A new machine learning method from Rice University helps scientists better understand the unique light signatures of molecules and materials. This AI algorithm breakthrough at Rice University offers clearer, faster analysis for medical and scientific applications.
OPEX® unveils its new Gemini™ Scanner with Right-Speed™ scanning technology
OPEX® Corporation, a global leader in Next Generation Automation for almost 50 years, has introduced...
Dayna Arnold, Project Manager at Zest Consult, discusses the benefits of using a synthetic data approach to machine learning as an innovative solution for increasing the availability, accuracy & security of more cost effective data.
Tumble drying laundry can worsen air pollution, as it releases vast amounts of possibly harmful microfibres into the air, if not coupled with more eco-friendly methods.
The study, published in The Lancet Digital Health, found that deep learning tech had an average accuracy of 88% when it came to diagnosing genetic syndromes.
David Knezevic, PhD, CTO of Akselos, discusses an emerging field of computing that is revolutionising how large-scale infrastructures, including onshore wind structures, offshore platforms and super-tankers are designed.
Jack Williams, Strategic Product Manager – AI & Analytics, Hexagon’s Safety & Infrastructure division, explores how assistive artificial intelligence (AI) will help public safety and smart cities of the future.
When it comes to finding 'alien' life on other planets, scientists have a new theory - that extraterrestrial life is completely different to Earth-life, so finding biosignatures may not be as important as previously thought.
When rethinking service transformation, the focus should be on reshaping - Christopher Sly, AVP, Digital Transformation, HGS UK, explains why knowing the limitations to emerging tech reshapes a far greater value story.
The research team believe that some people have a genetic predisposition that increases likelihood of severe COVID, which may be crucial to understanding how mutations could change outcomes.
A research team at MIT have created a machine-learning strategy to identify existing drugs that could be repurposed to fight COVID-19 in elderly patients.
