Machine learning Content

Unravelling AI Bias to Build Fair and Trustworthy Algorithms

Andy Fell — March 08, 2024 - 3:02pm

In 2017, Ian Davidson, a professor of computer science at swag��, was on sabbatical as a fellow of the Collegium de Lyon in France. The institute brings together intellectuals, philosophers, artists and academics from all over the world to live together for one year to "think about great things."

Google Weed View? Professor Trains Computer to Spot Invasive Weed

Emily C Dooley — December 07, 2023 - 8:00am

swag�� researchers are using AI and Google Street View to spot invasive weeds for a fraction of the cost and time to track them using traditional surveys.

Using Machine Learning to Predict Properties of Complex Materials

Andy Fell — July 03, 2020 - 8:22am

Germanium-manganese compounds can have a wide variety of structures with different electronic, magnetic or thermal properties. Scientists are interested in these materials which could have applications in next-generation technology for memory storage, sensors or electronics, among other things. But working out the properties of these materials can be challenging, especially for compounds that only exist under conditions of high heat or pressure.

Grant to Model Human Memory and Learning for Machines

Andy Fell — April 27, 2017 - 10:33pm

Much of what scientists know about human memory comes from studies involving relatively simple acts of recollection — remembering lists of words or associations between names and faces.

However, they know very little about the brain networks that support memories for complex events, like when we remember the plot of a book or movie or what we experienced, thought and felt during a childhood birthday party.

Computer Model Is ‘Crystal Ball’ for E. Coli Bacteria

Andy Fell — October 27, 2016 - 10:46am

It’s difficult to make predictions, especially about the future, and even more so when they involve the reactions of living cells — huge numbers of genes, proteins and enzymes, embedded in complex pathways and feedback loops. Yet researchers at the University of California, Davis, Genome Center and Department of Computer Science are attempting just that, building a computer model that predicts the behavior of a single cell of the bacterium Escherichia coli.

The results of their work were published Oct. 7 in the journal Nature Communications.