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AMP Robotics Pilots Automated Facility Design for Advanced Secondary Sortation

AMP Robotics Corp. (“AMP”), a pioneer in artificial intelligence (AI) and robotics for the waste industry, has piloted an automated facility design for advanced secondary sortation. The company-owned test facility, located in Denver, serves as an infrastructure model that economically can process and aggregate small volumes of difficult-to-recycle mixed plastics, paper, and metals sourced from residue supplied by primary MRFs.

5 Mar 2021

New Objectives may Lead to Next-Generation Artificial Intelligence

Human beings are living inside an ocean of signals. These signals enable human beings to demonstrate intelligence. Similarly, machines are also surrounded by signals. Artificial intelligence (AI) or machine intelligence has become a hot topic for many decades due to the high expectation of the public on the emergence of smart machines and smart products.

5 Mar 2021

AI-Based Method Offers New Treatment Targets for Alzheimer’s Disease

There is a desperate need to develop new therapies for Alzheimer’s disease, but multiple clinical trials performed on investigational drug candidates have not yielded potential options.

5 Mar 2021

New AI-Based Device Mimics Neural Activity of the Human Brain

Artificial intelligence (AI) needs a large amount of computing power and also multipurpose hardware to support this computing power.

3 Mar 2021

Teledyne e2v and Yumain Announce Collaboration to Create AI-Based Imaging Solutions for Machine Vision

Teledyne e2v, a Teledyne Technologies company and global innovator of imaging solutions, announces a new technology and industrial collaboration with Yumain (Dijon, France), a leading AI vision solution provider serving a broad range of industrial applications.

From Teledyne e2v 3 Mar 2021

Transparent, Reproducible AI Tool for Health Information Analysis

Clinical research necessitates the mining of data to gain crucial insights. Machine learning, which involves developing algorithms to identify patterns, finds it hard to do this in the case of data related to health records since information of this kind is neither static nor collected regularly.

26 Feb 2021

Using Machine Learning to Infer Building Heights from Historical Maps

A research team from Skoltech and FBK (Italy) presented a methodology to derive 4D building models using historical maps and machine learning. The implemented method relies on the geometric, neighbourhood, and categorical attributes to predict building heights.

25 Feb 2021

Revive the Map: 4D Building Reconstruction with Machine Learning

Research team from Skoltech and FBK (Italy) presented a methodology to derive 4D building models using historical maps and machine learning. The implemented method relies on geometric, neighbourhood, and categorical attributes in order to predict building heights.

25 Feb 2021

Novel Machine-Learning Approach Could Transform Computational Materials Discovery

A revolutionary machine-learning (ML) approach to simulate the motions of atoms in materials such as aluminum is described in this week's Nature Communications journal. This automated approach to "interatomic potential development" could transform the field of computational materials discovery.

24 Feb 2021