François Modave, PhD, is Professor of Artificial Intelligence, Digital Health at Wake Forest University (North Carolina). He is also a triathlete with over 30 years in the sport. In this episode, François discusses key concepts of artificial intelligence and how it could be applied (and to what level of success) in a triathlon context.
HIGHLIGHTS AND KEY TOPICS:
- What is artificial intelligence?
- What are the different types of systems that fall under the broader umbrella of AI?
- How do you train AI systems?
- What are the strengths and weaknesses of AI?
- Does François use AI-based tools in his triathlon training?
- How would François build an AI model for triathlon performance if he had unlimited resources?
- The importance of good data collection
- What is the potential of AI to support improved sports science?
- What is the potential of AI in a triathlon context to support improved training planning, strategic and long-term planning, race tactics and strategy, injury prevention, nutrition and hydration, mental strategies and psychology, and equipment choices and optimisation?
- What are the potential risks of using AI in a triathlon context?
- Are there ethical concerns or biases associated with AI?
- How AI could change the way humans work and the role of humans in professional settings
DETAILED EPISODE SHOWNOTES:
- We have detailed shownotes for all of our episodes. The shownotes are basically the podcast episode in written form, that you can read in 5-10 minutes. They are not transcriptions, but they are also not just surface-level overviews. They provide detailed insights and timestamps for each episode, and are great especially for later review, after you've already listened to an episode. Naturally, as great as they are, they do not cover absolutely everything in as great detail as we can do in a 45-90 minute podcast episode.
- The shownotes for today's episode can be found at www.scientifictriathlon.com/tts455/
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