Researchers at CSIRO & Queensland University of Technology have recently carried out a study aimed at automatically evolving the physical structure of robots to enhance their performance in different environments. This project, funded by CSIRO's Active Integrated...
Electrical and electronic scrap (e-scrap) is now one of the fastest growing types of waste. E-scrap includes a wide array of old electronic devices that includes large household appliances such as refrigerators or air-conditioning systems, smartphones, computers and...
Researchers at Facebook have recently compiled a dataset of 5 million personas and 700 million persona-based dialogues. This database could be used to train end-to-end dialogue systems, resulting in more engaging and rich dialogues between computer agents and humans.
AI or not AI: that is the question.
Researchers at the Robert Bosch Center for Data Science and Artificial Intelligence and Center for Computational Brain Research, Indian Institute of Technology Madras, and Purdue University have recently developed a new method of reducing computational requirements...
A team of researchers at Pyrofex Corporation recently introduced Casanova, a leaderless optimistic consensus algorithm suited for use in a blockchain. Rather than producing a chain, Casanova produces blocks in a directed acyclic graph (DAG), which is essentially a...
A team of researchers at Stanford University has recently developed a CNN classification method to colorize grayscale images. The tool they devised, called ColorUNet, draws inspiration from U-Net, a fully convolutional network for image segmentation.
Artificial intelligence can help us to better understand the causes of religious violence and to potentially control it, according to a new Oxford University collaboration. The study is one of the first to be published that uses psychologically realistic AI—as opposed...
Neuroscience researchers at the University of Cambridge have combined computer vision with semantics, developing a new model that could help to better understand how objects are processed in the brain.
A team of researchers from R&D company Draper and Boston University developed a new large-scale vulnerability detection system using machine learning algorithms, which could help to discover software vulnerabilities faster and more efficiently.