Practical AI

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Making artificial intelligence practical, productive, and accessible to everyone.

Practical AI Practical AI #40

Deep Reinforcement Learning

While attending the NVIDIA GPU Technology Conference in Silicon Valley, Chris met up with Adam Stooke, a speaker and PhD student at UC Berkeley who is doing groundbreaking work in large-scale deep reinforcement learning and robotics. Adam took Chris on a tour of deep reinforcement learning - explaining what it is, how it works, and why it’s one of the hottest technologies in artificial intelligence!

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Practical AI Practical AI #47

GANs, RL, and transfer learning oh my!

Daniel and Chris explore three potentially confusing topics - generative adversarial networks (GANs), deep reinforcement learning (DRL), and transfer learning. Are these types of neural network architectures? Are they something different? How are they used? Well, If you have ever wondered how AI can be creative, wished you understood how robots get their smarts, or were impressed at how some AI practitioners conquer big challenges quickly, then this is your episode!

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Practical AI Practical AI #51

AI code that facilitates good science

We’re talking with Joel Grus, author of Data Science from Scratch, 2nd Edition, senior research engineer at the Allen Institute for AI (AI2), and maintainer of AllenNLP. We discussed Joel’s book, which has become a personal favorite of the hosts, and why he decided to approach data science and AI “from scratch.” Joel also gives us a glimpse into AI2, an introduction to AllenNLP, and some tips for writing good research code. This episode is packed full of reproducible AI goodness!

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Practical AI Practical AI #36

Growing up to become a world-class AI expert

While at the NVIDIA GPU Technology Conference 2019 in Silicon Valley, Chris enjoyed an inspiring conversation with Anima Anandkumar. Clearly a role model - not only for women - but for anyone in the world of AI, Anima relayed how her lifelong passion for mathematics and engineering started when she was only 3 years old in India, and ultimately led to her pioneering deep learning research at Amazon Web Services, CalTech, and NVIDIA.

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