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LatestMicrosoft Releases GitHub Copilot Fusion, Routing Coding Tasks Between Claude and GPT Models
Why read thisThe original text provides Fusion and Claude Code's scores on the Coding Agent Index, per-task cost, and token usage comparison, making it easy to judge the actual trade-offs of the routing approach.
Microsoft AI has released the image editing model MAI Image 2.7, launched in preview form, ranking 3rd on Arena Edit and 2nd on the Artificial Analysis image editing leaderboard, making Microsoft AI the 2nd-ranked lab. The company states that the model outperforms 2.6 on all 10 use cases and 7 categories of editing actions evaluated by Artificial Analysis, leading the next-best model by 24 Elo in scenes and styles. It is currently available for trial on Arena, Artificial Analysis, and MAI Playground, with text-to-image functionality coming soon.
Why read thisThe official rankings of this image editing model on Arena Edit and Artificial Analysis leaderboards are given, along with the improvement margin of use cases relative to 2.6.
Anthropic publicly filed its prospectus with the SEC on Monday, planning to list on Nasdaq under the ticker ANT, with the number of shares offered and pricing not yet determined. First-half 2026 revenue rose from $116 million in the same period a year earlier to $1.63 billion, of which about 80% came from usage-based billing such as APIs; the operating loss narrowed from $210 million to $69.3 million, and the net loss of $8.07 billion mainly stemmed from a $72.4 billion book valuation effect. The prospectus also disclosed compute commitments of at least $11.45 billion to Google, $11 billion to Amazon, and $4.49 billion to Microsoft, as well as $161.2 billion in hardware lease obligations to Broadcom.
Why read thisThe prospectus discloses that Anthropic's first-half revenue rose to $1.63 billion and its operating loss narrowed, while also listing long-term compute commitments to cloud providers.
Microsoft Research has open-sourced Agensh, a multi-agent framework that removes the central orchestrator, with each worker claiming subtasks on its own, sharing findings, and merging code into the same Git repository. On ProgramBench, the team scaled from 1 agent to 1024, raising the average pass rate on the 5 hardest tasks from 19.31% to 28.78% (with 128 agents), and the single pandoc task reached 79.59% with GPT-6.1-sol paired with 32 agents. The code is released under the MIT license, with a default of 8 workers per single node; the 1024-agent run used 16 nodes with 64 agents per node.
Why read thisThe original text presents a multi-agent collaboration mechanism without a central orchestrator and scaling data from 1 to 1024 agents, making it possible to observe the division of labor that emerges as scale increases.
In a peer-reviewed study published in Science, the Microsoft MAI-DxO diagnostic system achieved a diagnostic accuracy of 83.2% on case records from the New England Journal of Medicine, compared with 36.1% for general practitioners using reference resources. The study proposes the Sequential Diagnosis Benchmark (SDBench), converting 304 journal cases and 325 MIMIC-IV-ED emergency cases into stepwise diagnostic tasks allowing sequential questioning and test ordering, scored by accuracy and test cost. DxO paired with GPT-5 cost an average of $5,431 per case under no budget constraint; the authors also note that the comparison does not involve specialists, multidisciplinary teams, or real clinical practice.
Why read thisThe paper presents a stepwise diagnostic benchmark and accuracy comparison under cost constraints, showing the practical gains of multi-agent orchestration in clinical reasoning.
Microsoft security researchers say hackers linked to the Chinese government breached ConnectWise's cloud backup service and stole application credentials used to establish data links, allowing them to log in as authorized users to customers' Microsoft hosted environments and access email and other files. The hackers used AI agents to compromise about 2,250 organizations at a rate of nearly 3,000 login attempts per minute, a speed Microsoft says left defenders almost no time to detect and respond. The AI framework used was the open-source stress-testing framework ARTEX, which was previously used in an intrusion into South Korea's financial system. ConnectWise said it has suspended access to the cloud backup system and launched an investigation, and as of Thursday was restoring service.
Why read thisAttack details disclosed by Microsoft show that AI agents pushed credential-stuffing to nearly 3,000 login attempts per minute, greatly compressing the response window left for defenders.
Microsoft Research researcher Xinzhi Zhang and co-authors proved the KLS conjecture proposed in 1995, giving a dimension-independent fixed bound; the previous best result only allowed the bound to grow slowly with dimension. The proof came from a human-guided agent search process, in which the team explored more than 100 candidate paths, with researchers evaluating, pruning, and redirecting them; an independent team also gave a complete proof at the same time, followed by Lean 4 formal verification. The authors say earlier unguided end-to-end attempts with multiple frontier models failed to achieve the goal.
Why read thisMicrosoft Research uses human-guided agent search to prove the KLS conjecture, allowing readers to see how AI is directed in mathematical discovery.
Why read thisThe agreement connects OpenAI models to Google Cloud and allows them to count toward existing cloud spending commitments, helping readers understand changes in multi-cloud procurement and compliant deployment.
Why read thisThe Anthropic IPO draft seen by WSJ discloses specific figures for revenue, book losses and compute commitments, which can be used to understand its compute dependence and customer concentration risk.
