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 ...

Your developers are already running AI locally: Why on-device inference is the CISO’s new blind spot

Shadow AI 2.0 isn’t a hypothetical future, it’s a predictable consequence of fast hardware, easy distribution, and developer ...
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 ...
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 ...
Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in ...
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 ...
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 ...
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 ...
XDA Developers on MSN

Stop obsessing over your GPU's core clock — memory clock matters more for local LLM inference

Your self-hosted LLMs care more about your memory performance ...
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 ...