The Engineering Behind the World’s Most Advanced Video AI

The Engineering Behind the World’s Most Advanced Video AI

Is video AI a viable path toward AGI?

Runway ML founder Cristóbal Valenzuela joins Lukas Biewald just after Gen 4.5 reached the #1 position on the Video Arena Leaderboard, according to community voting on Artificial Analysis.

Lukas examines how a focused research team at Runway outpaced much larger organizations like Google and Meta in one of the most compute-intensive areas of machine learning.


Cristóbal breaks down the architecture behind Gen 4.5 and explains the role of “taste” in model development. He details the engineering improvements in motion and camera control that solve long-standing issues like the restrictive “tripod look,” and shares why video models are starting to function as simulation engines with applications beyond media generation.


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Rachael Tatman — Conversational AI and Linguistics

Rachael Tatman — Conversational AI and Linguistics

🏅 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/

7 Apr 202036min

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

👨🏻‍💻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/

21 Mars 202044min

Brandon Rohrer — Machine Learning in Production for Robots

Brandon Rohrer — Machine Learning in Production for Robots

👨🏻‍💻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

11 Mars 202034min

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