Quantifying our confidence in neural networks and AI

We’re thrilled to welcome back Josh Starmer back to the USF Data Science Speaker Series!

Description: Although Large Language Models and AI are known to generate false and misleading responses to prompts, relatively little effort has gone into understanding how we can quantify the confidence we should have in the output from these models. In this seminar, I will illustrate the problem using a simple neural network and then demonstrate two methods for quantifying our confidence in the model outputs. I will then show how these methods can be applied to Large Language Models and AI.

About the Speaker: Josh Starmer is the person behind the popular YouTube channel, “StatQuest with Josh Starmer.” Since 2016, Josh has used an innovative and unique visual style to clearly explain Statistics, Data Science and Machine Learning concepts and algorithms to curious people all over the world. Rather than dumb down the material, Josh brings people up with simple examples worked through, step-by-step, using pictures to make sure every main idea is easy to understand and remember. By breaking down even the most complicated algorithms into bite sized pieces, StatQuest has helped people, all over the world, win data science competitions, pass exams, graduate from school, and get jobs and promotions.

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