In Nature this week, Satya Nadella says his organization’s new research shows how machine learning can improve weather forecasts two to six weeks out, a timeframe that has historically been very difficult to predict. He highlights the work’s potential to help people better prepare for extreme weather.
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We now have state-of-the-art pre-trained base models in the 3T-parameter weight class, built entirely in-house at MAI. Post-training results coming soon—stay tuned! Lots of details in our technical blog post. https://microsoft.ai/news/frontier-pre-training-at-microsoft-ai/
Why it matters: The announcement places MAI’s reported progress at the pre-training stage, with post-training results still forthcoming, providing context for interpreting its claim of state-of-the-art base models.
Microsoft Research presents Magnetar, a zero-knowledge virtual machine that proves RISC-V program execution using security based only on standard hash functions. It supports programs written in Rust, Go, or C without requiring developers to rewrite them as cryptographic circuits. Across 15 benchmark programs, Microsoft reports average speeds 10 to 39 times faster than the fastest existing comparable zkVMs on the same machine, with proofs verified in about 12 milliseconds.
Why it matters: The benchmark comparisons connect proving speed with general-purpose execution and standard hash functions, clarifying the tradeoffs that have limited broader adoption of verifiable computing.
Microsoft has optimized Windows for Nvidia’s Arm-based RTX Spark laptops through easier AI agent installation, tuned Prism emulation, and unified memory improvements. Tom Warren found Hermes setup mostly took two clicks, while OpenClaw required reinstallation and large local models responded more slowly than cloud models. Copilot Plus PC features, including Recall, are unavailable at launch, with initial Windows Insider availability expected later this year.
Epic released a publicly available Preview of its rebuilt Epic Games Launcher, describing it as faster and more responsive than the current version, with a new look. Epic Games Store General Manager and VP Martin Keely said the team used AI to write and review features from scratch in a different tech stack. He said this helped a small team rewrite the code base faster for Windows and Mac, with a Linux version also planned.
Microsoft researchers and collaborators published research in Nature on Probabilistic Bias Correction (PBC), an open-source machine learning tool that corrects systematic bias in existing weather models to improve forecasts two to six weeks ahead. In the study, PBC improved ECMWF’s physics-based model accuracy for 98 percent of precipitation and 92 percent of temperature targets, and doubled the accuracy of its AI forecasting system. The tool can run on CPUs, though ECMWF cautioned that operational implementation remains challenging.
Aravind Srinivas describes a user's project in which Perplexity Computer ported a Windows-only mechanical keyboard app with no Linux support or documentation to a native Rust app for Linux. Computer downloaded the binary in its cloud sandbox, decompiled it with headless Ghidra, and read the code to understand how it drives the keyboard. It rebuilt the app piece by piece with music-synced lighting over PipeWire, a 3D view, key remapping, macros, and profiles. https://www.reddit.com/r/GeminiAI/comments/1x4vvoi/my_mechanical_keyboards_software_only_runs_on/ https://github.com/trenbolone1122/aula-f75-linux
Tencent released integrated versions of WeCom and WorkBuddy on October 14, connecting workplace context through a shared WeCom account system. WeCom 5.0.12 adds WorkBuddy as a conversational bot in enterprise contacts, while WorkBuddy 5.8.0 supports WeCom login and authorized access to messages, documents, meetings, and cloud storage. Administrators can manage accounts, usage, AI compute purchases, and access permissions; integration is available to verified WeCom enterprises with limited free trial slots.
Microsoft is forming Xbox Labs, a small group of game makers, engineers, and scientists, to explore emerging game ports and remixes assisted by AI models. Xbox CEO Asha Sharma says the group will build openly and share tools with developers across the industry. Tom Warren raises questions about unauthorized use of Microsoft’s IP; the company did not respond to his request for comment before publication.
GitHub explains how its secret scanning pipeline combines regex candidate detection with a fine-tuned ModernBERT classifier to distinguish real credentials from lookalikes using surrounding context. Compared with the previous LLM pipeline, offline evaluation showed 13% higher precision and 19% higher recall; a customer A/B experiment showed 11.5% higher repository owner-weighted acceptance. Median post-push scan execution time fell 86%, and serving costs dropped more than 98%, making it practical to extend generic secret detection to push protection.
Why it matters: GitHub’s pipeline illustrates a transferable design pattern for narrow classification tasks, combining deterministic candidate generation with a compact contextual model trained on realistic hard negatives.
GitHub’s beginner guide explains four ways to tailor Copilot to a project: custom instructions for repository conventions, agent skills for repeatable procedures, custom agents for broader specialized tasks, and MCP servers for connecting to external tools and data. It recommends starting with a convention you often explain and adding it to `.github/copilot-instructions.md`.
Microsoft Research introduces StudentSim, a research system that trains personalized student simulators from publicly available, de-identified learner records to evaluate and improve AI tutors. StudentSimEval measures behavioral fidelity and guidance responsiveness across chess, second-language English writing, and mathematics, where StudentSim outperforms leading baselines. In a chess tutor study, training with StudentSim feedback achieves 90.5% accuracy versus 75.7% without reinforcement learning and 71.6% with GPT-5.4 feedback; real learner studies remain essential, and the paper and code are publicly available.
Why it matters: Evaluating both a simulated learner’s starting ability and response to guidance offers a concrete method for assessing tutor feedback beyond the correctness of an explanation.
A Microsoft Research study reports that Fork-and-Flush helps long-running AI research agents explore better solutions by creating parallel branches that retain workspace files but discard chat history. Across 13 tasks with the same compute budget, it achieved a min-max-normalized average score of 0.78, versus 0.47 for single runs and 0.54 for best-of-4. The researchers found that accumulated context can trap agents in similar approaches, even when conversation histories are periodically compressed.
Microsoft President Brad Smith called for urgent global AI safety rules, arguing that the U.K. is better positioned to lead than the U.S. or European Union. He said voluntary self-regulation lets responsible companies comply while leaving less responsible ones a concern. Smith supports legal breach reporting for rogue AI agents and spoke positively about outside evaluations before release and kill switches to pause or slow AI systems.
NVIDIA contributed Vera Rubin rack and compute tray designs to OCP through its open MGX architecture and launched open source components for DSX AI Factory. MGX 1.2 supports rack deployments up to 250kW and adds standardized power, cooling and interconnect interfaces. NVIDIA and partners also announced facility and grid resilience specifications, Meta’s adoption of Spectrum-6 switches, plans for USFP optical modules with Cisco, and Falcon Transport support on future ConnectX-10 SuperNICs and BlueField DPUs with Google.
Why it matters: The specifications show how shared rack, cooling, power and software interfaces can give infrastructure builders a common implementation target as AI factories scale to higher power densities.
Microsoft plans to deploy Azure Maia AI chips at multi-gigawatt scale starting in 2027, making them its main inference system across its products, executive Scott Guthrie writes. Maia 200 already runs Microsoft Copilot in the US, Europe, and Australia, with GitHub Copilot and Foundry following by year's end. Maia 300 ships in 2027 for long inputs, fast chats, and agentic tasks; Microsoft claims 40 percent more tokens per megawatt than leading GPU systems and up to seven times the tokens per 96-chip rack compared with a Maia 200 rack.
Mustafa Suleyman calls Microsoft’s new silicon 🔥 and highlights “40% more tokens per watt!” In the quoted announcement, Satya Nadella says Maia 300 delivers 40% more tokens per watt than leading GPU-based systems, with multi-gigawatt Maia deployments planned starting next calendar year as the primary inference system for Microsoft’s products and services. He says Maia 200 is already being deployed across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across Teams and Copilot experiences. https://twitter.com/satyanadella/status/2109631106404487523
Microsoft announced Maia 300, its third-generation in-house AI chip, with production rollout starting in 2027 and plans to make Maia its primary AI inference system. Microsoft expects 40 percent more tokens per megawatt than leading GPU-based systems and up to 7x Maia 200’s rack-scale token throughput in a full 96-accelerator configuration. Built on TSMC’s N2P process node, Maia 300 separates compute, memory controller, and I/O functions through a new chiplet architecture.
Microsoft is introducing Maia 300, which Satya Nadella says delivers 40% more tokens per watt compared to leading GPU-based systems. Starting next calendar year, Microsoft will scale its Maia family to multi-gigawatt deployments, making it the primary inference system for its own products and services. Microsoft is already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot, with a goal of building on full-stack efficiency gains while continuing to bring ecosystem innovations into its fleet.
Why it matters: Making Maia the primary inference system for Microsoft’s own products and services gives its stated efficiency gains a concrete deployment context.
Microsoft released Microsoft-Decision-1, a decision model post-trained from Qwen3.5-9B, and says it outperforms LLMs and decision models including Jev 1.13.0 on latency and accuracy in structured decision tasks. Its Xbox research team has used it to process more than 10,000 player feedback entries, while CEO Satya Nadella says Microsoft is testing applications across domains, including incident response, quality control, and scientific discovery. The report describes decision models as smaller, faster models that output predictions, probabilities, and confidence scores rather than natural language.
Baoyu summarizes Microsoft CEO Satya Nadella’s argument that enterprises should manage AI models as insider risks, with identities, restricted permissions, audit records, and controls to halt operations. Nadella outlines seven principles covering model diversity, observability, verification, independent control and auditing, containment, and incident disclosure. He calls for disclosing chains of thought while acknowledging that they may not faithfully reflect model reasoning, and argues that security controls must operate outside the model.
Some of Silicon Valley's most powerful figures are falling in line with President Donald Trump's push to rebrand artificial intelligence as "super intelligence." Elon Musk promised to rename SpaceXAI to SpaceXSI, Marc Benioff said Salesforce would rename AIForce to SIForce, Nvidia tied "super intelligence research" to a $1 billion commitment, and Microsoft's Satya Nadella repeatedly used the term in a post calling for an AI "emergency brake."
Amazon followed Microsoft in saying it will no longer use nondisclosure agreements when negotiating with local governments over data centers, a move buried in a longer blog post arguing data centers benefit communities. On TechCrunch's Equity podcast, Sean O'Kane, Rebecca Bellan and Anthony Ha debated whether the change will ease backlash, noting moratoriums typically last only a year or two while data centers take years to come online.
Microsoft CEO Satya Nadella used "Super Intelligence" instead of "Artificial Intelligence" in a new blog post, echoing President Trump's preferred terminology. Nadella argued AI models should be treated like insider security threats, calling for model diversity, complete logging, independent auditing and human shutdown ability, while criticizing Anthropic and OpenAI. The Decoder reports the rebranding breaks with decades of scientific meaning and that Nadella's arguments serve Microsoft's business strategy.
TypeSafe AI, the San Francisco company behind the decision-only model Jev, announced an $870 million Series A at a $7.5 billion post-money valuation, up from a $200 million valuation at its $40 million seed round 24 days earlier. a16z, Sequoia and DCVC participated, and a16z partner Martin Casado joined the board. The company says about one third of Fortune 500 companies now use or integrate Jev, which outputs decisions rather than chat.
In a lengthy post on X, Microsoft CEO Satya Nadella argued that highly advanced AI models pose dangers that require new safeguards, saying "we must assume a model is compromised and contain it from the start." He called for an "emergency brake" that lets an authorized person pause or shut down a model mid-task, plus timely incident disclosure, independent audits, verifiable data, and containment.
Microsoft CEO Satya Nadella called for an "emergency brake" on AI models, writing in a Saturday morning post on X that it's time "to step back and assess the trust architecture" of AI. He proposed separating the model from the harness that orchestrates its work, externalizing controls and safeguards, documenting every meaningful model action with "tamper-proof human readable evidence," and giving an authorized person the ability to pause or shut down a model mid-task.
Super Intelligence must be contained... Today, this is an engineering and governance challenge. And it isn't new. We've done it with planes, cars, nuclear materials, food safety, medicines... and everything else. Let's get to work! https://twitter.com/satyanadella/status/2108931348857827686
Microsoft released Decision-1, a decision model for classifications, evaluations and routing decisions, built on Qwen3.5-9B. Microsoft says it tops 36 benchmarks covering nearly 150,000 questions with 83.5% accuracy and 85 ms latency, and is 2.5 times faster than runner-up H2O-Lightning-4B. It is available through Microsoft Foundry and OpenRouter at $0.042 per million input tokens, with output tokens free.
Satya Nadella argues that frontier AI models should be treated as insider risks and surrounded by deterministic controls, because their behavior can be difficult to trace and they may have access to sensitive data and mission-critical actions. He calls for separating intelligence from authority, keeping access and action controls outside the model, and building systems around model diversity, observable activity, and continuous testing.
TypeSafe announced its Series AI round, and Sequoia disclosed that the company crossed $100M ARR in its first week, three weeks after launch, according to this AINews roundup. The same issue reports several vendors shipping typed decision models on one day, including OpenAI's Decisions API on GPT-6 Luna at $0.10/M input tokens and Perplexity's pplx-decider-v1.1-27b claiming 94.5% on Decision Bench.
Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.
Amazon announced it will no longer use NDAs when negotiating data center deals with local governments, after Microsoft made a similar move earlier this year. Meanwhile, a group of startups is betting that consumers will let AI agents access their inboxes, files, and credit cards, provided they can get websites to allow it. The TechCrunch Equity podcast discussed whether dropping NDAs will change how data center deals are done, and why trust may be the real product for personal AI startups.
Amazon announced it will no longer use non-disclosure agreements when negotiating data center deals with local governments, after Microsoft took a similar step earlier this year. The secrecy practices had previously fueled community opposition to AI infrastructure, with hundreds of proposed and enacted bans from New York to San Francisco. TechCrunch's Equity podcast discussed whether dropping NDAs will change how data center deals get done, and why trust may be the real product for personal AI startups.
Amazon Bedrock has launched OpenAI's GPT-6 Astra, Sol, and Luna series models, among which GPT-6 Astra supports up to 1 million input tokens, and the Ultrafast version boosts API inference speed by up to 6x, reaching 300 tokens/second.
Trump signed an executive order banning the use of the term "AI" where possible, requiring artificial intelligence to be renamed "Super Intelligence." The U.S. Center for AI Standards and Innovation (CAISI) has been renamed CAISSI, and Justice Department press releases have also adopted the term.
OpenAI has built a new sandbox mode for Codex on Windows using Microsoft’s Execution Containers (MXC), offering faster setup, stronger network enforcement, and granular file access controls. Requires a compatible Windows 11 device. https://t.co/VsMQe3gl1P
Anthropic introduced two beta features for Claude. Dashboards can connect to data sources including BigQuery, Databricks, Snowflake, and Salesforce.
Thank you, @POTUS, for this incredible honor today. I'm humbled to stand alongside so many giants of American innovation and looking forward for what we can continue to do together to advance technology and drive American prosperity. https://twitter.com/RapidResponse47/status/2108257009304822202
