We Hired an AI Coach So You Don't Have To! with Matti Rowe

Training Babble: Off-Road Insights for Mountain Bike and Gravel Cycling

Το περιεχόμενο παρέχεται από το Dave Schell. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Dave Schell ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.

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Summary
In this episode of the Training Babble Podcast, Coach Dave Schell and guest Matty Rowe of Gravel God Cycling dig into the implications of AI in coaching. They discuss the rise of AI tools like CoachCat, the challenges of relying on flawed metrics, and the importance of human expertise in interpreting data. The conversation highlights the complexities of training plans and the need for personalized coaching, emphasizing that while AI can assist, it cannot replace the nuanced understanding that comes from experience and direct athlete-coach interaction. In this conversation, Matti and Dave explore the complexities of coaching, particularly in the context of AI's role in athlete performance. They discuss the importance of context and nuance in coaching, the limitations of AI in understanding human experiences, and the distinction between information and knowledge. The conversation also touches on the barriers athletes face in achieving success and the potential future of AI in coaching, emphasizing the need for human connection and understanding.

Takeaways

AI is a significant trend in coaching, but it has limitations.
The rise of AI tools has led to a gold rush mentality.
AI can generate plausible-sounding information that may be incorrect.
Coaches must be wary of relying solely on AI-generated data.
Metrics like TSS and HRV can be flawed and misleading.
Personalized coaching is essential for effective training.
Athletes often seek simple solutions to complex training issues.
The body responds unpredictably to training inputs.
AI cannot address underlying issues like athlete priorities.
Training effectiveness is not solely determined by data metrics. Context is crucial in coaching; without it, advice can be meaningless.
AI lacks the nuance needed for effective coaching.
Coaches must understand the barriers athletes face beyond just data.
There's a significant difference between information and knowledge.
AI can assist coaches but cannot replace the human element.
Education and self-awareness are vital for athletes and coaches alike.
The future of coaching may involve AI, but human connection remains essential.
Athletes often overlook lifestyle factors that hinder performance.
AI can help manage tedious tasks, allowing coaches to focus on athletes.
Authenticity in coaching will be valued over AI-generated insights.

Matti's Article on AI

Dave's Article on AI

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#Sports #Endurance #Cycling #Bike #Training #Dave Schell #Gravel #Physiology #Ftp #Science #Fitness #Mountain Biking