The integration streamlines AI deployment, enhancing efficiency and autonomy in task execution, potentially transforming AI agent utilization.
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OpenServ (SERV) climbed nearly 70% in 24 hours. The token broke out of a falling wedge that had pressured price since late October 2025. The move arrived as autonomous AI agents returned as one of crypto’s leading narratives. SERV trades near $0.051 with a market cap of about $39 million. The project ranks 579 by market value. Daily volume sits close to $3.8 million. Falling Wedge Breakout Hints the Rally May Be Maturing The daily chart shows SERV escaping a falling wedge that compressed price action for roughly seven months. The pattern’s lower trendline ran from October 2025 lows, while the upper boundary tracked a series of lower highs. OpenServ (SERV) Price Performance. Source: TradingView In technical analysis, falling wedges typically resolve higher, and SERV’s breakout above the $0.0287 horizontal level confirmed the structure. Measured-move analysis points to
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.
The post Nous Research Proposes Lighthouse Attention: A Training-Only Selection-Based Hierarchical Attention That Delivers 1.4–1.7× Pretraining Speedup at Long Context appeared first on MarkTechPost.
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.
The post Lawsuit claims OpenAI’s ChatGPT enabled Florida State shooting by advising gunman to target children appeared first on Crypto Briefing.
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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