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AI Chronicles: Explainability Vs. Complexity

AI once again takes center stage in this week’s Fish Fry podcast! Johanna Pingel from MathWorks and I discuss the differences between complexity vs. explainability in artificial intelligence, how you will know if explainability is right for your application and how explainability will impact the future of AI. Also this week, I examine how AI could help predict extreme wildfire danger.

 

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Links for November 4, 2022

More information about MathWorks

Gwangju Institute of Science and Technology Researchers Design AI-based Model that Predicts Extreme Wildfire Danger (GIST)

Deep Learning Provides Substantial Improvements to County-Level Fire Weather Forecasting Over the Western United States (Journal of Advances in Modeling Earth Systems)

 

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Shishpal Rawat, Chairman – Accellera Systems Initiative

Kevin Bromber, CEO – myDevices

Daniel Hansson, CEO – Verifyter

Mark Papermaster, CTO – AMD

David Fried, CTO – Coventor

Dr. Steven LeBoeuf, President – Valencell

David Dutton, CEO – Silvaco

Bob Niemiec, CEO – TwistThink

Allan Martinson, COO – Starship Technologies

Zhihong Liu, Chairman and CEO – ProPlus Solutions

Taher Madraswala, CEO and President – Open-Silicon

Kapil Shankar, CEO and Director – AnDAPT

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Kim Rowe, Founder and CEO — RoweBots

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Alan Grau, CEO — Icon Labs

Carl Alberty, Vice President – Cirrus Logic

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Finbarr Moynihan, General Manager — MediaTek

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Harold Blomquist, CEO – Helix Semiconductor

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Dan Goehl, Co-founder and Chief Business Officer – UltraSense Systems

Charlie Green, Chief Operating & Technical Officer – Powercast

 

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