Does the advent of machine learning mean the classic methodology of hypothesise, predict and test has had its day?
MIT researchers are testing a simplified turbulence theory’s ability to model complex plasma phenomena using a novel machine-learning technique. To make fusion energy a viable resource for the world’s energy grid, researchers need to understand the t
2021 has shown us how digital technologies can undermine what philosophers call future "human flourishing."
AI job automation affects virtually every sector and industry. While this might seem like cause for alarm, it’s actually long overdue news.
AI regulations are on the way from governments including China. Plus, driverless tractors have reached the market -- with caveats.
The distinction between observability and monitoring is subtle but significant. In short, monitoring tells you what is happening, while observability tells you why it’s happening.
The company has used one giant A.I. representation of proteins to broaden the search for novel biologics, and hopes to do everything in silico someday.
'Bias in AI is not solely a technical problem; it is interweaved across departments.'
A farmer can put the tractor to work with a swipe of a smartphone app and then walk away to attend to other business.
Meta (formerly Facebook) claims its new AI system, AV-HuBERT, can improve speech recognition accuracy by reading the lips of speakers.
Citizen scientists have helped researchers discover new types of galaxies, design drugs to fight COVID-19, and map the bird world. The term describes a range of ways that the public can meaningfully contribute to scientific and engineering research, as well as environmental monitoring.
RoadRunner Recycling, a data-driven waste management platform that diverts junk from landfill, has raised $70 million.
The Ethiopian entrepreneur Sara Menker founded Gro Intelligence, which uses artificial intelligence to forecast global agricultural trends and battle food insecurity.
Artificial intelligence’s lack of transparency is leading many to fear the technology and others to elevate it to a mysterious god-like figure, but we should be more critical of those making decisions about how AI is used, says anthropologist, Beth S
Artificial intelligence’s lack of transparency is leading many to fear the technology and others to elevate it to a mysterious god-like figure, but we should be more critical of those making decisions about how AI is used, says anthropologist Beth Si
Warnings have emerged about the unreliability of the metrics used to detect whether an audio perturbation designed to fool AI models can be perceived by humans. Researchers show that the distortion metrics used to detect intentional perturbations in audio signals are not a reliable measure of human perception, and have proposed a series of improvements.
Artificial intelligence (AI) is increasingly based on machine learning models, trained using large datasets. Likewise, human-computer interaction is increasingly dependent on speech communication, mainly due to the remarkable performance of machine learning models in speech recognition tasks.
Imagine if a prosthetic hand could feel, or if a robotic leg could behave differently depending on where the user is. Researchers around the globe are working to make this level of sophistication a reality, and they are doing so with the use of AI.