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Machine Learning

Machine Learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
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Practical AI Practical AI #89

AI for Good: clean water access in Africa

Chandler McCann tells Daniel and Chris about how DataRobot engaged in a project to develop sustainable water solutions with the Global Water Challenge (GWC). They analyzed over 500,000 data points to predict future water point breaks. This enabled African governments to make data-driven decisions related to budgeting, preventative maintenance, and policy in order to promote and protect people’s access to safe water for drinking and washing. From this effort sprang DataRobot’s larger AI for Good initiative.

Practical AI Practical AI #87

Reinforcement learning for chip design

Daniel and Chris have a fascinating discussion with Anna Goldie and Azalia Mirhoseini from Google Brain about the use of reinforcement learning for chip floor planning - or placement - in which many new designs are generated, and then evaluated, to find an optimal component layout. Anna and Azalia also describe the use of graph convolutional neural networks in their approach.

Practical AI Practical AI #86

Exploring the COVID-19 Open Research Dataset

In the midst of the COVID-19 pandemic, Daniel and Chris have a timely conversation with Lucy Lu Wang of the Allen Institute for Artificial Intelligence about COVID-19 Open Research Dataset (CORD-19). She relates how CORD-19 was created and organized, and how researchers around the world are currently using the data to answer important COVID-19 questions that will help the world through this ongoing crisis.

Practical AI Practical AI #85

Achieving provably beneficial, human-compatible AI

AI legend Stuart Russell, the Berkeley professor who leads the Center for Human-Compatible AI, joins Chris to share his insights into the future of artificial intelligence. Stuart is the author of Human Compatible, and the upcoming 4th edition of his perennial classic Artificial Intelligence: A Modern Approach, which is widely regarded as the standard text on AI. After exposing the shortcomings inherent in deep learning, Stuart goes on to propose a new practitioner approach to creating AI that avoids harmful unintended consequences, and offers a path forward towards a future in which humans can safely rely of provably beneficial AI.

Practical AI Practical AI #83

Mapping the intersection of AI and GIS

Daniel Wilson and Rob Fletcher of ESRI hang with Chris and Daniel to chat about how AI powered modern geographic information systems (GIS) and location intelligence. They illuminate the various models used for GIS, spatial analysis, remote sensing, real-time visualization, and 3D analytics. You don’t want to miss the part about their work for the DoD’s Joint AI Center in humanitarian assistance / disaster relief.

Practical AI Practical AI #82

Speech recognition to say it just right

Catherine Breslin of Cobalt joins Daniel and Chris to do a deep dive on speech recognition. She also discusses how the technology is integrated into virtual assistants (like Alexa) and is used in other non-assistant contexts (like transcription and captioning). Along the way, she teaches us how to assemble a lexicon, acoustic model, and language model to bring speech recognition to life.

The Changelog The Changelog #380

Productionising real-world ML data pipelines

Yetunde Dada from QuantumBlack joins Jerod for a deep dive on Kedro, a workflow tool that helps structure reproducible, scaleable, deployable, robust, and versioned data pipelines. They discuss what Kedro’s all about and how it’s “changing the landscape of data pipelines in Python”, the ins/outs of open sourcing Kedro, and how they found early success by sweating the details. Finally, Jerod asks Yetunde about her passion project: a virtual reality film which debuted at the Sundance Film Festival in January.

Practical AI Practical AI #75

Insights from the AI Index 2019 Annual Report

Daniel and Chris do a deep dive into The AI Index 2019 Annual Report, which provides unbiased rigorously-vetted data that one can use “to develop intuitions about the complex field of AI”. Analyzing everything from R&D and technical advancements to education, the economy, and societal considerations, Chris and Daniel lay out this comprehensive report’s key insights about artificial intelligence.

Practical AI Practical AI #74

Testing ML systems

Production ML systems include more than just the model. In these complicated systems, how do you ensure quality over time, especially when you are constantly updating your infrastructure, data and models? Tania Allard joins us to discuss the ins and outs of testing ML systems. Among other things, she presents a simple formula that helps you score your progress towards a robust system and identify problem areas.

Practical AI Practical AI #72

How the U.S. military thinks about AI

Chris and Daniel talk with Greg Allen, Chief of Strategy and Communications at the U.S. Department of Defense (DoD) Joint Artificial Intelligence Center (JAIC). The mission of the JAIC is “to seize upon the transformative potential of artificial intelligence technology for the benefit of America’s national security… The JAIC is the official focal point of the DoD AI Strategy.” So if you want to understand how the U.S. military thinks about artificial intelligence, then this is the episode for you!

Practical AI Practical AI #66

Build custom ML tools with Streamlit

Streamlit recently burst onto the scene with their intuitive, open source solution for building custom ML/AI tools. It allows data scientists and ML engineers to rapidly build internal or external UIs without spending time on frontend development. In this episode, Adrien Treuille joins us to discuss ML/AI app development in general and Streamlit. We talk about the practicalities of working with Streamlit along with its seemingly instant adoption by AI2, Stripe, Stitch Fix, Uber, and Twitter.

Practical AI Practical AI #59

Flying high with AI drone racing at AlphaPilot

Chris and Daniel talk with Keith Lynn, AlphaPilot Program Manager at Lockheed Martin. AlphaPilot is an open innovation challenge, developing artificial intelligence for high-speed racing drones, created through a partnership between Lockheed Martin and The Drone Racing League (DRL).

AlphaPilot challenged university teams from around the world to design AI capable of flying a drone without any human intervention or navigational pre-programming. Autonomous drones will race head-to-head through complex, three-dimensional tracks in DRL’s new Artificial Intelligence Robotic Racing (AIRR) Circuit. The winning team could win up to $2 million in prizes.

Keith shares the incredible story of how AlphaPilot got started, just prior to its debut race in Orlando, which will be broadcast on NBC Sports.

Practical AI Practical AI #50

Celebrating episode 50 and the neural net!

Woo hoo! As we celebrate reaching episode 50, we come full circle to discuss the basics of neural networks. If you are just jumping into AI, then this is a great primer discussion with which to take that leap.

Our commitment to making artificial intelligence practical, productive, and accessible to everyone has never been stronger, so we invite you to join us for the next 50 episodes!

Practical AI Practical AI #49

Exposing the deception of DeepFakes

This week we bend reality to expose the deceptions of deepfake videos. We talk about what they are, why they are so dangerous, and what you can do to detect and resist their insidious influence. In a political environment rife with distrust, disinformation, and conspiracy theories, deepfakes are being weaponized and proliferated as the latest form of state-sponsored information warfare. Join us for an episode scarier than your favorite horror movie, because this AI bogeyman is real!

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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