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Trends in Machine Learning & Deep Learning with Zachary Lipton - #556

Trends in Machine Learning & Deep Learning with Zachary Lipton - #556

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


Trends in Machine Learning & Deep Learning with Zachary Lipton - #556

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
69 minutes
Released:
Jan 27, 2022
Format:
Podcast episode

Description

Today we continue our AI Rewind 2021 series joined by a friend of the show, assistant professor at Carnegie Mellon University, and AI Rewind veteran, Zack Lipton! In our conversation with Zack, we touch on recurring themes like “NLP Eating AI” and the recent slowdown in innovation in the field, the redistribution of resources across research problems, and where the opportunities for real breakthroughs lie. We also discuss problems facing the current peer-review system, notable research from last year like the introduction of the WILDS library, and the evolution of problems (and potential solutions) in fairness, bias, and equity. Of course, we explore some of the use cases and application areas that made notable progress in 2021, what Zack is looking forward to in 2022 and beyond, and much more!

The complete show notes for this episode can be found at twimlai.com/go/556
Released:
Jan 27, 2022
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.