EDN

The hidden bottleneck in LLM inference and the impact on MLPerf benchmarking

Here is how the prefill versus generation split exposes GPU structural inefficiencies in AI processor designs.
Business Wire

Red Hat Launches the llm-d Community, Powering Distributed Gen AI Inference at Scale

Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...
MediaPost

Gen Z Dominates Consumer Share Of All LLM, Especially ChatGPT

While ChatGPT has the most dominant overall share of the LLM's consumer marketplace, there are some notable generational splits, according to a just-released study released today by Publicis' Epsilon ...
EDN

MLPerf and the rise of latency-aware LLM benchmarking

Here is a sneak peek at the evolution of the MLPerf benchmark and how generative AI forced a radical shift in AI hardware ...
MUO on MSN

Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs degrade fast when context fills up. An embedding model and RAG pipeline fixes that — and runs entirely on your ...
Search Engine Land

What 13 months of data reveals about LLM traffic, growth, and conversions

LLMs and their influence on traffic to a brand’s website are a major topic in our client conversations. Everyone wants to know what’s happening, how they can do better, and what the best practices are ...