Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
NextBigFuture

Defeating Nondeterminism in LLM Inference by Thinking Machines

A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
VentureBeat

How attention offloading reduces the costs of LLM inference at scale

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...
Business Wire

Enfabrica Unveils Industry’s First Ethernet-Based AI Memory Fabric System for Efficient Superscaling of LLM Inference

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Enfabrica Corporation, an industry leader in high-performance networking silicon for artificial intelligence (AI) and accelerated computing, today announced the ...
Semiconductor Engineering

LLM Inference: Core Bottlenecks Imposed By Memory, Compute Capacity, Synchronization Overheads (NVIDIA)

A new technical paper titled “Efficient LLM Inference: Bandwidth, Compute, Synchronization, and Capacity are all you need” was published by NVIDIA. “This paper presents a limit study of ...
Semiconductor Engineering

Transformers At The Edge: Efficient LLM Deployment

Since the groundbreaking 2017 publication of “Attention Is All You Need,” the transformer architecture has fundamentally reshaped artificial intelligence research and development. This innovation laid ...
XDA Developers on MSN

I served a 200 billion parameter LLM from a Lenovo workstation the size of a Mac Mini

This mini PC is small and ridiculously powerful.
SDxCentral

AI inference crisis: Google engineers on why network latency and memory trump compute

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...
techtimes

AI at the Edge: LLM on NVIDIA Jetson

Demand for AI solutions is rising—and with it, the need for edge AI is growing as well, emerging as a key focus in applied machine learning. The launch of LLM on NVIDIA Jetson has become a true ...