Inference NPUs from South Korea Enter Japanese Data Centers: Will the GPU-Only Estimate Change?

When the topic of running LLMs in-house comes up, the first thing that usually appears is a GPU model number.What follows ...

Beyond the Limits of a Single GPU: Distributed Inference Technologies Supporting Massive AI Models

The video released by IBM Technology delves deep into the mechanisms that allow massive AI models to operate efficiently ...
Semiconductor Engineering

A Comprehensive Guide to Understanding AI Inference on the CPU

As AI continues to revolutionize industries, new workloads, like generative AI, inspire new use cases, the demand for efficient and scalable AI-based solutions has never been greater. While training ...
VentureBeat

Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use ...

NVIDIA PAIR Explained: What Is Personal AI Router, How It Works, Features and Requirements

NVIDIA PAIR is a beta tool for local AI inference, connecting PCs, Macs and DGX Spark systems into a personal AI cluster.
Forbes

Nvidia And d-Matrix Announce Collaboration Roadmap For Fast Inference

Forbes contributors publish independent expert analyses and insights. Founder and Principal Analyst, Cambrian-AI Research LLC This voice experience is generated by AI. Learn more. This voice ...
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Not Nvidia. Not Broadcom. Intel is going to be the biggest winner of the artificial intelligence (AI) inference era

Inference workloads are on course to consume a significant chunk of AI computing power in 2026. Intel is well positioned to capitalize on the growing demand for AI inference thanks to the efficiency ...