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All digests tagged Hugging Face
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The session explores the future of AI, from open models to physical AI. Key topics include digital twin simulation, agentic orchestration, and multi-modal generative models like Flux 3 for robotics and manufacturing.
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The shift to open intelligence means owning the entire AI stack. Customization now involves RL, environments, and controlling data/safety, moving beyond simple API calls.
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Learn how to build an intelligent robot arm from scratch, moving from basic servos and microcontrollers to advanced AI integration using Physical AI principles.
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OpenRouter is positioned as critical infrastructure, solving the problem of model labs struggling with developer distribution. It provides a neutral layer for model diversity, orchestration, and governance in the rapidly expanding AI token economy.
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The discussion covers the debate around slowing AI development (pacing), details the technical features of IBM's Granite 4.2 models, and analyzes Meta's new personal agent, Muse.
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Domyn outlines building sovereign AI models for regulated industries using advanced techniques like model compression, CPT, and RL. They detail custom tooling (Swarm, FinalFlows) essential for managing large-scale ML pipelines.
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MiniMax M3 combines a functional one-million-token context window with native multimodality, achieved through the Minimax Sparse Attention (MSA) architecture. This enables advanced agentic capabilities.
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IBM unveiled a new dual processor combining z/OS and Arm for mainframes. NVIDIA's strategy involves acquiring Hugging Face to dominate open AI, while Z.ai revealed GLM-5.3-Flash.
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Learn how to automate a job using agents: Niels Rogge discusses building two systems—a deterministic workflow and an autonomous agent loop—to scale artifact discoverability at Hugging Face.
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This technical talk explores LLM vulnerabilities, detailing attacks like Policy Puppetry and computational graph backdoors. Learn how to secure AI systems against sophisticated threats.
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Arithmetic developed a benchmark focused on access control, requiring models to make logical leaps across chained systems like Keycloak and Vault. The goal is training AI to out-think hackers.
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