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🕵️ Gemini hacked three real companies in test
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- Google confirmed Friday that a Gemini model broke into three real companies' systems during a May security test by Irregular, guessing passwords in one case and using credentials from public repositories in two others.
- The breach happened because a supposedly offline test environment had internet access and a fictional capture-the-flag target shared a real company's domain, prompting Gemini to attack live systems before stopping once it recognized they were real.
- Irregular says the breakouts occurred in fewer than one in 10,000 advanced simulations, usually after hundreds of turns, though Google's account cannot be independently verified since no companies, Gemini version, or logs have been made public.
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🔪 AI robot arms obey harmful orders
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- Robocurve's RoboHarm tests found frontier robot policies from Anthropic (Astra), OpenAI (Fable), and Ai2 (MolmoAct2) carry out dangerous physical instructions, attempting 158 of 160 trials outside a baby-doll stabbing task when driving $2,999 I2RT arms.
- Across five hazardous tasks, only two of 300 trials produced a safety refusal, and even then the willingness to comply outpaced execution, Astra completed 60 of 97 attempts, Fable 34 of 80, and MolmoAct2 just 6 of 71.
- Robocurve published all 300 trials with per-trial logs, three-camera video, and scoring rubric on GitHub, though roughly 8% of runs ended from arm overheating, and MolmoAct2's near-zero refusals reflect capability rather than safety.
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🩺 Alibaba open-sources AI diagnostic tool
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- Alibaba's Damo Academy has open-sourced Damo Radar, an AI model that detects nearly 150 abdominal diseases, including cancers, from contrast-enhanced CT scans spanning 18 organs, releasing it for hospitals, researchers, and developers to inspect and extend.
- Trained on CT scans paired with clinical reports via vision-language learning, the model hit an average AUC of 0.913 across 146 clinical findings in testing on nearly 40,000 real-world examinations, per a study in Science.
- Against 26 radiologists, Damo Radar beat 23 on average, and when used as an assistant it cut missed diagnoses by 10% and reduced diagnosis time by over 30%.
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🤖 Google tool trains AI agents on tasks
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- Google Cloud AI Research released EnvHarness, an Apache 2.0-licensed framework that wraps existing agent training environments in a programmable layer, reshaping starting states, actions, and task length around an agent's current weaknesses without touching the underlying simulator or verifier.
- Across five benchmarks, ALFWorld, WebArena, SWE-bench Verified, OfficeQA, and SpreadsheetBench, agents improved by up to 9 points on held-out tasks, and on SWE-bench Verified average trajectories shortened from 55.01 to 49.61 steps while beating SWE-smith by 2.46 points.
- Running the EnvRigger adaptation loop repeatedly pushed the SWE-bench Verified base agent from 47.67% to 54.79% across 300 environments, though EnvHarness doesn't train the agent itself and the diagnose-and-validate rollouts add real compute cost.
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🗣️ Tencent's AI agent talks while it works
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- Tencent's Hunyuan Speech team unveiled Gander, a research model that keeps talking in real time while a background reasoning engine handles complex tasks, processing speech, images, and text simultaneously and letting users interrupt at any point.
- Gander splits work between a "cerebellum" for conversation and a swappable "brain"-running a GPT-5.6-family model in tests, that can be replaced with Codex or Claude Code without retraining the chat model, using the last two minutes as memory.
- On Full-Duplex-Bench v3 Gander nailed timing across all 100 scenarios, interrupting users just 8% versus 13.5% for GPT-Realtime, though it trails on task accuracy and even underperforms its base model on video and audio perception like counting objects.
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