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 […]
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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 […]
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 […]
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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 […]
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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Neuphonic has released NeuTTS Air, an open-source text-to-speech (TTS) speech language model designed to run locally in real time on CPUs. The Hugging Face model card lists 748M parameters (Qwen2 architecture) and ships in GGUF […]
IBM just released Granite 4.0, an open-source LLM family that swaps monolithic Transformers for a hybrid Mamba-2/Transformer stack to cut serving memory while keeping quality. Sizes span a 3B dense “Micro,” a 3B hybrid “H-Micro,” […]
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