I am training for a marathon, and, as I increase both by distance and pace, I am always excited when I have a "Pareto run": a run along the Pareto frontier of me trying to maximize distance and speed. When explaining it to some coworkers, I stumbled on a fairly intuitive explanation: "I've run farther before, and I've run faster before, but I've never run _this_ far, _this fast." There was some pushback about why not…
Pareto Front
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Re: Pareto Front
#62I have a weightlifting spreadsheet with weight on the vertical axis and reps on the horizontal axis. The value of each cell is the estimated 1 rep max if I accomplish that lift. In theory if my e1RM is 100kg then I can lift any permutation of (weight,reps) that have the same e1RM. This is akin to knowing Pareto Frontier of my current strength. I use conditional formatting to color cells according to the probability t…
Please don't make an app based on this.
Re: Pareto Front
#63Earlier quoted context omitted.
Almost the complete opposite of prioritisation. The Pareto points are where you sacrifice the least of anything to get the most of everything. There's the saying about buying computers. Good, Cheap, Fast, pick any two. That's where you would prioritise. If someone makes something that better, cheaper, and faster, or even pretty close to the best on two of those and clearly better on the other. It's a Pareto point. Ov…
Given this in the TFA > a Pareto front represents the set of solutions where no solution outperforms any other solution in the set at every objective I do not believe you are correct when you say > something that better, cheaper, and faster, or even pretty close to the best on two of those and clearly better on the other. It's a Pareto point. Since that would outperform on every objective GP's point that it's priorit…
Re: Pareto Front
#64I have a weightlifting spreadsheet with weight on the vertical axis and reps on the horizontal axis. The value of each cell is the estimated 1 rep max if I accomplish that lift. In theory if my e1RM is 100kg then I can lift any permutation of (weight,reps) that have the same e1RM. This is akin to knowing Pareto Frontier of my current strength. I use conditional formatting to color cells according to the probability t…
My main finding for “pick whatever weight you want today” was that picking a lot of different weights made the curve less identifiable, so my latest iteration encourages you to pick a ladder for a few sentinel exercises per mesocycle in order to improve the statistical power. In addition, strength improves more quickly at >80% of 1RM, and hypertrophy depends on proximity to failure, so if you pick a lower weight, you really need to go to failure, which burns you out for the rest of your session, where leaving 1-2 reps in reserve is probably sufficient for hypertrophy and leaves a lot more gas in the tank for the rest of the session. Definitely open to suggestion/discussion here.
https://curvefit.app (it runs on Cloudflare free tier, so I won’t have to start running ads or charging until I hit a couple thousand users)
Re: Pareto Front
#65I have a weightlifting spreadsheet with weight on the vertical axis and reps on the horizontal axis. The value of each cell is the estimated 1 rep max if I accomplish that lift. In theory if my e1RM is 100kg then I can lift any permutation of (weight,reps) that have the same e1RM. This is akin to knowing Pareto Frontier of my current strength. I use conditional formatting to color cells according to the probability t…
Respectfully, that's a cool illustration of the idea of xRMs etc but is missing the whole point of programming for higher or lower reps. E.g. lower reps are more stressful / higher cost of recovery but more strength-specific; high reps are better for hypertrophy work. But then, any well designed program will have you working across a range of rep ranges and so on. Please don't make an app based on this.
Some nuance here: the latest research shows that proximity to failure is the main hypertrophy driver regardless of load and rep count; high rep count makes proximity to failure harder to gauge; so high load/low reps close to failure is probably better for hypertrophy (there are other good reasons to do higher reps/lower load work though)
Re: Pareto Front
#66Earlier quoted context omitted.
This is a cool way to gamify weightlifting. Cheers!
Indeed, GP should take a spin at turning into an app. Could be worthwhile to have Claude take a first stab at a MVP. If pursued, good luck!
Re: Pareto Front
#67I have a weightlifting spreadsheet with weight on the vertical axis and reps on the horizontal axis. The value of each cell is the estimated 1 rep max if I accomplish that lift. In theory if my e1RM is 100kg then I can lift any permutation of (weight,reps) that have the same e1RM. This is akin to knowing Pareto Frontier of my current strength. I use conditional formatting to color cells according to the probability t…
Could you please share this spreadsheet? I would really love to have my own version of this.
Re: Pareto Front
#68I have a weightlifting spreadsheet with weight on the vertical axis and reps on the horizontal axis. The value of each cell is the estimated 1 rep max if I accomplish that lift. In theory if my e1RM is 100kg then I can lift any permutation of (weight,reps) that have the same e1RM. This is akin to knowing Pareto Frontier of my current strength. I use conditional formatting to color cells according to the probability t…
Respectfully, that's a cool illustration of the idea of xRMs etc but is missing the whole point of programming for higher or lower reps. E.g. lower reps are more stressful / higher cost of recovery but more strength-specific; high reps are better for hypertrophy work. But then, any well designed program will have you working across a range of rep ranges and so on. Please don't make an app based on this.
If you want the most 'optimal' form of this (aka, hell on earth), you should purchase a rowing machine. Being able to engage with very aggressive, full-body exercise every single day without exceptions is almost like cheating biology. You can maintain a 2-3x VO2 max premium over your peers with very little risk of injury.
Re: Pareto Front
#69Re: Pareto Front
#70You can see the Pareto Frontier well in DeepSWE's chart here - https://deepswe.datacurve.ai/ ChatGPT 5.6 Luna on the right (cheaper) cover most of the frontier, with a point for Deepseek flash, and higher performance overlapping heavily between 5.6 Sol and Fable. That DeepSeek point will probably move back towards Luna as deepseek announced a "significant" price increase coming to their API [1], which kind of demonst…
I've been wondering if OpenAI make Luna artificially cheap to get people into their eco system. I think it's great and hope the price can stay the same.
Going from 81GB of weights to 79GB of weights can mean a 50% reduction in GPU capacity required.
If you can fit a model in just one GPU (or rack) as opposed to across an entire datacenter, the latency gains can be substantial too. If you can reduce token latency by half, that would double the amount of customers you could support.