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 ...
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 ...
Semiconductor Engineering

Novel NorthPole Architecture Enables Low-Latency, High-Energy-Efficiency LLM inference (IBM Research)

A new technical paper titled “Breakthrough low-latency, high-energy-efficiency LLM inference performance using NorthPole” was published by researchers at IBM Research. At the IEEE High Performance ...
InfoWorld

Google targets AI inference bottlenecks with TurboQuant

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...
Forbes

The Inference Economy: How Sparse Computing And Model Optimization Are Reshaping Enterprise AI Deployment

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...
Newsweek

DeepSeek’s More Efficient AI Model Throws Doubt on Tech’s Energy Outlook

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. A Chinese AI company's more frugal approach to training large language ...