In this new and updates show, Daniel and Chris discuss, among other things, efforts to use AI in art and efforts to make AI interfaces look human. They also discuss some learning resources related to neural nets, AI fairness, and reinforcement learning.
Lindsey Zuloaga joins us to discuss bias in hiring, bias in AI, and how we can fight bias in hiring with AI. Lindsey tells us about her experiences fighting bias at HireVue, where she is director of data science, and she gives some practical advice to AI practitioners about fairness in models and data.
Chris and Daniel are back together in another news/updates show. They discuss PyTorch v1.0, some disturbing uses of AI for tracking social credit, and learning resources to get you started with machine learning.
NVIDIA Chief Scientist Bill Dally joins Daniel Whitenack and Chris Benson for an in-depth conversation about ‘everything AI’ at NVIDIA. As the leader of NVIDIA Research, Bill schools us on GPUs, and then goes on to address everything from AI-enabled robots and self-driving vehicles, to new AI research innovations in algorithm development and model architectures. This episode is so packed with information, you may want to listen to it multiple times.
We met up with Wojciech Zaremba at the O’Reilly AI conference in SF. He took some time to talk to us about some of his recent research related to reinforcement learning and robots. We also discussed AI safety and the hype around OpenAI.
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.
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 favorite online courses.
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 with Mask R-CNN.
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 it!
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.
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 resources to learn more about pandas, the vim editor, and AI algorithms.
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.
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.
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.
In this special episode of The Changelog we’re sharing a full-length episode of our newly launched podcast called Practical AI — covering AI, Machine Learning, and Data Science. In this episode Mat Ryer and David Hernandez joined Daniel and Chris to talk about MachineBox, building a company around AI, and democratizing AI.
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).
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.
Mat Ryer and David Hernandez joined Daniel and Chris to talk about MachineBox, building a company around AI, and democratizing AI.
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 hosts of this podcast.
In this super informative show with Daniel Whitenack we discuss Go and data science. We talk about what data science really is, tools and projects for getting started with data science using Go, and what to expect from Daniel’s talk at GopherCon this year titled “Go for Data Science”.
