Apple Watch has been a popular choice in running and triathlon. You can now track and execute your AI Endurance custom running, cycling and swimming workouts on your Apple Watch.
Finding the ideal training regimen to align with your goals and abilities can be challenging. This is where our unique AI technology steps in to address this hurdle. Our custom workouts utilize the wealth of data gathered from your daily activities, heart rate, and previous workouts to create tailored training plans that meet your specific needs. Whether you're a beginner looking to build stamina or an experienced runner training for a marathon, these AI workouts offer a dynamic and intelligent approach to your training.
We have partnered with Watchletic to bring you the AI Endurance experience to your Apple Watch. Via Watchletic you can
Follow these steps to connect your Apple Watch to AI Endurance via Watchletic:
One of the most remarkable aspects of AI Endurance is the ability to learn and evolve alongside your progress. As you continue with these workouts, the AI algorithms become more familiar with your strengths, weaknesses, and preferences. This ongoing learning enables the system to refine and optimize your training plans, delivering a truly personalized and adaptive experience that propels you towards your desired outcomes.
With AI Endurance custom running workouts for Apple Watch, runners of all levels can benefit from optimized training plans that adapt to their progress, conveniently accessible from their wrists. Whether you aim to enhance your running endurance, set new personal records, or prepare for a specific race, our AI-powered workouts on Apple Watch provide the tools and guidance to help you efficiently and effectively achieve your goals. Embrace the power of AI and let your Apple Watch elevate your running experience to new heights.
by Stefano Andriolo. We demonstrate a universal relationship between cycling power and DFA alpha 1 from every day workout data that allows accessible and regular tracking of aerobic and anaerobic thresholds without the need of an exercise lab or even a dedicated testing protocol.
by Stefano Andriolo. Building on previous work, we refine a method to accurately determine the relationship between DFA alpha 1 and power. This method can be used to track fitness and thresholds of an athlete. We find in some cases ramp detection tends to overestimate thresholds, a finding mirrored in recent physiological papers. On the other hand, thresholds based on clustering of DFA alpha 1 values tend to agree well with this new method. We propose a hybrid lab and everyday workout experiment to further study the relationship.
In this post, we explain how to use AI Endurance’s cycling training plan that we generated for Paris to Ancaster, Canada’s biggest gravel racing event. The plan includes detailed workout instructions. For indoor cycling, we show how to use AI Endurance with Trainerroad and Zwift.
There are different options on the market for optimized AI training plans that are based on applying machine learning to your individual data. In this post, we compare the different options and their features.
