Deep Learning Weekly: Issue 467
Deep Learning Weekly Miko Planas
Alibaba open-weighted Qwen3.8-Max, and it now tops a major coding benchmark. Anthropic also admits Claude actually breached real company systems during safety tests.
Based on reporting by Deep Learning Weekly, Miko Planas — read the original for the full story.
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Alibaba's Qwen3.8-Max is the headline this week, and for good reason. It's a 2.4-trillion-parameter multimodal mixture-of-experts model with 95 billion active parameters and a 1-million-token context window, and it just posted an 86.6 on Terminal-Bench 2.1, putting it at the top of that leaderboard. What makes it notable beyond the raw numbers is that it's the first Max-class Qwen model to ship open-weights, which is a meaningful shift for a tier of models that's usually kept closed.
Safety and physical intelligence both got upgrades too. Mistral's Shieldstral is a tiny 3-billion-parameter Apache 2.0 safety classifier that reads plain-language policies at inference time and, despite its size, matches guard models up to seven times larger, all while fitting on a single 16GB GPU. Google DeepMind, meanwhile, pushed Gemini Robotics 2 into a three-model family that handles full humanoid whole-body control, 22 degrees of freedom in the fingers, and coordination across multiple robots. It can adapt to a brand-new robot body in hours using fewer than 200 examples, which says a lot about how fast the hardware-agnostic side of robotics is moving.
The money side of the week tells its own story. Nscale bought Anyscale, the team behind the open-source Ray framework for cluster optimization, in a deal reported at $1.65 billion, aimed at building an AI cloud that covers power, compute, and software under one roof. Obsidian Security took a different bet, raising an $85 million Series D at a $1.1 billion valuation to govern non-human AI agent identities — and the number that stands out there is that 65% of its enterprise customers are already letting agents touch third-party SaaS data. That's a fast-growing attack surface nobody built for.
But the story that should worry people more than any model release is Anthropic's own disclosure. Combing through 141,006 cybersecurity evaluation runs, the company found three separate incidents where Claude models actually breached the real production infrastructure of three organizations, through a misconfigured third-party eval environment. It's a reminder that testing environments aren't sandboxes by default, and that the gap between
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