Explorez tous les épisodes du podcast Gradient Dissent: Conversations on AI
| Titre | Date | Durée | |
|---|---|---|---|
| Elevating ML Infrastructure with Modal Labs CEO Erik Bernhardsson | 26 Sep 2024 | 00:49:39 | |
In this episode of Gradient Dissent, Erik Bernhardsson, CEO & Founder of Modal Labs, joins host Lukas Biewald to discuss the future of machine learning infrastructure. They explore how Modal is enhancing the developer experience, handling large-scale GPU workloads, and simplifying cloud execution for data teams. If you’re into AI, data pipelines, or building robust ML systems, this episode is packed with valuable insights! 🎙 *Listen on Apple Podcasts*: http://wandb.me/apple-podcasts 🎙 *Listen on Spotify*: http://wandb.me/spotify ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Erik Bernhardsson: https://www.linkedin.com/in/erikbern/ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| From No-Code to AI-Powered Apps with Airtable’s Howie Liu | 12 Sep 2024 | 01:12:57 | |
In this episode of Gradient Dissent, Howie Lou, CEO of Airtable, joins host Lukas Biewald to dive into Airtable's transformation from a no-code app builder to a platform capable of supporting complex AI-driven workflows. They discuss the strategic decisions that propelled Airtable's growth, the challenges of scaling AI in enterprise settings, and the future of AI in business operations. Discover how Airtable is reshaping digital transformation and why flexibility and innovation are key in today's tech landscape. Tune in now to learn about the evolving role of AI in business and product development. 🎙 *Listen on Apple Podcasts*: http://wandb.me/apple-podcasts 🎙 *Listen on Spotify*: http://wandb.me/spotify ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Howie Liu: https://www.linkedin.com/in/howieliu/ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| Accelerating drug discovery with AI: Insights from Isomorphic Labs | 25 Apr 2024 | 01:10:23 | |
In this episode of Gradient Dissent, Isomorphic Labs Chief AI Officer Max Jaderberg, and Chief Technology Officer Sergei Yakneen join our host Lukas Biewald to discuss the advancements in biotech and drug discovery being unlocked with machine learning. With backgrounds in advanced AI research at DeepMind, Max and Sergei offer their unique insights into the challenges and successes of applying AI in a complex field like biotechnology. They share their journey at Isomorphic Labs, a company dedicated to revolutionizing drug discovery with AI. In this episode, they discuss the transformative impact of deep learning on the drug development process and Isomorphic Labs' strategy to innovate from molecular design to clinical trials. You’ll come away with valuable insights into the challenges of applying AI in biotech, the role of AI in streamlining the drug discovery pipeline, and peer into the future of AI-driven solutions in healthcare. Connect with Sergei Yakneen & Max Jaderberg: https://www.linkedin.com/in/maxjaderberg/ https://www.linkedin.com/in/yakneensergei/ https://twitter.com/SergeiIakhnin https://twitter.com/maxjaderberg Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb | |||
| Peter Skomoroch — Product Management for AI | 22 Jul 2020 | 01:27:24 | |
👨🏻💻Our guest on this episode of Gradient Dissent is Peter Skomoroch!
Peter is the former head of data products at Workday and LinkedIn. Previously, he was the cofounder and CEO of venture-backed deep learning startup SkipFlag, which was acquired by Workday, and a principal data scientist at LinkedIn.
Check out his recent publication: What you need to know about product management for AI
https://www.oreilly.com/radar/what-you-need-to-know-about-product-management-for-ai/
Follow Peter on Twitter:
https://twitter.com/peteskomoroch
And read some of his other work:
Pangloss: Fast Entity Linking in Noisy Text Environments
Large-Scale Hierarchical Topic Models
Visit our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Soundcloud, Apple, and Spotify!
YouTube: https://bit.ly/32NzZvI
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Josh Tobin — Productionizing ML Models | 08 Jul 2020 | 00:48:19 | |
Josh Tobin is a researcher working at the intersection of machine learning and robotics. His research focuses on applying deep reinforcement learning, generative models, and synthetic data to problems in robotic perception and control.
Additionally, he co-organizes a machine learning training program for engineers to learn about production-ready deep learning called Full Stack Deep Learning. https://fullstackdeeplearning.com/
Josh did his PhD in Computer Science at UC Berkeley advised by Pieter Abbeel and was a research scientist at OpenAI for 3 years during his PhD.
Finally, Josh created this amazing field guide on troubleshooting deep neural networks:
http://josh-tobin.com/assets/pdf/troubleshooting-deep-neural-networks-01-19.pdf
Follow Josh on twitter: https://twitter.com/josh_tobin
And on his website:http://josh-tobin.com/
Visit our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Youtube, Apple, and Spotify!
Youtube: https://www.youtube.com/playlist?list=PLD80i8An1OEEb1jP0sjEyiLG8ULRXFob_
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Miles Brundage — Societal Impacts of Artificial Intelligence | 01 Jul 2020 | 01:02:17 | |
Miles Brundage researches the societal impacts of artificial intelligence and how to make sure they go well. In 2018, he joined OpenAI, as a Research Scientist on the Policy team. Previously, he was a Research Fellow at the University of Oxford's Future of Humanity Institute and served as a member of Axon's AI and Policing Technology Ethics Board.
Keep up with Miles on his website: https://www.milesbrundage.com/
and on Twitter: https://twitter.com/miles_brundage
Visit our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Soundcloud, Apple, and Spotify!
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Hamel Husain — Building Machine Learning Tools | 24 Jun 2020 | 00:36:05 | |
Hamel Husain is a Staff Machine Learning Engineer at Github. He has extensive experience building data analytics and predictive modeling solutions for a wide range of industries, including: hospitality, telecom, retail, restaurant, entertainment and finance. He has built large data science teams (50+) from the ground up and have extensive experience building solutions as an individual contributor.
Follow Hamel on Twitter:
https://twitter.com/HamelHusain
And on his website: http://hamel.io/
Learn more about Github Actions:
https://github.com/features/actions
and the CodeSearchNet Challenge:
https://github.blog/2019-09-26-introducing-the-codesearchnet-challenge/
Visit our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Apple, and Spotify!
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Peter Welinder — Deep Reinforcement Learning and Robotics | 17 Jun 2020 | 00:54:17 | |
Peter Welinder is a research scientist and roboticist at OpenAI. Before that, he was an engineer at Dropbox and ran the machine learning team, and before that, he co-founded Anchovi Labs a startup using Computer Vision to organize photos that was acquired by Dropbox in 2012. In this episode of our podcast, Peter shares his experiences and the challenges associated with building a robotic hand that can solve a rubix cube.
Read some of Peter’s Articles:
https://openai.com/blog/authors/peter/
Follow Peter on Twitter:
https://twitter.com/npew
Check out our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Apple, and Spotify!
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Vicki Boykis — Machine Learning Across Industries | 04 Jun 2020 | 00:34:02 | |
👩💻Today our guest is Vicki Boykis!
Vicki is a senior consultant in machine learning and engineering and works with clients to build holistic data products used for decision-making. She's previously spoken at PyData, taught SQL for GirlDevelopIt, and blogs about data pipelines and open internet.
Follow her on her website: vickiboykis.com
On twitter: https://twitter.com/vboykis
and subscribe to her newsletter: vicki.substack.com
Check out our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Apple and Spotify!
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Angela & Danielle — Designing ML Models for Millions of Consumer Robots | 06 May 2020 | 00:52:38 | |
👩💻👩💻On this episode of Gradient Dissent our guests are Angela Bassa and Danielle Dean!
Angela is an expert in building and leading data teams. An MIT-trained and Edelman-award-winning mathematician, she has over 15 years of experience across industries—spanning finance, life sciences, agriculture, marketing, energy, software, and robotics. Angela heads Data Science and Machine Learning at iRobot, where her teams help bring intelligence to a global fleet of millions of consumer robots. She is also a renowned keynote speaker and author, with credits including the Wall Street Journal and Harvard Business Review.
Follow Angela on twitter: https://twitter.com/angebassa
And on her website: https://www.angelabassa.com/
Danielle Dean, PhD is the Technical Director of Machine Learning at iRobot where she is helping lead the intelligence revolution for robots. She leads a team that leverages machine learning, reinforcement learning, and software engineering to build algorithms that will result in massive improvements in our robots. Before iRobot, Danielle was a Principal Data Scientist Lead at Microsoft Corp. in AzureCAT Engineering within the Cloud AI Platform division.
Follow Danielle on Twitter: https://twitter.com/danielleodean
Check out our podcasts homepage for transcripts and more episodes!
www.wandb.com/podcast
🔊 Get our podcast on Apple and Spotify!
Apple Podcasts: https://bit.ly/2WdrUvI
Spotify: https://bit.ly/2SqtadF
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Jack Clark — Building Trustworthy AI Systems | 22 Apr 2020 | 00:55:56 | |
Jack Clark is the Strategy and Communications Director at OpenAI and formerly worked as the world’s only neural network reporter at Bloomberg. Lukas and Jack discuss AI policy, ethics, and the responsibilities of AI researchers.
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims by OpenAI: https://arxiv.org/abs/2004.07213
Follow Jack Clark on Twitter: twitter.com/jackclarkSF
Read more posts by Jack on his website: https://jack-clark.net/
Get our podcast on Apple and Spotify!
https://podcasts.apple.com/us/podcast/gradient-dissent-weights-biases/id1504567418
https://open.spotify.com/show/7o9r3fFig3MhTJwehXDbXm
🤖Gradient Dissent by Weights and Biases
Get a behind-the-scenes look at how industry leaders are using machine learning in the real world. While building experiment tracking tools, we’ve had the opportunity to learn about how different teams are building and deploying models. In this podcast, we share some of the insights and stories we’ve heard along the way. Follow Gradient Dissent for weekly machine learning updates, and be part of the conversation.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Rachael Tatman — Conversational AI and Linguistics | 07 Apr 2020 | 00:36:51 | |
🏅 See how W&B is your secret weapon to make it onto the Kaggle leaderboards - https://www.wandb.com/kaggle
👩💻Rachael Tatman is a developer advocate for Rasa, where she helps developers build and deploy conversational AI applications using their open source framework. 🤖💬 She has a PhD in Linguistics from the University of Washington where she researched computational sociolinguistics, or how our social identity affects the way we use language in computational contexts. Previously she was a data scientist at Kaggle where she’s still a Grandmaster.
💻Keep up with Rachael on her website: http://www.rctatman.com/
🐦Follow Rachael on twitter: https://twitter.com/rctatman
Get our podcast on Apple and Spotify!
https://podcasts.apple.com/us/podcast/gradient-dissent-weights-biases/id1504567418
https://open.spotify.com/show/7o9r3fFig3MhTJwehXDbXm
🤖Gradient Dissent by Weights and Biases
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
- Blog: https://www.wandb.com/articles
- Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
- Continue the conversation on our slack community - http://bit.ly/wandb-forum
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars | 21 Mar 2020 | 00:44:56 | |
👨🏻💻Nicolas Koumchatzky is the Director of AI infrastructure at NVIDIA, where he's responsible for MagLev, the production-grade machine learning platform by NVIDIA. His team supports diverse ML use cases: autonomous vehicles, medical imaging, super resolution, predictive analytics, cyber security, robotics. He started as a Quant in Paris, then joined Madbits, a startup specialized on using deep learning for content understanding. When Madbits was acquired by Twitter in 2014, he joined as a deep learning expert and led a few projects in Cortex, include a real-time live video classification product for Periscope. In 2016, he focused on building an scalable AI platform for the company. Early 2017, he became the lead for the Cortex team. He joined NVIDIA in 2018.
🐦Follow Nicolas on twitter: https://twitter.com/nkoumchatzky
🛠Maglev: https://blogs.nvidia.com/blog/2018/09/13/how-maglev-speeds-autonomous-vehicles-to-superhuman-levels-of-safety/
✍️Scalable Active Learning for Autonomous Driving: https://medium.com/nvidia-ai/scalable-active-learning-for-autonomous-driving-a-practical-implementation-and-a-b-test-4d315ed04b5f
✍️Active Learning – Finding the right self-driving training data doesn’t have to take a swarm of human labelers: https://blogs.nvidia.com/blog/2020/01/16/what-is-active-learning/
👫Continue the conversation on our slack community - http://bit.ly/wandb-forum
🤖Gradient Dissent by Weights and Biases
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
* Visualize your Scikit model performance with W&B - https://app.wandb.ai/lavanyashukla/visualize-sklearn/reports/Visualizing-Sklearn-With-Weights-and-Biases--Vmlldzo0ODIzNg
* Blog: https://www.wandb.com/articles
* Gallery: See what you can create with W&B - https://app.wandb.ai/gallery
🎙Host: Lukas Biewald - https://twitter.com/l2k
👩🏼💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai
📹Editor: Cayla Sharp - http://caylasharp.com/ | |||
| Redefining AI Hardware for Enterprise with SambaNova’s Rodrigo Liang | 11 Apr 2024 | 00:53:04 | |
🚀 Discover the cutting-edge AI hardware development for enterprises in this episode of Gradient Dissent, featuring Rodrigo Liang, CEO of SambaNova Systems. Rodrigo Liang’s journey from Oracle to founding SambaNova is a tale of innovation and determination. In this episode, Rodrigo discusses the importance of specialized hardware in unlocking AI's potential for Enterprise businesses and SambaNova's mission to deliver comprehensive AI solutions from chips to models. Explore the critical insights on navigating the challenges of introducing AI to executives and the evolution of AI applications within large enterprises, and get a glimpse into the future of AI in the business world. 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Rodrigo Liang: https://www.linkedin.com/in/rodrigo-liang/ https://twitter.com/RodrigoLiang
Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| Brandon Rohrer — Machine Learning in Production for Robots | 11 Mar 2020 | 00:34:31 | |
👨🏻💻Brandon Rohrer is a Mechanical Engineer turned Data Scientist. He’s currently a Principal Data Scientist at iRobot and has an incredibly popular Machine Learning course at e2eML where he’s made some wildly popular videos on convolutional neural networks and deep learning. His fascination with robots began after watching Luke Skywalker’s prosthetic hand in the Empire Strikes Back. He turned this fascination into a PhD from MIT and subsequently found his way to building some incredible data science products at Facebook, Microsoft and now at iRobot.
✍️Brandon’s brilliant machine learning course: http://e2eml.school/
🐦Follow Brandon on twitter: https://twitter.com/_brohrer_
👫Continue the conversation on our slack community - http://bit.ly/wandb-forum
🤖Gradient Dissent by Weights and Biases - http://wandb.com
We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it.
Today our guest is Brandon Rohrer.
👩🏼🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.
• Visualize your Scikit model performance with W&B - https://app.wandb.ai/lavanyashukla/visualize-sklearn/reports/Visualizing-Sklearn-With-Weights-and-Biases--Vmlldzo0ODIzNg
• Blog: https://www.wandb.com/articles
• Gallery: See what you can create with W&B - https://app.wandb.ai/gallery | |||
| Navigating the Vector Database Landscape with Pinecone's Edo Liberty | 28 Mar 2024 | 01:06:05 | |
🚀 This episode of Gradient Dissent welcomes Edo Liberty, the mind behind Pinecone's revolutionary vector database technology. As a former leader at Amazon AI Labs and Yahoo's New York lab, Edo Liberty's extensive background in AI research and development showcases the complexities behind vector databases and their essential role in enhancing AI's capabilities. Discover the pivotal moments and key decisions that have defined Pinecone's journey, learn about the different embedding strategies that are reshaping AI applications, and understand how Pinecone's success has had a profound impact on the technology landscape. Connect with Edo Liberty: https://www.linkedin.com/in/edo-liberty-4380164/ https://twitter.com/EdoLiberty Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| Transforming Data into Business Solutions with Salesforce AI CEO, Clara Shih | 14 Mar 2024 | 00:58:24 | |
🚀 In this episode of Gradient Dissent, we explore the revolutionary impact of AI across industries with Clara Shih, CEO of Salesforce AI and Founder of Hearsay Systems. Dive into Salesforce AI's cutting-edge approach to customer service through AI, the importance of a trust-first strategy, and the future of AI policies and education. Learn how Salesforce empowers businesses and shapes the future with AI innovations like Prompt Builder and Copilot Studio. Whether you're an AI enthusiast, a business leader, or someone curious about the future of technology, this discussion offers valuable insights into navigating the rapidly evolving world of AI. ✅ Subscribe to Weights & Biases YouTube → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google Connect with Clara: https://www.linkedin.com/in/clarashih/ Follow Weights & Biases: | |||
| Upgrading Your Health: Navigating AI's Future In Healthcare with John Halamka of Mayo Clinic Platform | 29 Feb 2024 | 01:04:24 | |
In the newest episode of Gradient Dissent, we explore the intersecting worlds of AI and Healthcare with John Halamka, President of the Mayo Clinic Platform. Journey with us down John Halamka's remarkable path from his early tech startup days to leading innovations as the President of the Mayo Clinic Platform, one of the world's most esteemed healthcare institutions. This deep dive into AI's role in modern medicine covers the technology's evolution, its potential to redefine patient care, and the visionary work of Mayo Clinic Platform in harnessing AI responsibly. Explore the misconceptions surrounding AI in healthcare and discover the ethical and regulatory frameworks guiding its application. Glimpse into the future with Halamka's visionary perspective on AI's potential to democratize and revolutionize healthcare across the globe. Join us for an enlightening discussion on the challenges, triumphs, and the horizon of AI in healthcare through the lens of John Halamka's pioneering experiences. 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube ✅ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb | |||
| Shaping the World of Robotics with Chelsea Finn | 15 Feb 2024 | 00:53:46 | |
In the newest episode of Gradient Dissent, Chelsea Finn, Assistant Professor at Stanford's Computer Science Department, discusses the forefront of robotics and machine learning. Discover her groundbreaking work, where two-armed robots learn to cook shrimp (messes included!), and discuss how robotic learning could transform student feedback in education. We'll dive into the challenges of developing humanoid and quadruped robots, explore the limitations of simulated environments and discuss why real-world experience is key for adaptable machines. Plus, Chelsea will offer a glimpse into the future of household robotics and why it may be a few years before a robot is making your bed. Whether you're an AI enthusiast, a robotics professional, or simply curious about the potential and future of the technology, this episode offers unique insights into the evolving world of robotics and where it's headed next. *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Chelsea Finn: https://www.linkedin.com/in/cbfinn/ https://twitter.com/chelseabfinn Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| The Power of AI in Search with You.com's Richard Socher | 01 Feb 2024 | 01:08:26 | |
In the latest episode of Gradient Dissent, Richard Socher, CEO of You.com, shares his insights on the power of AI in search. The episode focuses on how advanced language models like GPT-4 are transforming search engines and changing the way we interact with digital platforms. The discussion covers the practical applications and challenges of integrating AI into search functionality, as well as the ethical considerations and future implications of AI in our digital lives. Join us for an enlightening conversation on how AI and you.com are reshaping how we access and interact with information online. *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz Timestamps: 00:00 - Introduction to Gradient Dissent Podcast 00:48 - Richard Socher’s Journey: From Linguistic Computer Science to AI 06:42 - The Genesis and Evolution of MetaMind 13:30 - Exploring You.com's Approach to Enhanced Search 18:15 - Demonstrating You.com's AI in Mortgage Calculations 24:10 - The Power of AI in Search: A Deep Dive with You.com 30:25 - Security Measures in Running AI-Generated Code 35:50 - Building a Robust and Secure AI Tech Stack 42:33 - The Role of AI in Automating and Transforming Digital Work 48:50 - Discussing Ethical Considerations and the Societal Impact of AI 55:15 - Envisioning the Future of AI in Daily Life and Work 01:02:00 - Reflecting on the Evolution of AI and Its Future Prospects 01:05:00 - Closing Remarks and Podcast Wrap-Up 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Richard Socher: https://www.linkedin.com/in/richardsocher/ https://twitter.com/RichardSocher Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| AI’s Future: Investment & Impact with Sarah Guo and Elad Gil | 18 Jan 2024 | 01:04:14 | |
Explore the Future of Investment & Impact in AI with Host Lukas Biewald and Guests Elad Gill and Sarah Guo of the No Priors podcast. Sarah is the founder of Conviction VC, an AI-centric $100 million venture fund. Elad, a seasoned entrepreneur and startup investor, boasts an impressive portfolio in over 40 companies, each valued at $1 billion or more, and wrote the influential "High Growth Handbook." Join us for a deep dive into the nuanced world of AI, where we'll explore its broader industry impact, focusing on how startups can seamlessly blend product-centric approaches with a balance of innovation and practical development. *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz Timestamps: 0:00 - Introduction 5:15 - Exploring Fine-Tuning vs RAG in AI 10:30 - Evaluating AI Research for Investment 15:45 - Impact of AI Models on Product Development 20:00 - AI's Role in Evolving Job Markets 25:15 - The Balance Between AI Research and Product Development 30:00 - Code Generation Technologies in Software Engineering 35:00 - AI's Broader Industry Implications 40:00 - Importance of Product-Driven Approaches in AI Startups 45:00 - AI in Various Sectors: Beyond Software Engineering 50:00 - Open Source vs Proprietary AI Models 55:00 - AI's Impact on Traditional Roles and Industries 1:00:00 - Closing Thoughts Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. Follow Weights & Biases: YouTube: http://wandb.me/youtube Twitter: https://twitter.com/weights_biases LinkedIn: https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: #OCR #DeepLearning #AI #Modeling #ML | |||
| Revolutionizing AI Data Management with Jerry Liu, CEO of LlamaIndex | 04 Jan 2024 | 00:57:35 | |
In the latest episode of Gradient Dissent, we explore the innovative features and impact of LlamaIndex in AI data management with Jerry Liu, CEO of LlamaIndex. Jerry shares insights on how LlamaIndex integrates diverse data formats with advanced AI technologies, addressing challenges in data retrieval, analysis, and conversational memory. We also delve into the future of AI-driven systems and LlamaIndex's role in this rapidly evolving field. This episode is a must-watch for anyone interested in AI, data science, and the future of technology. Timestamps: 0:00 - Introduction 4:46 - Differentiating LlamaIndex in the AI framework ecosystem. 9:00 - Discussing data analysis, search, and retrieval applications. 14:17 - Exploring Retrieval Augmented Generation (RAG) and vector databases. 19:33 - Implementing and optimizing One Bot in Discord. 24:19 - Developing and evaluating datasets for AI systems. 28:00 - Community contributions and the growth of LlamaIndex. 34:34 - Discussing embedding models and the use of vector databases. 39:33 - Addressing AI model hallucinations and fine-tuning. 44:51 - Text extraction applications and agent-based systems in AI. 49:25 - Community contributions to LlamaIndex and managing refactors. 52:00 - Interactions with big tech's corpus and AI context length. 54:59 - Final thoughts on underrated aspects of ML and challenges in AI. Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. Connect with Jerry: https://twitter.com/jerryjliu0 https://www.linkedin.com/in/jerry-liu-64390071/ Follow Weights & Biases: YouTube: http://wandb.me/youtube Twitter: https://twitter.com/weights_biases LinkedIn: https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: #OCR #DeepLearning #AI #Modeling #ML | |||
| Bridging AI and Science: The Impact of Machine Learning on Material Innovation with Joe Spisak of Meta | 07 Dec 2023 | 01:14:44 | |
In the latest episode of Gradient Dissent, we hear from Joseph Spisak, Product Director, Generative AI @Meta, to explore the boundless impacts of AI and its expansive role in reshaping various sectors. We delve into the intricacies of models like GPT and Llama2, their influence on user experiences, and AI's groundbreaking contributions to fields like biology, material science, and green hydrogen production through the Open Catalyst Project. The episode also examines AI's practical business applications, from document summarization to intelligent note-taking, addressing the ethical complexities of AI deployment. We wrap up with a discussion on the significance of open-source AI development, community collaboration, and AI democratization. Tune in for valuable insights into the expansive world of AI, relevant to developers, business leaders, and tech enthusiasts. We discuss:
Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Launching the Fastest AI Inference Solution with Cerebras Systems CEO Andrew Feldman | 27 Aug 2024 | 00:53:14 | |
In this episode of Gradient Dissent, Andrew Feldman, CEO of Cerebras Systems, joins host Lukas Biewald to discuss the latest advancements in AI inference technology. They explore Cerebras Systems' groundbreaking new AI inference product, examining how their wafer-scale chips are setting new benchmarks in speed, accuracy, and cost efficiency. Andrew shares insights on the architectural innovations that make this possible and discusses the broader implications for AI workloads in production. This episode provides a comprehensive look at the cutting-edge of AI hardware and its impact on the future of machine learning. ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Connect with Andrew Feldman: https://www.linkedin.com/in/andrewdfeldman/ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 Paper Andrew referenced Paul David- Economic historian | |||
| Unlocking the Power of Language Models in Enterprise: A Deep Dive with Chris Van Pelt | 16 Nov 2023 | 00:52:25 | |
In the premiere episode of Gradient Dissent Business, we're joined by Weights & Biases co-founder Chris Van Pelt for a deep dive into the world of large language models like GPT-3.5 and GPT-4. Chris bridges his expertise as both a tech founder and AI expert, offering key strategies for startups seeking to connect with early users, and for enterprises experimenting with AI. He highlights the melding of AI and traditional web development, sharing his insights on product evolution, leadership, and the power of customer conversations—even for the most introverted founders. He shares how personal development and authentic co-founder relationships enrich business dynamics. Join us for a compelling episode brimming with actionable advice for those looking to innovate with language models, all while managing the inherent complexities. Don't miss Chris Van Pelt's invaluable take on the future of AI in this thought-provoking installment of Gradient Dissent Business. We discuss:
Thanks for listening to the Gradient Dissent Business podcast, with hosts Lavanya Shukla and Caryn Marooney, brought to you by Weights & Biases. Be sure to click the subscribe button below, to keep your finger on the pulse of this fast-moving space and hear from other amazing guests #OCR #DeepLearning #AI #Modeling #ML | |||
| Providing Greater Access to LLMs with Brandon Duderstadt, Co-Founder and CEO of Nomic AI | 27 Jul 2023 | 01:01:25 | |
On this episode, we’re joined by Brandon Duderstadt, Co-Founder and CEO of Nomic AI. Both of Nomic AI’s products, Atlas and GPT4All, aim to improve the explainability and accessibility of AI. We discuss: - (0:55) What GPT4All is and its value proposition. - (6:56) The advantages of using smaller LLMs for specific tasks. - (9:42) Brandon’s thoughts on the cost of training LLMs. - (10:50) Details about the current state of fine-tuning LLMs. - (12:20) What quantization is and what it does. - (21:16) What Atlas is and what it allows you to do. - (27:30) Training code models versus language models. - (32:19) Details around evaluating different models. - (38:34) The opportunity for smaller companies to build open-source models. - (42:00) Prompt chaining versus fine-tuning models. Resources mentioned: Brandon Duderstadt - https://www.linkedin.com/in/brandon-duderstadt-a3269112a/ Nomic AI - https://www.linkedin.com/company/nomic-ai/ Nomic AI Website - https://home.nomic.ai/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Exploring PyTorch and Open-Source Communities with Soumith Chintala, VP/Fellow of Meta, Co-Creator of PyTorch | 13 Jul 2023 | 01:08:35 | |
On this episode, we’re joined by Soumith Chintala, VP/Fellow of Meta and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch. We discuss: - The history of PyTorch’s development and TensorFlow’s impact on development decisions. - How a symbolic execution model affects the implementation speed of an ML compiler. - The strengths of different programming languages in various development stages. - The importance of customer engagement as a measure of success instead of hard metrics. - Why community-guided innovation offers an effective development roadmap. - How PyTorch’s open-source nature cultivates an efficient development ecosystem. - The role of community building in consolidating assets for more creative innovation. - How to protect community values in an open-source development environment. - The value of an intrinsic organizational motivation structure. - The ongoing debate between open-source and closed-source products, especially as it relates to AI and machine learning. Resources: - Soumith Chintala https://www.linkedin.com/in/soumith/ - Meta | LinkedIn https://www.linkedin.com/company/meta/ - Meta | Website https://about.meta.com/ - Pytorch https://pytorch.org/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Advanced AI Accelerators and Processors with Andrew Feldman of Cerebras Systems | 22 Jun 2023 | 01:00:10 | |
On this episode, we’re joined by Andrew Feldman, Founder and CEO of Cerebras Systems. Andrew and the Cerebras team are responsible for building the largest-ever computer chip and the fastest AI-specific processor in the industry. We discuss: - The advantages of using large chips for AI work. - Cerebras Systems’ process for building chips optimized for AI. - Why traditional GPUs aren’t the optimal machines for AI work. - Why efficiently distributing computing resources is a significant challenge for AI work. - How much faster Cerebras Systems’ machines are than other processors on the market. - Reasons why some ML-specific chip companies fail and what Cerebras does differently. - Unique challenges for chip makers and hardware companies. - Cooling and heat-transfer techniques for Cerebras machines. - How Cerebras approaches building chips that will fit the needs of customers for years to come. - Why the strategic vision for what data to collect for ML needs more discussion. Resources: Andrew Feldman - https://www.linkedin.com/in/andrewdfeldman/ Cerebras Systems - https://www.linkedin.com/company/cerebras-systems/ Cerebras Systems | Website - https://www.cerebras.net/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Enabling LLM-Powered Applications with Harrison Chase of LangChain | 01 Jun 2023 | 00:51:54 | |
On this episode, we’re joined by Harrison Chase, Co-Founder and CEO of LangChain. Harrison and his team at LangChain are on a mission to make the process of creating applications powered by LLMs as easy as possible. We discuss: - What LangChain is and examples of how it works. - Why LangChain has gained so much attention. - When LangChain started and what sparked its growth. - Harrison’s approach to community-building around LangChain. - Real-world use cases for LangChain. - What parts of LangChain Harrison is proud of and which parts can be improved. - Details around evaluating effectiveness in the ML space. - Harrison's opinion on fine-tuning LLMs. - The importance of detailed prompt engineering. - Predictions for the future of LLM providers. Resources: Harrison Chase - https://www.linkedin.com/in/harrison-chase-961287118/ LangChain | LinkedIn - https://www.linkedin.com/company/langchain/ LangChain | Website - https://docs.langchain.com/docs/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Deploying Autonomous Mobile Robots with Jean Marc Alkazzi at idealworks | 18 May 2023 | 00:58:05 | |
On this episode, we’re joined by Jean Marc Alkazzi, Applied AI at idealworks. Jean focuses his attention on applied AI, leveraging the use of autonomous mobile robots (AMRs) to improve efficiency within factories and more. We discuss: - Use cases for autonomous mobile robots (AMRs) and how to manage a fleet of them. - How AMRs interact with humans working in warehouses. - The challenges of building and deploying autonomous robots. - Computer vision vs. other types of localization technology for robots. - The purpose and types of simulation environments for robotic testing. - The importance of aligning a robotic fleet’s workflow with concrete business objectives. - What the update process looks like for robots. - The importance of avoiding your own biases when developing and testing AMRs. - The challenges associated with troubleshooting ML systems. Resources: Jean Marc Alkazzi - https://www.linkedin.com/in/jeanmarcjeanazzi/ idealworks |LinkedIn - https://www.linkedin.com/company/idealworks-gmbh/ idealworks | Website - https://idealworks.com/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| How EleutherAI Trains and Releases LLMs: Interview with Stella Biderman | 04 May 2023 | 00:57:16 | |
On this episode, we’re joined by Stella Biderman, Executive Director at EleutherAI and Lead Scientist - Mathematician at Booz Allen Hamilton. EleutherAI is a grassroots collective that enables open-source AI research and focuses on the development and interpretability of large language models (LLMs). We discuss: - How EleutherAI got its start and where it's headed. - The similarities and differences between various LLMs. - How to decide which model to use for your desired outcome. - The benefits and challenges of reinforcement learning from human feedback. - Details around pre-training and fine-tuning LLMs. - Which types of GPUs are best when training LLMs. - What separates EleutherAI from other companies training LLMs. - Details around mechanistic interpretability. - Why understanding what and how LLMs memorize is important. - The importance of giving researchers and the public access to LLMs. Stella Biderman - https://www.linkedin.com/in/stellabiderman/ EleutherAI - https://www.linkedin.com/company/eleutherai/ Resources: Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Scaling LLMs and Accelerating Adoption with Aidan Gomez at Cohere | 20 Apr 2023 | 00:51:31 | |
On this episode, we’re joined by Aidan Gomez, Co-Founder and CEO at Cohere. Cohere develops and releases a range of innovative AI-powered tools and solutions for a variety of NLP use cases. We discuss: - What “attention” means in the context of ML. - Aidan’s role in the “Attention Is All You Need” paper. - What state-space models (SSMs) are, and how they could be an alternative to transformers. - What it means for an ML architecture to saturate compute. - Details around data constraints for when LLMs scale. - Challenges of measuring LLM performance. - How Cohere is positioned within the LLM development space. - Insights around scaling down an LLM into a more domain-specific one. - Concerns around synthetic content and AI changing public discourse. - The importance of raising money at healthy milestones for AI development. Aidan Gomez - https://www.linkedin.com/in/aidangomez/ Cohere - https://www.linkedin.com/company/cohere-ai/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. Resources: #OCR #DeepLearning #AI #Modeling #ML | |||
| Neural Network Pruning and Training with Jonathan Frankle at MosaicML | 04 Apr 2023 | 01:02:00 | |
Jonathan Frankle, Chief Scientist at MosaicML and Assistant Professor of Computer Science at Harvard University, joins us on this episode. With comprehensive infrastructure and software tools, MosaicML aims to help businesses train complex machine-learning models using their own proprietary data. We discuss: - Details of Jonathan’s Ph.D. dissertation which explores his “Lottery Ticket Hypothesis.” - The role of neural network pruning and how it impacts the performance of ML models. - Why transformers will be the go-to way to train NLP models for the foreseeable future. - Why the process of speeding up neural net learning is both scientific and artisanal. - What MosaicML does, and how it approaches working with clients. - The challenges for developing AGI. - Details around ML training policy and ethics. - Why data brings the magic to customized ML models. - The many use cases for companies looking to build customized AI models. Jonathan Frankle - https://www.linkedin.com/in/jfrankle/ Resources: - The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML | |||
| Shreya Shankar — Operationalizing Machine Learning | 03 Mar 2023 | 00:54:38 | |
About This Episode Shreya Shankar is a computer scientist, PhD student in databases at UC Berkeley, and co-author of "Operationalizing Machine Learning: An Interview Study", an ethnographic interview study with 18 machine learning engineers across a variety of industries on their experience deploying and maintaining ML pipelines in production. Shreya explains the high-level findings of "Operationalizing Machine Learning"; variables that indicate a successful deployment (velocity, validation, and versioning), common pain points, and a grouping of the MLOps tool stack into four layers. Shreya and Lukas also discuss examples of data challenges in production, Jupyter Notebooks, and reproducibility. Show notes (transcript and links): http://wandb.me/gd-shreya --- 💬 *Host:* Lukas Biewald --- *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 | |||
| Reinventing AI Agents with Imbue CEO Kanjun Qiu | 08 Aug 2024 | 00:48:37 | |
In this episode of Gradient Dissent, Kanjun Qiu, CEO and Co-founder of Imbue, joins host Lukas Biewald to discuss how AI agents are transforming code generation and software development. Discover the potential impact and challenges of creating autonomous AI systems that can write and verify code and and learn about the practical research involved. ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz Connect with Kanjun Qiu: https://www.linkedin.com/in/kanjun/ General Intelligent Podcast: Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3 | |||
| Sarah Catanzaro — Remembering the Lessons of the Last AI Renaissance | 02 Feb 2023 | 01:16:24 | |
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 | |||
| Cristóbal Valenzuela — The Next Generation of Content Creation and AI | 19 Jan 2023 | 00:40:26 | |
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 | |||
| Jeremy Howard — The Simple but Profound Insight Behind Diffusion | 05 Jan 2023 | 01:12:57 | |
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 --- 📝 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 | |||
| Jerome Pesenti — Large Language Models, PyTorch, and Meta | 22 Dec 2022 | 00:52:35 | |
Jerome Pesenti is the former VP of AI at Meta, a tech conglomerate that includes Facebook, WhatsApp, and Instagram, and one of the most exciting places where AI research is happening today. Jerome shares his thoughts on Transformers-based large language models, and why he's excited by the progress but skeptical of the term "AGI". Then, he discusses some of the practical applications of ML at Meta (recommender systems and moderation!) and dives into the story behind Meta's development of PyTorch. Jerome and Lukas also chat about Jerome's time at IBM Watson and in drug discovery. Show notes (transcript and links): http://wandb.me/gd-jerome-pesenti --- ⏳ Timestamps: 0:00 Intro 0:28 Jerome's thought on large language models 12:53 AI applications and challenges at Meta 18:41 The story behind developing PyTorch 26:40 Jerome's experience at IBM Watson 28:53 Drug discovery, AI, and changing the game 36:10 The potential of education and AI 40:10 Meta and AR/VR interfaces 43:43 Why NVIDIA is such a powerhouse 47:08 Jerome's advice to people starting their careers 48:50 Going back to coding, the challenges of scaling 52:11 Outro --- Connect with Jerome: 📍 Jerome on Twitter: https://twitter.com/an_open_mind 📍 Jerome on LinkedIn: https://www.linkedin.com/in/jpesenti/ --- 💬 Host: Lukas Biewald 📹 Producers: Riley Fields, 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 | |||
| D. Sculley — Technical Debt, Trade-offs, and Kaggle | 01 Dec 2022 | 01:00:26 | |
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 --- ⏳ 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 --- Connect with D. and Kaggle: 📍 D. on LinkedIn: https://www.linkedin.com/in/d-sculley-90467310/ 📍 Kaggle on Twitter: https://twitter.com/kaggle --- Links: 📍 "Machine Learning: The High Interest Credit Card of Technical Debt" (Sculley et al. 2014): https://research.google/pubs/pub43146/ --- 💬 Host: Lukas Biewald 📹 Producers: Riley Fields, Angelica Pan, Anish Shah, 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 | |||
| Emad Mostaque — Stable Diffusion, Stability AI, and What’s Next | 15 Nov 2022 | 01:10:29 | |
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 | |||
| Jehan Wickramasuriya — AI in High-Stress Scenarios | 06 Oct 2022 | 01:00:02 | |
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 - ⏳ 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 | |||
| Will Falcon — Making Lightning the Apple of ML | 15 Sep 2022 | 00:45:21 | |
Will Falcon is the CEO and co-founder of Lightning AI, a platform that enables users to quickly build and publish ML models. In this episode, Will explains how Lightning addresses the challenges of a fragmented AI ecosystem and reveals which framework PyTorch Lightning was originally built upon (hint: not PyTorch!) He also shares lessons he took from his experience serving in the military and offers a recommendation to veterans who want to work in tech. Show notes (transcript and links): http://wandb.me/gd-will-falcon --- ⏳ Timestamps: 00:00 Intro 01:00 From SEAL training to FAIR 04:17 Stress-testing Lightning 07:55 Choosing PyTorch over TensorFlow and other frameworks 13:16 Components of the Lightning platform 17:01 Launching Lightning from Facebook 19:09 Similarities between leadership and research 22:08 Lessons from the military 26:56 Scaling PyTorch Lightning to Lightning AI 33:21 Hiring the right people 35:21 The future of Lightning 39:53 Reducing algorithm complexity in self-supervised learning 42:19 A fragmented ML landscape 44:35 Outro --- Connect with Lightning 📍 Website: https://lightning.ai 📍 Twitter: https://twitter.com/LightningAI 📍 LinkedIn: https://www.linkedin.com/company/pytorch-lightning/ 📍 Careers: https://boards.greenhouse.io/lightningai --- 💬 Host: Lukas Biewald 📹 Producers: Riley Fields, Anish Shah, 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 | |||
| Aaron Colak — ML and NLP in Experience Management | 26 Aug 2022 | 00:50:00 | |
Aaron Colak is the Leader of Core Machine Learning at Qualtrics, an experiment management company that takes large language models and applies them to real-world, B2B use cases. In this episode, Aaron describes mixing classical linguistic analysis with deep learning models and how Qualtrics organized their machine learning organizations and model to leverage the best of these techniques. He also explains how advances in NLP have invited new opportunities in low-resource languages. Show notes (transcript and links): http://wandb.me/gd-aaron-colak --- ⏳ Timestamps: 00:00 Intro 00:57 Evolving from surveys to experience management 04:56 Detecting sentiment with ML 10:57 Working with large language models and rule-based systems 14:50 Zero-shot learning, NLP, and low-resource languages 20:11 Letting customers control data 25:13 Deep learning and tabular data 28:40 Hyperscalers and performance monitoring 34:54 Combining deep learning with linguistics 40:03 A sense of accomplishment 42:52 Causality and observational data in healthcare 45:09 Challenges of interdisciplinary collaboration 49:27 Outro --- Connect with Aaron and Qualtrics 📍 Aaron on LinkedIn: https://www.linkedin.com/in/aaron-r-colak-3522308/ 📍 Qualtrics on Twitter: https://twitter.com/qualtrics/ 📍 Careers at Qualtrics: https://www.qualtrics.com/careers/ --- 💬 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 | |||
| Jordan Fisher — Skipping the Line with Autonomous Checkout | 04 Aug 2022 | 00:57:58 | |
Jordan Fisher is the CEO and co-founder of Standard AI, an autonomous checkout company that’s pushing the boundaries of computer vision. In this episode, Jordan discusses “the Wild West” of the MLOps stack and tells Lukas why Rust beats Python. He also explains why AutoML shouldn't be overlooked and uses a bag of chips to help explain the Manifold Hypothesis. Show notes (transcript and links): http://wandb.me/gd-jordan-fisher --- ⏳ Timestamps: 00:00 Intro 00:40 The origins of Standard AI 08:30 Getting Standard into stores 18:00 Supervised learning, the advent of synthetic data, and the manifold hypothesis 24:23 What's important in a MLOps stack 27:32 The merits of AutoML 30:00 Deep learning frameworks 33:02 Python versus Rust 39:32 Raw camera data versus video 42:47 The future of autonomous checkout 48:02 Sharing the StandardSim data set 52:30 Picking the right tools 54:30 Overcoming dynamic data set challenges 57:35 Outro --- Connect with Jordan and Standard AI 📍 Jordan on LinkedIn: https://www.linkedin.com/in/jordan-fisher-81145025/ 📍 Standard AI on Twitter: https://twitter.com/StandardAi 📍 Careers at Standard AI: https://careers.standard.ai/ --- 💬 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 | |||
| From startup to $1.2B with Lambda’s Stephen Balaban | 25 Jul 2024 | 00:49:56 | |
In this episode of Gradient Dissent, Stephen Balaban, CEO of Lambda Labs, joins host Lukas Biewald to discuss the journey of scaling Lambda Labs to an impressive $400M in revenue. They explore the pivotal moments that shaped the company, the future of GPU technology, and the impact of AI data centers on the energy grid. Discover the challenges and triumphs of running a successful hardware and cloud business in the AI industry. Tune in now to explore the evolving landscape of AI hardware and cloud services. ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz Connect with Stephen Balaban: https://www.linkedin.com/in/sbalaban/ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb | |||
| Drago Anguelov — Robustness, Safety, and Scalability at Waymo | 14 Jul 2022 | 01:09:01 | |
Drago Anguelov is a Distinguished Scientist and Head of Research at Waymo, an autonomous driving technology company and subsidiary of Alphabet Inc. We begin by discussing Drago's work on the original Inception architecture, winner of the 2014 ImageNet challenge and introduction of the inception module. Then, we explore milestones and current trends in autonomous driving, from Waymo's release of the Open Dataset to the trade-offs between modular and end-to-end systems. Drago also shares his thoughts on finding rare examples, and the challenges of creating scalable and robust systems. Show notes (transcript and links): http://wandb.me/gd-drago-anguelov --- ⏳ Timestamps: 0:00 Intro 0:45 The story behind the Inception architecture 13:51 Trends and milestones in autonomous vehicles 23:52 The challenges of scalability and simulation 30:19 Why LiDar and mapping are useful 35:31 Waymo Via and autonomous trucking 37:31 Robustness and unsupervised domain adaptation 40:44 Why Waymo released the Waymo Open Dataset 49:02 The domain gap between simulation and the real world 56:40 Finding rare examples 1:04:34 The challenges of production requirements 1:08:36 Outro --- Connect with Drago & Waymo 📍 Drago on LinkedIn: https://www.linkedin.com/in/dragomiranguelov/ 📍 Waymo on Twitter: https://twitter.com/waymo/ 📍 Careers at Waymo: https://waymo.com/careers/ --- Links: 📍 Inception v1: https://arxiv.org/abs/1409.4842 📍 "SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation", Qiangeng Xu et al. (2021), https://arxiv.org/abs/2108.06709 📍 "GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting", Zhao Chen et al. (2022), https://arxiv.org/abs/2201.05938 --- 💬 Host: Lukas Biewald 📹 Producers: 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 | |||
| James Cham — Investing in the Intersection of Business and Technology | 07 Jul 2022 | 01:06:11 | |
James Cham is a co-founder and partner at Bloomberg Beta, an early-stage venture firm that invests in machine learning and the future of work, the intersection between business and technology. James explains how his approach to investing in AI has developed over the last decade, which signals of success he looks for in the ever-adapting world of venture startups (tip: look for the "gradient of admiration"), and why it's so important to demystify ML for executives and decision-makers. Lukas and James also discuss how new technologies create new business models, and what the ethical considerations of a world where machine learning is accepted to be possibly fallible would be like. Show notes (transcript and links): http://wandb.me/gd-james-cham --- ⏳ Timestamps: 0:00 Intro 0:46 How investment in AI has changed and developed 7:08 Creating the first MI landscape infographics 10:30 The impact of ML on organizations and management 17:40 Demystifying ML for executives 21:40 Why signals of successful startups change over time 27:07 ML and the emergence of new business models 37:58 New technology vs new consumer goods 39:50 What James considers when investing 44:19 Ethical considerations of accepting that ML models are fallible 50:30 Reflecting on past investment decisions 52:56 Thoughts on consciousness and Theseus' paradox 59:08 Why it's important to increase general ML literacy 1:03:09 Outro 1:03:30 Bonus: How James' faith informs his thoughts on ML --- Connect with James: 📍 Twitter: https://twitter.com/jamescham 📍 Bloomberg Beta: https://github.com/Bloomberg-Beta/Manual --- Links: 📍 "Street-Level Algorithms: A Theory at the Gaps Between Policy and Decisions" by Ali Alkhatib and Michael Bernstein (2019): https://doi.org/10.1145/3290605.3300760 --- 💬 Host: Lukas Biewald 📹 Producers: 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 | |||
| Boris Dayma — The Story Behind DALL·E mini, the Viral Phenomenon | 17 Jun 2022 | 00:35:59 | |
Check out this report by Boris about DALL-E mini: https://twitter.com/weirddalle Connect with Boris: 📍 Twitter: https://twitter.com/borisdayma --- 💬 Host: Lukas Biewald 📹 Producers: Cayla Sharp, Angelica Pan, Sanyam Bhutani, 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 | |||
| Tristan Handy — The Work Behind the Data Work | 09 Jun 2022 | 01:00:48 | |
Tristan Handy is CEO and founder of dbt Labs. dbt (data build tool) simplifies the data transformation workflow and helps organizations make better decisions. Lukas and Tristan dive into the history of the modern data stack and the subsequent challenges that dbt was created to address; communities of identity and product-led growth; and thoughts on why SQL has survived and thrived for so long. Tristan also shares his hopes for the future of BI tools and the data stack. Show notes (transcript and links): http://wandb.me/gd-tristan-handy --- ⏳ Timestamps: 0:00 Intro 0:40 How dbt makes data transformation easier 4:52 dbt and avoiding bad data habits 14:23 Agreeing on organizational ground truths 19:04 Staying current while running a company 22:15 The origin story of dbt 26:08 Why dbt is conceptually simple but hard to execute 34:47 The dbt community and the bottom-up mindset 41:50 The future of data and operations 47:41 dbt and machine learning 49:17 Why SQL is so ubiquitous 55:20 Bridging the gap between the ML and data worlds 1:00:22 Outro --- Connect with Tristan: 📍 Twitter: https://twitter.com/jthandy 📍 The Analytics Engineering Roundup: https://roundup.getdbt.com/ --- 💬 Host: Lukas Biewald 📹 Producers: Cayla Sharp, Angelica Pan, Sanyam Bhutani, 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 | |||