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S6E4: Joel Ye: Examining Neural Data More Efficiently and Holistically
Manage episode 489425685 series 2954335
Content provided by Sarah Webb and Krell Institute. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sarah Webb and Krell Institute or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Understanding how the brain works remains a grand scientific challenge, and it's yet another area where researchers are examining whether foundation models could help them find patterns in complex data. Joel Ye of Carnegie Mellon University talks about his work on foundation models, their potential and limitations and how others can get involved in applying these AI tools.
Joel Ye is a Ph.D. student in the program in neural computation at Carnegie Mellon University in Pittsburgh, where he studies ways to understand brain data and brain-computer interfaces. He's a third-year Department of Energy Computational Science Graduate Fellow.
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Manage episode 489425685 series 2954335
Content provided by Sarah Webb and Krell Institute. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sarah Webb and Krell Institute or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Understanding how the brain works remains a grand scientific challenge, and it's yet another area where researchers are examining whether foundation models could help them find patterns in complex data. Joel Ye of Carnegie Mellon University talks about his work on foundation models, their potential and limitations and how others can get involved in applying these AI tools.
Joel Ye is a Ph.D. student in the program in neural computation at Carnegie Mellon University in Pittsburgh, where he studies ways to understand brain data and brain-computer interfaces. He's a third-year Department of Energy Computational Science Graduate Fellow.
33 episodes
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Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
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…
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