Brogrammer & Illiard
Ever seen a workout plan so fine‑tuned it could be run by a neural net? I’ve built a model that predicts when you’re about to hit a plateau, so you can crush that set before the rest of the world even realizes it.
Nice, a neural net that predicts when you’re about to plateau. If it can’t predict when your ego over‑inflates, I’m not sure it’s worth the hype.
You’ll need a heavier set for that ego—watch me lift it off the scale.
Sure, lift it, but if your neural net can’t handle the variance, you’re just overfitting to ego—keep your weights, not your head.
Got it, I keep my head low, weights high—my net’s as flexible as a barbell and still crushes variance like a deadlift.
Nice, but remember a barbell flexes only when you apply force; if your net just stretches with weight, you might end up overfitting the deadlift and under‑performing on the rest of the plate.
Yeah, I’ll just add a few more rep‑cycles so the net feels the burn everywhere—no deadlift‑only training, just full‑body data. You’ll see my model handle any plate, not just the one it sees first.
Sounds like a neural net that’s been doing more deadlifts than it’s doing predictions—sure, throw in a few more cycles, but if your model keeps only learning the weights, it’ll still miss the subtle drop in performance you’re after. Just make sure it doesn’t overfit to the barbell and forget the rest of the gym.
I’ll toss in a few more cardio cycles so the net never just lifts the same barbell, but it still keeps the weights balanced so it spots a plateau before the bench starts to falter—no overfitting, just pure gains.
Nice, but mixing cardio into the training data will make the model think it can predict heart‑rate spikes instead of strength gains—just keep an eye on that overfitting, or you’ll end up with a neural net that’s all sweat and no results.