Suhail Doshi: The Future of Computer Vision

Suhail Doshi: The Future of Computer Vision

Author: Daniel Bashir May 16, 2024 Duration: 1:08:07

Episode 123

I spoke with Suhail Doshi about:

* Why benchmarks aren’t prepared for tomorrow’s AI models

* How he thinks about artists in a world with advanced AI tools

* Building a unified computer vision model that can generate, edit, and understand pixels.

Suhail is a software engineer and entrepreneur known for founding Mixpanel, Mighty Computing, and Playground AI (they’re hiring!).

Reach me at editor@thegradient.pub for feedback, ideas, guest suggestions.

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

Outline:

* (00:00) Intro

* (00:54) Ad read — MLOps conference

* (01:30) Suhail is *not* in pivot hell but he *is* all-in on 50% AI-generated music

* (03:45) AI and music, similarities to Playground

* (07:50) Skill vs. creative capacity in art

* (12:43) What we look for in music and art

* (15:30) Enabling creative expression

* (18:22) Building a unified computer vision model, underinvestment in computer vision

* (23:14) Enhancing the aesthetic quality of images: color and contrast, benchmarks vs user desires

* (29:05) “Benchmarks are not prepared for how powerful these models will become”

* (31:56) Personalized models and personalized benchmarks

* (36:39) Engaging users and benchmark development

* (39:27) What a foundation model for graphics requires

* (45:33) Text-to-image is insufficient

* (46:38) DALL-E 2 and Imagen comparisons, FID

* (49:40) Compositionality

* (50:37) Why Playground focuses on images vs. 3d, video, etc.

* (54:11) Open source and Playground’s strategy

* (57:18) When to stop open-sourcing?

* (1:03:38) Suhail’s thoughts on AGI discourse

* (1:07:56) Outro

Links:

* Playground homepage

* Suhail on Twitter



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
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…
Kevin K. Yang: Engineering Proteins with ML [not-audio_url] [/not-audio_url]

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 emp…
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…