Categories: AI/ML News

Alternate framework for distributed computing tames Big Data’s ever growing costs

The sheer volume of ‘Big Data’ produced today by various sectors is beginning to overwhelm even the extremely efficient computational techniques developed to sift through all that information. But a new computational framework based on random sampling looks set to finally tame Big Data’s ever-growing communication, memory and energy costs into something more manageable.

How to compare a noisy quantum processor to a classical computer

August 25, 2023

In "FAANG"

A new neural machine code to program reservoir computers

Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing…

July 8, 2023

In "AI/ML News"

A face recognition framework based on vision transformers

Face recognition tools are computational models that can identify specific people in images, as well as CCTV or video footage. These tools are already being used in a wide range of real-world settings, for instance aiding law enforcement and border control agents in their criminal investigations and surveillance efforts, and…

December 20, 2022

In "AI/ML News"

AI Generated Robotic Content