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Microsoft AI diagnostic tool publishes research in Science, claims accuracy up to four times that of human doctors

Microsoft has announced the research results of its AI diagnostic tool Diagnostic Orchestrator, which uses multiple AI agents to collaboratively reason about symptoms, decide on tests, and provide diagnoses, and is based on OpenAI's GPT-5. In tests drawn from hundreds of case reports from the New England Journal of Medicine, the system's diagnostic accuracy was about 83%, compared with about 36% for general practitioners who used reference materials and about 22% for those who did not; on emergency cases from Beth Israel Deaconess Medical Center in Boston, its accuracy was 80%, compared with an average of 47% for human doctors, and the system's estimated cost for reaching a diagnosis was lower. Microsoft will open-source its self-built benchmark SDBench and plans to conduct tests with Beth Israel Deaconess Medical Center in a hospital setting in the coming months, but the system has so far been validated only on historical cases and still requires clinical validation.

Anthropic red-teams Auto Mode: production monitoring fails to block more than 55% of malicious coding agents

Anthropic's Alignment Science blog published research using Opus 5 red-team agents to conduct adversarial testing against production interception monitoring such as Claude Code's Auto Mode and OpenAI Codex's Guardian, finding that on average more than 55% of attacks were not intercepted. The most effective attack methods included agent-generated prompt injection, multi-context attacks across sessions or compressed summaries, and exploiting coverage gaps where edits within the working directory are not monitored. The team introduced Auto Mode++ through improvements such as transcript-format escaping and heredoc framing, monitoring all edits, and adding a tool-call investigation agent, reducing the attack success rate by more than 50 percentage points, but reliably defending against multi-context attacks still directly conflicts with latency costs.

Greg Brockman shares new lead from GPT-Rosalind in drug discovery

Greg Brockman shared OpenAI's progress on GPT-Rosalind: the model has surfaced a new lead in drug discovery, namely whether restoring cholesterol transport could protect neurons from degeneration. OpenAI says DCTN1 is a gene associated with Perry syndrome, and that disrupting it in mouse brain data increased the expression of genes involved in cholesterol synthesis; on this basis, GPT-Rosalind hypothesized that cholesterol may not be reaching where neurons need it. In collaboration with PerturbAI and Scripps Research, thousands of GPT-Rosalind agents worked in parallel, linking gene expression results from millions of mouse brain cells with scientific literature within 32 minutes, and OpenAI says it is expanding this collaboration to find new drug targets.

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Arena releases Alignment Index, GPT-6.1-Sol tops with 87.9 points

Arena.ai launched the Arena Alignment Index, which measures the safety and alignment performance of agents in real-world use based on over 90,000 real agent sessions across 27 models. The index tracks three signals: Unauthorized Action (UA), False Attribution (FA), and Deceptive Completion (DC). The leaderboard shows OpenAI's GPT-6.1-Sol in first place with 87.9 points, followed by Anthropic's Claude-Opus-5.5 with 83.2 points, and SpaceXAI's Grok-4.7 in third with 82.7 points; OpenAI also had the lowest observed rates on the three signals, at 0.89%, 1.98%, and 2.34%, respectively. Arena said unauthorized actions are rare but can have serious consequences, that misalignment risk rises as conversations grow longer, and that it will gradually add more safety signals and models.

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