Years ago, Armando Mastracci got a recumbent bike that could provide him with heart rate, cadence and power data. As Mastracci trained on the bike indoors throughout one winter, the graduate of engineering science at the University of Toronto recorded his training data on spreadsheets. He also started performing his own experiments. What happened if he maintained a certain cadence? Or power? He started noticing patterns in the data, patterns that led him to algorithms, which in turn led to the launch of a training platform called Xert that Mastracci continues to build and expand today.

From the beginning, Xert had AI-like features. It could look at a rider’s power data and make predictions. But, until this past December, the company didn’t really lean into the term artificial intelligence. Then, eight months ago, Xert began rolling about a beta version of a feature called Forecast AI. What was it about this feature that made it AI? Why wasn’t the previous predictive number crunching of the software AI? Mastracci not only discusses these questions, but explores larger ideas that affect cyclists looking to improve their performance, as well as the AI field as a whole. Can an AI model handle all the data that cyclists can now collect, such as heart-rate variability to blood-sugar levels? Some AI models have shown certain biases. Are there biases in training platforms? With AI training systems getting better and better, should traditional coaches be worried? Take a listen to this fascinating interview with Mastracci and get a glimpse of the future of training.

Also in this episode, an update from Paris. Canadian Cycling Magazine writer Tara Nolan is at the Summer Games. She checks in with behind-the-scenes news from the time trial and mountain bike races. Make sure to read Nolan’s stories about the races against the clock and the Holmgren siblings, who competed in their first Olympics in cross country mountain biking. How did the Holmgrens get to Paris? Well, that’s a good story, too. You can listen to it in a previous episode.

AI and training insights from a Toronto cyclist working to make riders stronger

Powered by Wave AI