AI For Runners And Athletes: We're Making Excellent Progress

There were some very insightful perspectives in this speech—background information about engineering that showed us why artificial intelligence is so good at supporting people’s physical exercise.

I will outline a core idea from each contributor’s perspective to demonstrate three design aspects that are an important part of our exploration of the application of artificial intelligence in sports.

Edge devices and raw personal data

This idea about artificial intelligence actually contains two components—one related to where we place large language models and the other is related to the differences between our human language and the language that our vital signs “express” when measured in real time.

Alexander Amini knows both running and tennis, but he is also involved in a company that is revolutionizing the artificial intelligence of our time.

When describing how AI works for athletes, Amini first said it was about “enabling AI to exist where data exists.”

He explained that early LLMs were placed on the internet because edge devices did not have the ability to run them. Transformers are expensive and complex.

Now, the new model means we can install smart LLM on edge devices, which will reduce costs while helping athletes in places without internet access.

“It opens a whole new dimension of how we think about how we interact with AI,” he said. “AI doesn’t have to be something that (you) sends all of your data to third-party providers. It can now be something that is deeply embedded in your life, every stage of your day.”

Another point of his is that by wearing these wearable devices, we get a powerful set of data. This goes far beyond the information we get through conversations.

“It really comes down to the way we communicate with AI,” he said.

He elaborated on this further. Here is my interpretation: essentially, language is a set of symbols that we use to convey thoughts back and forth. In his words, it is "compressed". It's not original. By contrast, if you consider all the data your body is releasing every microsecond, it is a different medium of communication. If AI is taking all this data and using it instead of listening to your conversation, it will learn more about you as a person.

“The data we generate from the body cannot be compressed through language,” Amini said. "It's highly multidimensional and a highly expressed signal, right? And it's continuous. The amount of data is huge, and in many cases it's impossible to actually transfer the full complexity of our physical energy into these systems in real time. That's why, when we talk about bringing artificial intelligence to ourselves...that's what we unlock."

Am I dehydrated?

Emily Capodilupo offers another good point of view, she designed a tool called Whoop.

She explained that humans are not good at diagnosing whether they are dehydrated.

“We are actually bad judges of dehydration judgment,” she said. "Humans tend to be unaware that they are dehydrating. Generally speaking... your body knows a lot... but if you have algorithms running on your wrist, there are incredible safe use cases that can help you understand the ratio between the intensity of your body working and your speed: If they start to deviate too quickly, this may indicate that you are about to... hit the wall, or you are suffering from dehydration."

This is true for being a runner: If you consider trying to self-diagnose as a human, it really depends on whether you feel thirsty, fever, or you can tell whether you are dehydrated by your skin. Artificial intelligence can make a more meticulous judgment of what your body needs, which is a huge advantage for any athlete equipped with these tools.

My digital twin

Jamie was another person who spoke that day. He has done a lot of research on his own body through a process called digital twin technology.

Digital twins are just powerful models of something in the real world. I often use the word “stand-in” to talk about creating systems. This is a highly detailed simulation of things outside the digital world in physical things or simulated space.

Digital twins provide an analysis site that helps us improve measurements.

Jamie revealed that he has created 100 of his own samples, each costing about $5,000.

“I’ve spent $500,000 over the past decade on my biology, measuring the changes in results,” he said. “These results changes accumulate into this digital twin, which can predict my future, predict the risk of all my diseases, and we now have blood tests.”

In terms of accessibility, he quoted William Gibson: “The future is here—just uneven distribution.”

“We now have blood tests for basically all human diseases,” he continued, “and its accuracy is five to ten times higher than the current forecasts on the market.”

Going further, he explained that the institute applying new technologies found that based on the collected data, half of the analyzed patients could benefit from major interventions.

“Of the people we analyze these, we find that they have life-changing operational information in them, which is likely to extend their lifespan, and that is calculated, predicted and analyzed,” he said. This is an amazing statistic.

Future-oriented innovation

Each of these three discoveries illustrates the immense power of AI in helping us to “fine-tune” life (for health, for longevity, and so on). In many ways, we no longer need to guess.

Basically, most of what we previously thought was science fiction is now real. Some tools may or may not be available yet – so far, we haven’t seen all of these technologies play a role in our lives. But that will change soon.

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