Emad Mostaque — Stable Diffusion, Stability AI, and What’s Next
11/15/22 • 70 min
1 Listener
Emad Mostaque is CEO and co-founder of Stability AI, a startup and network of decentralized developer communities building open AI tools. Stability AI is the company behind Stable Diffusion, the well-known, open source, text-to-image generation model.
Emad shares the story and mission behind Stability AI (unlocking humanity's potential with open AI technology), and explains how Stability's role as a community catalyst and compute provider might evolve as the company grows. Then, Emad and Lukas discuss what the future might hold in store: big models vs "optimal" models, better datasets, and more decentralization.
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🎶 Special note: This week’s theme music was composed by Weights & Biases’ own Justin Tenuto with help from Harmonai’s Dance Diffusion.
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Show notes (transcript and links): http://wandb.me/gd-emad-mostaque
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⏳ Timestamps:
00:00 Intro
00:42 How AI fits into the safety/security industry
09:33 Event matching and object detection
14:47 Running models on the right hardware
17:46 Scaling model evaluation
23:58 Monitoring and evaluation challenges
26:30 Identifying and sorting issues
30:27 Bridging vision and language domains
39:25 Challenges and promises of natural language technology
41:35 Production environment
43:15 Using synthetic data
49:59 Working with startups
53:55 Multi-task learning, meta-learning, and user experience
56:44 Optimization and testing across multiple platforms
59:36 Outro
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Connect with Jehan and Motorola Solutions:
📍 Jehan on LinkedIn: https://www.linkedin.com/in/jehanw/
📍 Jehan on Twitter: https://twitter.com/jehan/
📍 Motorola Solutions on Twitter: https://twitter.com/MotoSolutions/
📍 Careers at Motorola Solutions: https://www.motorolasolutions.com/en_us/about/careers.html
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💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan, Lavanya Shukla, Anish Shah
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Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Emad Mostaque is CEO and co-founder of Stability AI, a startup and network of decentralized developer communities building open AI tools. Stability AI is the company behind Stable Diffusion, the well-known, open source, text-to-image generation model.
Emad shares the story and mission behind Stability AI (unlocking humanity's potential with open AI technology), and explains how Stability's role as a community catalyst and compute provider might evolve as the company grows. Then, Emad and Lukas discuss what the future might hold in store: big models vs "optimal" models, better datasets, and more decentralization.
-
🎶 Special note: This week’s theme music was composed by Weights & Biases’ own Justin Tenuto with help from Harmonai’s Dance Diffusion.
-
Show notes (transcript and links): http://wandb.me/gd-emad-mostaque
-
⏳ Timestamps:
00:00 Intro
00:42 How AI fits into the safety/security industry
09:33 Event matching and object detection
14:47 Running models on the right hardware
17:46 Scaling model evaluation
23:58 Monitoring and evaluation challenges
26:30 Identifying and sorting issues
30:27 Bridging vision and language domains
39:25 Challenges and promises of natural language technology
41:35 Production environment
43:15 Using synthetic data
49:59 Working with startups
53:55 Multi-task learning, meta-learning, and user experience
56:44 Optimization and testing across multiple platforms
59:36 Outro
-
Connect with Jehan and Motorola Solutions:
📍 Jehan on LinkedIn: https://www.linkedin.com/in/jehanw/
📍 Jehan on Twitter: https://twitter.com/jehan/
📍 Motorola Solutions on Twitter: https://twitter.com/MotoSolutions/
📍 Careers at Motorola Solutions: https://www.motorolasolutions.com/en_us/about/careers.html
-
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan, Lavanya Shukla, Anish Shah
-
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Previous Episode
Jehan Wickramasuriya — AI in High-Stress Scenarios
Jehan Wickramasuriya is the Vice President of AI, Platform & Data Services at Motorola Solutions, a global leader in public safety and enterprise security.
In this episode, Jehan discusses how Motorola Solutions uses AI to simplify data streams to help maximize human potential in high-stress situations. He also shares his thoughts on augmenting synthetic data with real data and the challenges posed in partnering with startups.
Show notes (transcript and links): http://wandb.me/gd-jehan-wickramasuriya
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⏳ Timestamps:
00:00 Intro
00:42 How AI fits into the safety/security industry
09:33 Event matching and object detection
14:47 Running models on the right hardware
17:46 Scaling model evaluation
23:58 Monitoring and evaluation challenges
26:30 Identifying and sorting issues
30:27 Bridging vision and language domains
39:25 Challenges and promises of natural language technology
41:35 Production environment
43:15 Using synthetic data
49:59 Working with startups
53:55 Multi-task learning, meta-learning, and user experience
56:44 Optimization and testing across multiple platforms
59:36 Outro
-
Connect with Jehan and Motorola Solutions:
📍 Jehan on LinkedIn: https://www.linkedin.com/in/jehanw/
📍 Jehan on Twitter: https://twitter.com/jehan/
📍 Motorola Solutions on Twitter: https://twitter.com/MotoSolutions/
📍 Careers at Motorola Solutions: https://www.motorolasolutions.com/en_us/about/careers.html
-
💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Cayla Sharp, Angelica Pan, Lavanya Shukla
-
Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
Next Episode
D. Sculley — Technical Debt, Trade-offs, and Kaggle
D. Sculley is CEO of Kaggle, the beloved and well-known data science and machine learning community.
D. discusses his influential 2015 paper "Machine Learning: The High Interest Credit Card of Technical Debt" and what the current challenges of deploying models in the real world are now, in 2022. Then, D. and Lukas chat about why Kaggle is like a rain forest, and about Kaggle's historic, current, and potential future roles in the broader machine learning community.
Show notes (transcript and links): http://wandb.me/gd-d-sculley
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⏳ Timestamps:
0:00 Intro
1:02 Machine learning and technical debt
11:18 MLOps, increased stakes, and realistic expectations
19:12 Evaluating models methodically
25:32 Kaggle's role in the ML world
33:34 Kaggle competitions, datasets, and notebooks
38:49 Why Kaggle is like a rain forest
44:25 Possible future directions for Kaggle
46:50 Healthy competitions and self-growth
48:44 Kaggle's relevance in a compute-heavy future
53:49 AutoML vs. human judgment
56:06 After a model goes into production
1:00:00 Outro
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Connect with D. and Kaggle:
📍 D. on LinkedIn: https://www.linkedin.com/in/d-sculley-90467310/
📍 Kaggle on Twitter: https://twitter.com/kaggle
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Links:
📍 "Machine Learning: The High Interest Credit Card of Technical Debt" (Sculley et al. 2014): https://research.google/pubs/pub43146/
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💬 Host: Lukas Biewald
📹 Producers: Riley Fields, Angelica Pan, Anish Shah, Lavanya Shukla
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Subscribe and listen to our podcast today!
👉 Apple Podcasts: http://wandb.me/apple-podcasts
👉 Google Podcasts: http://wandb.me/google-podcasts
👉 Spotify: http://wandb.me/spotify
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