How DeepSeek’s DSpark Makes LLMs 85% Faster Without Retraining

DeepSeek has introduced DSpark, an open-source speculative decoding method that accelerates LLM inference by up to 85% ...
techtimes

Embodied AI World Models Attracted $6 Billion, But the LLM Parallel May Not Hold

The robot AI investment community has a story it tells about its own future: world models will do for physical machines what transformers did for language. Pre-train on the dynamics of the physical ...
The Next Platform

Finding NeMo Features for Fresh LLM Building Boost

This week Nvidia shared details about upcoming updates to its platform for building, tuning, and deploying generative AI models. The framework, called NeMo (not to be confused with Nvidia’s ...
Semiconductor Engineering

Scalable Chiplet System for LLM Training, Finetuning and Reduced DRAM Accesses (Tsinghua University)

A new technical paper titled “Hecaton: Training and Finetuning Large Language Models with Scalable Chiplet Systems” was published by researchers at Tsinghua University. “Large Language Models (LLMs) ...
Tech Times

NVIDIA’s New LLM Decodes 6x More Tokens Without an Auxiliary Draft Model

NVIDIA Nemotron-Labs-Diffusion is a new tri-mode language model that eliminates the separate draft model in speculative ...
EDN

MLPerf and the rise of latency-aware LLM benchmarking

Any discussion of modern AI system performance must include MLCommons and its MLPerf benchmark suite, which has become the industry’s de facto standard for measuring machine learning performance.