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 ...
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 ...
Forbes

Cerebras Now The Fastest LLM Inference Processor; Its Not Even Close

The company tackled inferencing the Llama-3.1 405B foundation model and just crushed it. And for the crowds at SC24 this week in Atlanta, the company also announced it is 700 times faster than ...
Semiconductor Engineering

Four Architectural Opportunities for LLM Inference Hardware (Google)

“Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI ...
Semiconductor Engineering

Systematic Analysis of CPU-Induced Slowdowns in Multi-GPU LLM Inference (Georgia Tech)

A new technical paper, “Characterizing CPU-Induced Slowdowns in Multi-GPU LLM Inference,” was published by the Georgia ...
InfoQ

GPULlama3.java Brings GPU-Accelerated LLM Inference to Pure Java

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
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 ...
NextBigFuture

OpenAI Strawberry LLM Reasoning Needs More Compute and Energy for Inference

Jim Fan is one of Nvidia’s senior AI researchers. The shift could be about many orders of magnitude more compute and energy needed for inference that can handle the improved reasoning in the OpenAI ...
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 ...
Forbes

The New Frontier Of LLM Inference: Where The Next Tenfold Gains Will Come From

Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...
Digi Times

In-depth: Google TurboQuant cuts LLM memory 6x, resets AI inference cost curve

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...