharma companies report AI gains primarily in manufacturing optimization rather than drug discovery breakthroughs.
Anthropic Announces SpaceX Colossus Compute Deal and Higher Claude Usage Limits
Anthropic has signed an agreement with SpaceX to access the full compute capacity of the Colossus 1 data center, gaining over 300 megawatts and 220,000+ NVIDIA GPUs within a month. This deal, combined with prior agreements with Amazon, Google/Broadcom, Microsoft/NVIDIA, and Fluidstack, enables Anthropic to double Claude Code rate limits, remove peak-hour restrictions for Pro/Max users, and raise API rate limits for Claude Opus models. The announcement also notes interest in developing orbital AI compute capacity with SpaceX, and outlines international infrastructure expansion for enterprise compliance needs.
Experimenting with Automatic PII Detection on the Hub using Presidio
Hugging Face describes an experiment integrating Microsoft's Presidio library for automatic personally identifiable information (PII) detection across datasets hosted on the Hub. The effort aims to flag or redact sensitive data before it can be used in model training pipelines. This represents a practical infrastructure-level approach to data governance and privacy compliance for open ML datasets.
A Chatbot on your Laptop: Phi-2 on Intel Meteor Lake
This post demonstrates running Microsoft's Phi-2 small language model locally on Intel Meteor Lake laptop hardware. It covers the inference pipeline, optimization techniques, and performance characteristics of deploying a 2.7B parameter model on consumer-grade NPU/CPU hardware. The piece highlights the growing feasibility of on-device LLM inference without cloud dependency.
Accelerating SD Turbo and SDXL Turbo Inference with ONNX Runtime and Olive
This Hugging Face blog post details how to accelerate Stable Diffusion Turbo and SDXL Turbo inference using ONNX Runtime and Microsoft's Olive optimization toolkit. The post covers the workflow for converting and optimizing diffusion models for faster deployment. This is a practical inference optimization guide targeting practitioners deploying image generation models.
Llama 2 is here - get it on Hugging Face
Meta released Llama 2, a new family of open-weights large language models, made available through Hugging Face. The release includes both base and fine-tuned chat variants across multiple parameter sizes. This represents a significant expansion of accessible open-weights frontier models, with Meta and Microsoft partnering on distribution.
Optimum + ONNX Runtime: Faster Training for Hugging Face Models
Hugging Face's Optimum library integrates with Microsoft's ONNX Runtime Training to accelerate fine-tuning of transformer models. The integration aims to reduce training time and memory usage with minimal code changes for practitioners using the Hugging Face ecosystem. This tooling update targets enterprise and research users looking to optimize training efficiency on existing hardware.