Cristóbal Valenzuela — The Next Generation of Content Creation and AI
01/19/23 • 40 min
Cristóbal Valenzuela is co-founder and CEO of Runway ML, a startup that's building the future of AI-powered content creation tools. Runway's research areas include diffusion systems for image generation.
Cris gives a demo of Runway's video editing platform. Then, he shares how his interest in combining technology with creativity led to Runway, and where he thinks the world of computation and content might be headed to next. Cris and Lukas also discuss Runway's tech stack and research.
Show notes (transcript and links): http://wandb.me/gd-cristobal-valenzuela
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⏳ Timestamps:
0:00 Intro
1:06 How Runway uses ML to improve video editing
6:04 A demo of Runway’s video editing capabilities
13:36 How Cris entered the machine learning space
18:55 Cris’ thoughts on the future of ML for creative use cases
28:46 Runway’s tech stack
32:38 Creativity, and keeping humans in the loop
36:15 The potential of audio generation and new mental models
40:01 Outro
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🎥 Runway's AI Film Festival is accepting submissions through January 23! 🎥
They are looking for art and artists that are at the forefront of AI filmmaking. Submissions should be between 1-10 minutes long, and a core component of the film should include generative content
📍 https://aiff.runwayml.com/
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📝 Links
📍 "High-Resolution Image Synthesis with Latent Diffusion Models" (Rombach et al., 2022)", the research paper behind Stable Diffusion: https://research.runwayml.com/publications/high-resolution-image-synthesis-with-latent-diffusion-models
📍 Lexman Artificial, a 100% AI-generated podcast: https://twitter.com/lexman_ai
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Connect with Cris and Runway:
📍 Cris on Twitter: https://twitter.com/c_valenzuelab
📍 Runway on Twitter: https://twitter.com/runwayml
📍 Careers at Runway: https://runwayml.com/careers/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan
---
Subscribe and listen to Gradient Dissent today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Cristóbal Valenzuela is co-founder and CEO of Runway ML, a startup that's building the future of AI-powered content creation tools. Runway's research areas include diffusion systems for image generation.
Cris gives a demo of Runway's video editing platform. Then, he shares how his interest in combining technology with creativity led to Runway, and where he thinks the world of computation and content might be headed to next. Cris and Lukas also discuss Runway's tech stack and research.
Show notes (transcript and links): http://wandb.me/gd-cristobal-valenzuela
---
⏳ Timestamps:
0:00 Intro
1:06 How Runway uses ML to improve video editing
6:04 A demo of Runway’s video editing capabilities
13:36 How Cris entered the machine learning space
18:55 Cris’ thoughts on the future of ML for creative use cases
28:46 Runway’s tech stack
32:38 Creativity, and keeping humans in the loop
36:15 The potential of audio generation and new mental models
40:01 Outro
---
🎥 Runway's AI Film Festival is accepting submissions through January 23! 🎥
They are looking for art and artists that are at the forefront of AI filmmaking. Submissions should be between 1-10 minutes long, and a core component of the film should include generative content
📍 https://aiff.runwayml.com/
--
📝 Links
📍 "High-Resolution Image Synthesis with Latent Diffusion Models" (Rombach et al., 2022)", the research paper behind Stable Diffusion: https://research.runwayml.com/publications/high-resolution-image-synthesis-with-latent-diffusion-models
📍 Lexman Artificial, a 100% AI-generated podcast: https://twitter.com/lexman_ai
---
Connect with Cris and Runway:
📍 Cris on Twitter: https://twitter.com/c_valenzuelab
📍 Runway on Twitter: https://twitter.com/runwayml
📍 Careers at Runway: https://runwayml.com/careers/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan
---
Subscribe and listen to Gradient Dissent today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Previous Episode
Jeremy Howard — The Simple but Profound Insight Behind Diffusion
Jeremy Howard is a co-founder of fast.ai, the non-profit research group behind the popular massive open online course "Practical Deep Learning for Coders", and the open source deep learning library "fastai".
Jeremy is also a co-founder of #Masks4All, a global volunteer organization founded in March 2020 that advocated for the public adoption of homemade face masks in order to help slow the spread of COVID-19. His Washington Post article "Simple DIY masks could help flatten the curve." went viral in late March/early April 2020, and is associated with the U.S CDC's change in guidance a few days later to recommend wearing masks in public.
In this episode, Jeremy explains how diffusion works and how individuals with limited compute budgets can engage meaningfully with large, state-of-the-art models. Then, as our first-ever repeat guest on Gradient Dissent, Jeremy revisits a previous conversation with Lukas on Python vs. Julia for machine learning.
Finally, Jeremy shares his perspective on the early days of COVID-19, and what his experience as one of the earliest and most high-profile advocates for widespread mask-wearing was like.
Show notes (transcript and links): http://wandb.me/gd-jeremy-howard-2
---
⏳ Timestamps:
0:00 Intro
1:06 Diffusion and generative models
14:40 Engaging with large models meaningfully
20:30 Jeremy's thoughts on Stable Diffusion and OpenAI
26:38 Prompt engineering and large language models
32:00 Revisiting Julia vs. Python
40:22 Jeremy's science advocacy during early COVID days
1:01:03 Researching how to improve children's education
1:07:43 The importance of executive buy-in
1:11:34 Outro
1:12:02 Bonus: Weights & Biases
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📝 Links
📍 Jeremy's previous Gradient Dissent episode (8/25/2022): http://wandb.me/gd-jeremy-howard
📍 "Simple DIY masks could help flatten the curve. We should all wear them in public.", Jeremy's viral Washington Post article: https://www.washingtonpost.com/outlook/2020/03/28/masks-all-coronavirus/
📍 "An evidence review of face masks against COVID-19" (Howard et al., 2021), one of the first peer-reviewed papers on the effectiveness of wearing masks: https://www.pnas.org/doi/10.1073/pnas.2014564118
📍 Jeremy's Twitter thread summary of "An evidence review of face masks against COVID-19": https://twitter.com/jeremyphoward/status/1348771993949151232
📍 Read more about Jeremy's mask-wearing advocacy: https://www.smh.com.au/world/north-america/australian-expat-s-push-for-universal-mask-wearing-catches-fire-in-the-us-20200401-p54fu2.html
---
Connect with Jeremy and fast.ai:
📍 Jeremy on Twitter: https://twitter.com/jeremyphoward
📍 fast.ai on Twitter: https://twitter.com/FastDotAI
📍 Jeremy on LinkedIn: https://www.linkedin.com/in/howardjeremy/
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan
Next Episode
Sarah Catanzaro — Remembering the Lessons of the Last AI Renaissance
Sarah Catanzaro is a General Partner at Amplify Partners, and one of the leading investors in AI and ML. Her investments include RunwayML, OctoML, and Gantry.
Sarah and Lukas discuss lessons learned from the "AI renaissance" of the mid 2010s and compare the general perception of ML back then to now. Sarah also provides insights from her perspective as an investor, from selling into tech-forward companies vs. traditional enterprises, to the current state of MLOps/developer tools, to large language models and hype bubbles.
Show notes (transcript and links): http://wandb.me/gd-sarah-catanzaro
---
⏳ Timestamps:
0:00 Intro
1:10 Lessons learned from previous AI hype cycles
11:46 Maintaining technical knowledge as an investor
19:05 Selling into tech-forward companies vs. traditional enterprises
25:09 Building point solutions vs. end-to-end platforms
36:27 LLMS, new tooling, and commoditization
44:39 Failing fast and how startups can compete with large cloud vendors
52:31 The gap between research and industry, and vice versa
1:00:01 Advice for ML practitioners during hype bubbles
1:03:17 Sarah's thoughts on Rust and bottlenecks in deployment
1:11:23 The importance of aligning technology with people
1:15:58 Outro
---
📝 Links
📍 "Operationalizing Machine Learning: An Interview Study" (Shankar et al., 2022), an interview study on deploying and maintaining ML production pipelines: https://arxiv.org/abs/2209.09125
---
Connect with Sarah:
📍 Sarah on Twitter: https://twitter.com/sarahcat21
📍 Sarah's Amplify Partners profile: https://www.amplifypartners.com/investment-team/sarah-catanzaro
---
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan
---
Subscribe and listen to Gradient Dissent today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
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