Microsoft Research has developed an end-to-end machine learning pipeline that uses solar wind observations at L1, forecasts of the AE and Dst indices, and local geological conductivity data to estimate local space weather risks 30 to 60 minutes ahead for 66,935 substations in the contiguous United States.
Amazon Bedrock has introduced Anthropic's Claude Opus 5, Claude Sonnet 5 and Claude Haiku 4.5 in India, using geographic cross-region inference to process data within the country.
Amazon Bedrock now supports in-region inference for Anthropic Claude models in Seoul and Singapore. Seoul supports Claude Opus 5 and Claude Sonnet 5, while Singapore supports Claude Sonnet 5, all invoked through the bedrock-runtime endpoint.
GPT-6.1 Sol is now generally available on Amazon Bedrock, offering stronger reasoning for agentic coding, computer use and everyday professional workloads. OpenAI says it matches GPT-6 Astra on DeepSWE v1.1 at roughly one-fifth the cost per task, and exceeds GPT-6 Sol’s best result by 6.4 percentage points.
Microsoft Research released Quine, an AI research system for biological complexity, comprising a biological world model trained on multimodal data spanning sequences, structures, functions, cell states and imaging, and an interactive harness connecting the model, scientific tools, literature and experimental researchers.
MSRA – Singapore, Microsoft's first research lab in Southeast Asia, spent its first year focusing on next-generation AI models and agent systems, domain AI, AI-native research practices and talent ecosystems. It works with Singapore's healthcare ecosystem on multimodal medical AI and self-evolving diagnostic agents, and jointly held a logistics and transport AI executive roundtable with EDB in February 2026.
A canvas in the GitHub Copilot app is a customisable two-way interface. Entering /create-canvas in an agent session and describing a workflow generates boards, release checklists or dashboards without coding. Canvases are saved as extensions, shareable with projects or reusable personally, with community templates available through Awesome Copilot.
The GitHub Copilot app introduced canvas, full-stack mini-apps running inside the app without browser chrome. They communicate bidirectionally with Copilot agents and can call third-party APIs or execute code locally.
Dutch retailer HEMA built internal AI assistant HAL with MCP and Amazon Bedrock AgentCore, consolidating knowledge scattered across portals and wikis and delivering it directly into everyday tools such as Kiro and Claude.
GitHub rebuilt its Copilot app's pull request view to handle rendering pressure from huge diffs and comments, testing an open-source PR with 2,200 files, over 1 million changed lines and more than 400 inline comments. It separates document height into deterministic code geometry and dynamic block geometry: code line heights are computed precisely in advance, while comments and other dynamic blocks use bounded heights and deferred measurements, with corrections anchored to the user's current position.
Microsoft Research systematically measured mobile manipulation robot workloads and found that offloading physical AI inference from onboard GPUs to edge or cloud GPUs can improve task success, support larger models and extend battery life.
Microsoft published RetroChimera, a retrosynthesis prediction framework, in Nature and open-sourced its implementation and weights. It combines the Transformer model R-SMILES 2 with GNN-based NeuralLoc, using a learned ensemble to rerank predictions. Chemists preferred its single-step reaction predictions in blind testing.
GitHub used the Copilot app and Copilot CLI to completely rewrite the Copilot agent runtime from TypeScript into over 800,000 lines of production Rust. AI agents wrote most of the code, delivered incrementally across 128 PRs, improving performance by several orders of magnitude.
GitHub's Japan and Korea marketing leads used Copilot to automate event operations. GitHub Issues are work units, Issue forms collect structured fields and labels trigger Actions workflows to generate UTM links, landing pages and invitation emails and clean registrant lists.
Copilot's built-in diff, terminal and browser panels enable review, execution and preview of AI code without switching applications. The diff highlights additions in green and deletions in red, supporting acceptance, comments or further edits. The terminal runs project commands with multiple windows, while the browser's Pick & Polish selects elements for agent adjustments.
GitHub released a research preview of Project HydraFusion, using runtime multi-model orchestration to deliver frontier-level coding through Copilot. Users can enable it via /experimental in GitHub Copilot CLI, paying each model's standard rates for tokens actually consumed.
Copilot app runs multiple agent sessions simultaneously in separate Git worktrees, preserving context without interference. The sessions view shows titles and progress, allowing switching and resuming without restating tasks. The article demonstrates funded sort development, accessibility review and testing in parallel in tailspin-toys.
Microsoft Research introduced GigaPath-Flash and GigaTIME-Flash, greatly reducing pathology compute requirements with a 22M-parameter ViT-S backbone distilled from the billion-parameter GigaPath encoder, open-source under Apache 2.0.
Hugging Face proposed three tests to quantify benchmark optimisation in speech recognition: a consensus-disagreement probe, masked-entity retrieval and spelling switches. Evaluating 11 open-source ASR models, it found some high-scoring models reproduce errors in VoxPopuli and LibriSpeech reference transcripts even when contradicted by audio, when relevant words are muted or when both spellings fit the audio.
Microsoft Research released deep-learning DFT functional Skala 1.1, trained on 2.5 times more data than the previous public version. It ranks first in 32 of GMTKN55's 55 categories with 2.8 kcal/mol weighted average error. Available in CP2K and being integrated into Psi4, FHI-aims, ORCA and VASP, it is tracked by a new living performance benchmark.
Microsoft Research introduced MindTopo to evaluate multimodal models' reasoning and planning over connectivity, enclosure, order, separation and knotting. Current models perform much better at static-image recognition than interactive planning, with failures mainly in planning rather than perception and overall performance far below humans. Image and video generation helps only when preserving structural relations in a single frame; multi-step operations often change topology or violate constraints.
Microsoft Research released CARE-X, a unified chest X-ray vision-language research model for report generation and structured prediction. It rewards clinical correctness using multitask reinforcement learning (DAPO). Generation and dual-inference modes cover lesion presence and negation, localisation, multilabel classification, catheter and tube malposition detection, and localisation of 29 anatomical regions.
Microsoft Research released the open-source Orchard framework, centred on the Kubernetes environment service Orchard Env. It reuses environments, data pipelines and evaluation workflows across tasks and supports training agents directly within real deployment frameworks such as Codex, OpenClaw and ZeroClaw.
Microsoft Research proposed Echoverse, constructing twelve training worlds for computer-use agents: ten deep domain worlds and two capability worlds. Code, data and scorers for four worlds are open-sourced.
At Build 2026, Microsoft announced Foundry Managed Compute and a Hugging Face model collection, with weekly updates to open-weight models and one-click deployment to Foundry's managed GPU platform.