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I asked two OpenAI LLMs to help me get fit—one stood out.
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OK, I thought, I’ve got a challenge for o3: Make me physically stronger. Ten times stronger, in fact.
It’s been a life goal of mine to improve my chinups. I started 2024 unable to do even one, and months of working out alone got me nowhere. It wasn’t until I started working with a calisthenics trainer, Silvia, that I finally, after half a dozen focused sessions, got my first shaky repetition.
Now I want to do ten.
What better way to test AI’s capacity for teaching people in the real world than to ask it to help me achieve a goal I’ve never even come close to?
The more I thought about it, the more I liked this plan. I’d pit GPT-4o against o3 and see which model gave me a better chance of progressing from one to 10 unassisted chin-ups. I wanted to know which one would be a better teacher: 4o, the fast and reliable model I’ve been using as my daily driver, or o3, the more advanced reasoning model. Would either be up to the task? Would one emerge victorious? Let’s find out.
I would use OpenAI’s older standard model GPT-4o and o3 separately to generate a training plan. I created a set of rubrics against which to evaluate the models, based on what I think matters when you’re trying to learn something in the real world: quick feedback so you don’t make the same mistake over and over again, advice that’s tailored to your specific situation, incremental progress, and the motivation to keep going.
To judge the LLMs’ training plans, I also needed to define what “good” looks like. I trust my trainer, and she’s already delivered real results—so her guidance and the techniques she uses with me will serve as my baseline, the standard against which I’ll measure everything else.
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