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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. SIGNIFICANT · dev.to — LLM tag English(EN) · · [2 sources]

    NyayAI: Building an AI Legal Assistant for 1.4 Billion People — A Technical Deep Dive

    NyayAI is an AI-powered legal intelligence platform designed to make Indian law accessible and affordable for its 1.4 billion citizens. The platform addresses the critical issue of over 50 million pending court cases in India by providing lawyers and citizens with tools to navigate complex legal texts. Unlike general-purpose AI models that often hallucinate or lack legal depth, NyayAI is built from the ground up with a curated corpus of Indian legal documents, offering precise retrieval, summarization, and citation-grounded answers. AI

    IMPACT Aims to democratize legal access in India by providing an AI-powered tool specifically trained on Indian jurisprudence, potentially impacting millions of citizens and legal professionals.

  2. RESEARCH · Hugging Face Daily Papers English(EN) · · [2 sources]

    Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX

    Researchers have developed Mahjax, a new GPU-accelerated simulator for the complex game of Riichi Mahjong, implemented in JAX. This tool is designed to facilitate reinforcement learning research, particularly for agents learning from scratch rather than relying on human play data. Mahjax achieves high throughput, processing up to 2 million steps per second on multiple GPUs, and has been validated for training agents to improve their performance. AI

    IMPACT Enables large-scale reinforcement learning research for complex games, potentially leading to more general AI decision-making capabilities.

  3. RESEARCH · arXiv cs.CL English(EN) · · [2 sources]

    ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU

    Researchers have developed ModeSwitch-LLM, a lightweight controller designed to enhance the efficiency of large language model inference on a single GPU. This system dynamically routes requests to various inference modes, including quantized, speculative, and hybrid configurations, based on workload features. Evaluations on Meta-Llama-3.1-8B-Instruct demonstrated a 2.10x speedup in latency and a 51.7% reduction in energy consumption per token compared to standard FP16, while maintaining near-equivalent accuracy. AI

    IMPACT Improves LLM inference efficiency on single GPUs, potentially lowering operational costs and increasing accessibility.