Google DeepMind has deployed a new AI agent designed to autonomously find and fix critical security vulnerabilities in software code. The system, aptly-named CodeMender, has already contributed 72 security fixes to established open-source projects in […]
Do curated, tool-grounded demonstrations build stronger software agents than broad piles of generic instruction data? A team of researchers from Shanghai Jiao Tong University and SII Generative AI Research Lab […]
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In the race to automate everything – from customer service to code – AI is being heralded as a silver bullet. The narrative is seductive: AI tools that can write entire applications, streamline engineering teams […]
Optimizing only for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is insufficient for modern, interactive voice agents. Robust evaluation must measure end-to-end task success, barge-in behavior and latency, and hallucination-under-noise—alongside ASR, safety, and […]
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A cycle-accurate alternative to speculation — unifying scalar, vector and matrix compute For more than half a century, computing has relied on the Von Neumann or Harvard model. Nearly every modern chip — CPUs, GPUs […]
Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and even neural network […]
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Huawei’s Computing Systems Lab in Zurich has introduced a new open-source quantization method for large language models (LLMs) aimed at reducing memory demands without sacrificing output quality. The technique, called SINQ (Sinkhorn-Normalized Quantization), is designed […]
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