The integration streamlines AI deployment, enhancing efficiency and autonomy in task execution, potentially transforming AI agent utilization.
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Nous Research has published Lighthouse Attention, a selection-based hierarchical attention mechanism that wraps around standard scaled dot-product attention during pretraining and is removed afterward. Unlike prior methods such as NSA and HISA that pool only keys and values, Lighthouse pools Q, K, and V symmetrically across a multi-resolution pyramid, reducing the attention call from O(N·S·d) to O(S²·d) and running stock FlashAttention on a small dense sub-sequence. Tested on a 530M Llama-3-style model at 98K context, it achieves a 1.40–1.69× end-to-end wall-clock speedup against a cuDNN SDPA baseline with matching or lower final training loss.
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Nous Research releases Token Superposition Training (TST), a two-phase pre-training method that cuts wall-clock training time by up to 2.5x at matched FLOPs by averaging contiguous token embeddings into bags during Phase 1 and reverting to standard next-token prediction in Phase 2 — without changing the model architecture, tokenizer, optimizer, or inference-time behavior. Validated at 270M, 600M, 3B dense, and 10B-A1B MoE scales.
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Agentic AI is changing the way users get work done. Following the success of OpenClaw, the community is embracing new open source agentic frameworks. The latest is Hermes Agent, which crossed 140,000 GitHub stars in under three months.
The lawsuit could redefine AI liability, prompting stricter safety protocols and reshaping industry standards for AI deployment and oversight.
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There is no governmental mechanism to pay for an AI agent that monitors a patient between visits, calls to check in, coordinates a housing referral, or makes sure someone picks up their medication. ACCESS creates that mechanism for the first time.
AI agents are moving beyond simple command-line tools into systems that can plan, schedule, call tools, and run automated workflows. Nous Research’s Hermes Agent framework offers a self-hosted runtime for building advanced agents with state management, tool integration, and secure execution. It supports multi-step planning, background task control, and real-world automation beyond single-purpose coding assistants. […]
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