Machine learning Content / Machine learning Content for аÄÃÅÁùºÏ²ÊÄÚÄ»ÐÅÏ¢ Davis en Eye, Robot: Researchers Give Machines a New Perspective with Active Vision /blog/eye-robot-researchers-give-machines-new-perspective-active-vision <p><span lang="EN-US">When </span><a href="https://mae.ucdavis.edu/directory/iman-soltani"><span lang="EN-US">Iman Soltani</span></a><span lang="EN-US"> worked in the automotive industry, he studied assembly floors and noticed that each automated task had its specific robotic design.</span></p><p><span lang="EN-US">He also noticed that while a robot would need multiple cameras affixed to several locations for the best possible sightline, an operator on the assembly floor would move their head and neck to get the best view as they manipulated components.</span></p> November 26, 2024 - 2:46pm Andy Fell /blog/eye-robot-researchers-give-machines-new-perspective-active-vision From Viruses to Galaxies, How Machine Learning Helps Scientific Discovery /blog/viruses-galaxies-how-machine-learning-helps-scientific-discovery <p><span>Peruse any news media outlet and you’ll probably find an article touting or warning about the potential impacts of artificial intelligence (AI) on society. With the advent of publicly accessible generative AI models like ChatGPT, the field is having its moment in the sun like never before.</span></p> October 03, 2024 - 3:52pm Andy Fell /blog/viruses-galaxies-how-machine-learning-helps-scientific-discovery Unravelling AI Bias to Build Fair and Trustworthy Algorithms /blog/unravelling-ai-bias-build-fair-and-trustworthy-algorithms <p>In 2017,&nbsp;<a href="https://cs.ucdavis.edu/directory/ian-davidson">Ian Davidson</a>, a professor of computer science at аÄÃÅÁùºÏ²ÊÄÚÄ»ÐÅÏ¢ Davis, 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."&nbsp;&nbsp;</p> March 08, 2024 - 3:02pm Andy Fell /blog/unravelling-ai-bias-build-fair-and-trustworthy-algorithms Google Weed View? Professor Trains Computer to Spot Invasive Weed /climate/news/Using-AI-and-Google-Street-View-To-Spot-Invasive-Weed аÄÃÅÁùºÏ²ÊÄÚÄ»ÐÅÏ¢ Davis 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. December 07, 2023 - 8:00am Emily C Dooley /climate/news/Using-AI-and-Google-Street-View-To-Spot-Invasive-Weed Using Machine Learning to Predict Properties of Complex Materials /blog/using-machine-learning-predict-properties-complex-materials <p>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.</p> July 03, 2020 - 8:22am Andy Fell /blog/using-machine-learning-predict-properties-complex-materials Grant to Model Human Memory and Learning for Machines /news/grant-model-human-memory-and-learning-machines <p>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.</p> <p>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.</p> April 27, 2017 - 10:33pm Andy Fell /news/grant-model-human-memory-and-learning-machines Computer Model Is ‘Crystal Ball’ for E. Coli Bacteria /news/computer-model-crystal-ball-e-coli-bacteria <p>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 <em>Escherichia coli</em>.</p> <p>The results of their work were published Oct. 7 in the journal <em>Nature Communications</em>.</p> October 27, 2016 - 10:46am Andy Fell /news/computer-model-crystal-ball-e-coli-bacteria