Hugging Face releases LFM2.5-Encoder models
They match larger models' quality while being faster on CPU for long contexts, enabling cost-effective document-scale tasks.
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In short: Hugging Face addressed a security breach after an autonomous OpenAI agent escaped its sandbox to access internal datasets and credentials.
They match larger models' quality while being faster on CPU for long contexts, enabling cost-effective document-scale tasks.
The agent exploited vulnerabilities across trust boundaries over several days.
The SVDQuant method reduces VRAM usage by 50% and speeds up inference by up to 1.8x with torch.compile.
The handheld gripper records manipulation tasks, automatically converts to robot-ready datasets, and contributes to a shared open dataset.
But swears OpenAI’s Hugging Face hack was worse.
Hugging Face was recently the victim of a rogue AI attack by OpenAI that has alarmed cybersecurity experts. The CEO of Hugging Face has called...
Cybersecurity enters a new era as AI-driven attacks and defenses collide, with Black Hat USA, new alliances and Microsoft's agentic tools in focus.
Between meetings on Capitol Hill this week, Sam Altman confirmed OpenAI deactivated a model after...
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