Articles about 'machine learning'

A robot ‘chef’ has been trained to taste food at different stages of the chewing process to assess whether it’s sufficiently seasoned.

A new approach to solving the Travelling Salesperson Problem – one of the most difficult questions in computer science – significantly outperforms current approaches.

Researchers have developed a new approach to machine learning that ‘learns how to learn’ and out-performs current machine learning methods for drug design, which in turn could accelerate the search for new disease treatments.

Five internationally-recognised researchers, including Cambridge’s Professor Zoubin Ghahramani, have been appointed as the first Turing AI World-Leading Researcher Fellows to conduct work on artificial intelligence’s (AI) biggest challenges.

Rapid deployment of artificial intelligence and machine learning to tackle coronavirus must still go through ethical checks and balances, or we risk harming already disadvantaged communities in the rush to defeat the disease.

Systematic review finds that machine learning models for detecting and diagnosing COVID-19 from medical images have major flaws and biases, making them unsuitable for use in patients. However, researchers have suggested ways to remedy the problem.

The project will use machine learning to sequence the world’s regulatory text and create an open-source repository of machine-readable regulatory information. 

Five researchers at the University of Cambridge have won consolidator grants from the European Research Council (ERC), Europe’s premiere funding organisation for frontier research.

Arm is working with Cambridge researchers to make our phones and computers more secure, more efficient and ready for the digital revolution.

World-leading AI technology developed by the Cambridge Centre for AI in Medicine and their colleagues – some of which is being showcased this week at the North American Cystic Fibrosis Conference 2020 – offers a glimpse of the future of precision medicine, and unprecedented predictive power to clinicians caring for individuals with the life-limiting condition.