Categories: AI/ML News

Computing scheme accelerates machine learning while improving energy efficiency of traditional data operations

Artificial intelligence (AI) models like ChatGPT run on algorithms and have great appetites for data, which they process through machine learning, but what about the limits of their data-processing abilities? Researchers led by Professor Sun Zhong from Peking University’s School of Integrated Circuits and Institute for Artificial Intelligence set out to solve the von Neumann bottleneck that limits data-processing.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

Best guess as to which tools were used for this? VACE v2v?

credit to @ unreelinc submitted by /u/Leading_Primary_8447 [link] [comments]

12 hours ago

Calculating What Your Bank Spends on Marketing Compliance Reviews

By Taylor Mahoney, VP of Solutions ConsultingPicture this. The Federal Reserve has just dropped interest…

12 hours ago

AlphaGenome: AI for better understanding the genome

Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to…

12 hours ago

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining

This paper was accepted to the ACL 2025 main conference as an oral presentation. This…

12 hours ago

Build an intelligent multi-agent business expert using Amazon Bedrock

In this post, we demonstrate how to build a multi-agent system using multi-agent collaboration in…

12 hours ago

How Schroders built its multi-agent financial analysis research assistant

Financial analysts spend hours grappling with ever-increasing volumes of market and company data to extract…

12 hours ago