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The language of Machine Learning

The language of Machine Learning

FromPeople of AI


The language of Machine Learning

FromPeople of AI

ratings:
Length:
29 minutes
Released:
Mar 23, 2023
Format:
Podcast episode

Description

Meet Sharon Zhou, an adjunct faculty member at Stanford University and co-founder of Stealth Startup. Join us as we talk about the power and interconnectedness of language as we dive into generative AI models, stable diffusion, large language models, and learn how every problem – according to Sharon – is just a translation problem.    Check out Sharon’s startup here: https://goo.gle/3TENTJk    Learn more about Sharon’s courses here: Build Basic Generative Adversarial Networks (GANs) → https://goo.gle/3lr3AqU  Build Better Generative Adversarial Networks (GANs) → https://goo.gle/3JAPgUA   Apply Generative Adversarial Networks (GANs) → https://goo.gle/3ZdaoWK CS236G Generative Adversarial Networks (GANs) → https://goo.gle/3TCVhEX    Guest bio: Sharon Zhou is currently an adjunct faculty member at Stanford University where she defended her PhD (in an impressive 3.5 years) on generative AI models, advised by Andrew Ng. She is also the co-founder of Stealth Startup, working on democratizing access and ease of use of AI by making it easier to program and customize large language models. She has a passion for teaching AI and is currently teaching 80,000 students about GANs, diffusion models and more on Coursera, and was an AI advisor to key AI policymakers in Washington D.C. Fun facts about Sharon: she was the first student in the history of Harvard University to major in Classics and Computer Science, and is featured in MIT Technology Review's 35 Under 35. To top that, she is also a poet.   #AI #ML
Released:
Mar 23, 2023
Format:
Podcast episode

Titles in the series (24)

People of AI is a podcast showcasing inspiring people with interesting stories in the world of Artificial Intelligence (AI) and its subset, Machine Learning (ML). The podcast will interview leaders, practitioners, researchers and learners in the field of AI/ML and invite them to share their stories, what they are building, lessons learned along the way, and excitement for the AI/ML industry.