Kevin K. Yang: Engineering Proteins with ML

Kevin K. Yang: Engineering Proteins with ML

Author: Daniel Bashir September 28, 2023 Duration: 1:00:00

In episode 92 of The Gradient Podcast, Daniel Bashir speaks to Kevin K. Yang.

Kevin is a senior researcher at Microsoft Research (MSR) who works on problems at the intersection of machine learning and biology, with an emphasis on protein engineering. He completed his PhD at Caltech with Frances Arnold on applying machine learning to protein engineering. Before joining MSR, he was a machine learning scientist at Generate Biomedicines, where he used machine learning to optimize proteins.

Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub

Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:40) Kevin’s background

* (06:00) Protein engineering early in Kevin’s career

* (12:10) From research to real-world proteins: the process

* (17:40) Generative models + pretraining for proteins

* (22:47) Folding diffusion for protein structure generation

* (30:45) Protein evolutionary dynamics and generative models of protein sequences

* (40:03) Analogies and disanalogies between protein modeling and language models

* (41:45) In representation learning

* (45:50) Convolutions vs. transformers and inductive biases

* (49:25) Pretraining tasks for protein structure

* (51:45) More on representation learning for protein structure

* (54:06) Kevin’s thoughts on interpretability in deep learning for protein engineering

* (56:50) Multimodality in protein engineering and future directions

* (59:14) Outro

Links:

* Kevin’s Twitter and homepage

* Research

* Generative models + pre-training for proteins and chemistry

* Broad intro to techniques in the space

* Protein structure generation via folding diffusion

* Protein sequence design with deep generative models (review)

* Evolutionary velocity with protein language models predicts evolutionary dynamics of diverse proteins

* Protein generation with evolutionary diffusion: sequence is all you need

* ML for protein engineering

* ML-guided directed evolution for protein engineering (review)

* Learned protein embeddings for ML

* Adaptive machine learning for protein engineering (review)

* Multimodal deep learning for protein engineering



Get full access to The Gradient at thegradientpub.substack.com/subscribe

Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
Author: Language: English Episodes: 100

The Gradient: Perspectives on AI
Podcast Episodes
Laurence Liew: AI Singapore [not-audio_url] [/not-audio_url]

Duration: 50:28
In episode 98 of The Gradient Podcast, Daniel Bashir speaks to Laurence Liew.Laurence is the Director for AI Innovation at AI Singapore. He is driving the adoption of AI by the Singapore ecosystem through the 100 Experim…
Michael Levin & Adam Goldstein: Intelligence and its Many Scales [not-audio_url] [/not-audio_url]

Duration: 57:21
In episode 97 of The Gradient Podcast, Daniel Bashir speaks to Professor Michael Levin and Adam Goldstein. Professor Levin is a Distinguished Professor and Vannevar Bush Chair in the Biology Department at Tufts Universit…
Jonathan Frankle: From Lottery Tickets to LLMs [not-audio_url] [/not-audio_url]

Duration: 1:08:22
In episode 96 of The Gradient Podcast, Daniel Bashir speaks to Jonathan Frankle.Jonathan is the Chief Scientist at MosaicML and (as of release). Jonathan completed his PhD at MIT, where he investigated the properties of…
Nao Tokui: "Surfing" Musical Creativity with AI [not-audio_url] [/not-audio_url]

Duration: 1:02:19
In episode 95 of The Gradient Podcast, Daniel Bashir speaks to Nao Tokui.Nao Tokui is an artist/DJ and researcher based in Tokyo. While pursuing his Ph.D. at The University of Tokyo, he produced his first music album and…
Divyansh Kaushik: The Realities of AI Policy [not-audio_url] [/not-audio_url]

Duration: 1:17:44
In episode 94 of The Gradient Podcast, Daniel Bashir speaks to Divyansh Kaushik.Divyansh is the Associate Director for Emerging Technologies and National Security at the Federation of American Scientists where his focus…
Tal Linzen: Psycholinguistics and Language Modeling [not-audio_url] [/not-audio_url]

Duration: 1:14:50
In episode 93 of The Gradient Podcast, Daniel Bashir speaks to Professor Tal Linzen.Professor Linzen is an Associate Professor of Linguistics and Data Science at New York University and a Research Scientist at Google. He…
Miles Grimshaw: Benchmark, LangChain, and Investing in AI [not-audio_url] [/not-audio_url]

Duration: 1:00:47
In episode 90 of The Gradient Podcast, Daniel Bashir speaks to Miles Grimshaw.Miles is General Partner at Benchmark. He was previously a General Partner at Thrive Capital, where he helped the firm raise its fourth and fi…
Shreya Shankar: Machine Learning in the Real World [not-audio_url] [/not-audio_url]

Duration: 1:16:36
In episode 89 of The Gradient Podcast, Daniel Bashir speaks to Shreya Shankar.Shreya is a computer scientist pursuing her PhD in databases at UC Berkeley. Her research interest is in building end-to-end systems for peopl…
Stevan Harnad: AI's Symbol Grounding Problem [not-audio_url] [/not-audio_url]

Duration: 1:58:21
In episode 88 of The Gradient Podcast, Daniel Bashir speaks to Professor Stevan Harnad.Stevan Harnad is professor of psychology and cognitive science at Université du Québec à Montréal, adjunct professor of cognitive sci…