Practical AI

Practical AI
Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
13: Answering recent AI questions from Quora
Sep 18 • 48 min
An amazing panel of AI innovators joined us at the O’Reilly AI conference to answer the most pressing AI questions from Quora. We also discussed trends in the industry and some exciting new advances in FPGA hardware.
12: AI in healthcare, synthesizing dance moves, hardware acceleration
Sep 3 • 20 min
Chris and Daniel discuss new advances in AI research (including a creepy dancing video), how AI is creating opportunity for new chip startups, and uses of deep learning in healthcare. They also share some great learning resources, including one of Chris’s…
11: Robot Perception and Mask R-CNN
Aug 27 • 46 min
Chris DeBellis, a lead AI data scientist at Honeywell, helps us understand what Mask R-CNN is and why it’s useful for robot perception. We also explore how this method compares with other convolutional neural network approaches and how you can get started…
10: Open source tools, AI for Dota, and enterprise ML adoption
Aug 21 • 31 min
This week, Daniel and Chris talk about playing Dota at OpenAI, O’Reilly’s machine learning survey, AI-oriented open source (Julia, AutoKeras, Netron, PyTorch), robotics, and even the impact AI strategy has on corporate and national interests. Don’t miss…
9: Behavioral economics and AI-driven decision making
Aug 13 • 50 min
Mike Bugembe teaches us how to build a culture of data-driven decision making within a company, leverage behavioral economics, and identify high value use cases for AI.
8: Eye tracking, Henry Kissinger on AI, Vim
Aug 6 • 28 min
Chris and Daniel help us wade through the week’s AI news, including open ML challenges from Intel and National Geographic, Henry Kissinger’s views on AI, and a model that can detect personality based on eye movements. They also point out some useful…
7: Understanding the landscape of AI techniques
Jul 30 • 44 min
Jared Lander, the organizer of NYHackR and general data science guru, joined us to talk about the landscape of AI techniques, how deep learning fits into that landscape, and why you might consider using R for ML/AI.
6: Government use of facial recognition and AI at Google
Jul 23 • 18 min
In this episode, Chris and Daniel discuss the latest news, including an article about Google’s AI principles, and they highlight some useful resources to help you level up.
5: Detecting planets with deep learning
Jul 16 • 45 min
Andrew Vanderburg of UT Austin and Christ Shallue of Google Brain join us to talk about their deep learning collaboration, which involved searching through a crazy amount of space imagery to find new planets.
4: Data management, regulation, the future of AI
Jul 9 • 48 min
Matthew Carroll and Andrew Burt of Immuta talked with Daniel and Chris about data management for AI, how data regulation will impact AI, and schooled them on the finer points of the General Data Protection Regulation (GDPR).
3: Helping African farmers with TensorFlow
Jul 2 • 42 min
Amanda Ramcharan, Latifa Mrisho, and Peter McCloskey joined Daniel and Chris to talk about how Penn State University are collaborating to help African farmers increase their yields via a TensorFlow powered mobile app.
2: Putting AI in a box at MachineBox
Jul 2 • 45 min
Mat Ryer and David Hernandez joined Daniel and Chris to talk about MachineBox, building a company around AI, and democratizing AI.
1: Meet Practical AI hosts Daniel Whitenack and Chris Benson
Jul 2 • 35 min
In this inaugural episode of Practical AI — Adam Stacoviak and Jerod Santo sit down with Daniel Whitenack and Chris Benson to discuss their experiences in Artificial Intelligence, Machine Learning, and Data Science and what they hope to accomplish as…