AI-Powered Water Systems with Martha White | Approximately Correct Podcast

In the latest episode of the Approximately Correct podcast, Amii Fellow and Canada CIFAR AI Chair Martha White discusses the real-world application of reinforcement learning and her work in using it to make water treatment more effective.

White co-founded RL Core Technologies along with Adam White and Alden Christianson. The startup explores how reinforcement learning is being used to increase efficiency at a water treatment plant in Drayton Valley.

“In any industry, there are always innovators who always want to see the things they can do,” she told hosts Alona Fyshe and Scott Lilwall,

White also discusses her experience of navigating the world of AI startups and reflects on some of the lessons she’s learned for anyone wanting to use artificial intelligence in their business.

Tune into the full episode to hear more and subscribe to Approximately Correct on Spotify, Apple Podcasts or your favourite podcast platform.

Approximately Correct: An AI Podcast from Amii is hosted by Alona Fyshe and Scott Lilwall. It is produced by Lynda Vang, with video production by Chris Onciul.

Taylor stresses that it isn’t just a question of providing human oversight — a true HITL approach is collaborative and iterative, making best use of what people and AI are strongest at. It also means that machine learning scientists need to work closely with subject matter experts when designing AI systems from the start of any ML process. He poins to his current work using ML to improve power grid use as an example.

Taylor also touches on the importance of explainable AI (XAI) in helping people build trust in AI-aided decisions.

Tune into the full episode to hear more and subscribe to Approximately Correct on Spotify, Apple Podcasts or your favourite podcast platform.

Approximately Correct: An AI Podcast from Amii is hosted by Alona Fyshe and Scott Lilwall. It is produced by Lynda Vang, with video production by Chris Onciul.

You can hear episode three of Approximately Correct on Spotify, Apple Podcasts, Google Podcasts and other podcasting services.