Google’s TurboQuant Compression May Support Faster Inference, Same Accuracy on Less Capable Hardware
Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...
At NVIDIA’s DevSparks Pune 2026 masterclass session, attendees explored the software stack and built a Video Search and Summarization agent with NVIDIA DGX Spark, learning how compact AI systems ...
As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
Experts At The Table: AI/ML is driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge devices such as PCs and smartphones. Semiconductor ...
Training deep neural networks (DNNs) typically requires large-scale datasets, which poses substantial challenges related to computing resources and storage. Dataset Quantization (DQ) was introduced to ...
The 2025 Nobel Prize in Physics has been awarded to John Clarke, Michel H. Devoret, and John M. Martinis “for the discovery of macroscopic quantum tunneling and energy quantization in an electrical ...
This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
What if you could take a innovative language model like GPT-OSS and tailor it to your unique needs, all without needing a supercomputer or a PhD in machine learning? Fine-tuning large language models ...
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