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/

Jaksot(134)

Matthew Davis — Bringing Genetic Insights to Everyone

Matthew Davis — Bringing Genetic Insights to Everyone

Matthew explains how combining machine learning and computational biology can provide mainstream medicine with better diagnostics and insights. --- Matthew Davis is Head of AI at Invitae, the larges...

17 Kesä 202143min

Clément Delangue — The Power of the Open Source Community

Clément Delangue — The Power of the Open Source Community

Clem explains the virtuous cycles behind the creation and success of Hugging Face, and shares his thoughts on where NLP is heading. --- Clément Delangue is co-founder and CEO of Hugging Face, the AI...

10 Kesä 202146min

Wojciech Zaremba — What Could Make AI Conscious?

Wojciech Zaremba — What Could Make AI Conscious?

Wojciech joins us to talk the principles behind OpenAI, the Fermi Paradox, and the future stages of developments in AGI. --- Wojciech Zaremba is a co-founder of OpenAI, a research company dedicated ...

3 Kesä 202144min

Phil Brown — How IPUs are Advancing Machine Intelligence

Phil Brown — How IPUs are Advancing Machine Intelligence

Phil shares some of the approaches, like sparsity and low precision, behind the breakthrough performance of Graphcore's Intelligence Processing Units (IPUs). --- Phil Brown leads the Applications te...

27 Touko 202157min

Alyssa Simpson Rochwerger — Responsible ML in the Real World

Alyssa Simpson Rochwerger — Responsible ML in the Real World

From working on COVID-19 vaccine rollout to writing a book on responsible ML, Alyssa shares her thoughts on meaningful projects and the importance of teamwork. --- Alyssa Simpson Rochwerger is as a ...

20 Touko 202145min

Sean Taylor — Business Decision Problems

Sean Taylor — Business Decision Problems

Sean joins us to chat about ML models and tools at Lyft Rideshare Labs, Python vs R, time series forecasting with Prophet, and election forecasting. --- Sean Taylor is a Data Scientist at (and forme...

13 Touko 202145min

Polly Fordyce — Microfluidic Platforms and Machine Learning

Polly Fordyce — Microfluidic Platforms and Machine Learning

Polly explains how microfluidics allow bioengineering researchers to create high throughput data, and shares her experiences with biology and machine learning. --- Polly Fordyce is an Assistant Pro...

29 Huhti 202145min

Adrien Gaidon — Advancing ML Research in Autonomous Vehicles

Adrien Gaidon — Advancing ML Research in Autonomous Vehicles

Adrien Gaidon shares his approach to building teams and taking state-of-the-art research from conception to production at Toyota Research Institute. --- Adrien Gaidon is the Head of Machine Learning...

22 Huhti 202148min

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