The technique aims to ease GPU memory constraints that limit how enterprises scale AI inference and long-context applications ...

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...

Large language models (LLMs) have made significant strides in artificial intelligence (AI) natural language generation. Models such as GPT-3, Megatron-Turing, Chinchilla, PaLM-2, Falcon, and Llama 2 ...

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability*, particularly for reasoning and planning (known as System 2 abilities) has been lacking.

The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the difference—and the implications.

A new technical paper titled “Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review” was published in “Proceedings of the IEEE” by researchers at University ...

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale. High inference latency and ...

Researchers from DeepSeek and Tsinghua University say combining two techniques improves the answers the large language model creates with computer reasoning techniques. Image: Envato/DC_Studio ...