It's all unstructured text (title, company, company size, experience, skills, raw text, etc.) and LLMs are pretty bad at assigning numerical scores in a vacuum. To make it work, we'd have to provide a representative set of examples, break scoring down by specific field, etc.
Kind of a lot of work compared to just dumping the text of 2 profiles into a context window along with a vague description of what I want, and having the LLM make the binary judgment.
Yeah that's exactly what we observed. Our goal was to create an absolute score that's completely independent from the Corpus, which is difficult because naturally all ELO distributions are inherently tied to the corpus itself!
When we were exploring the mathematical foundations, we considered ELO scoring against a "Universal Corpus" based on the natural entropy of human language (Obviously that's intractable, but sometimes this term cancels out like in the DPO proof).
But eventually we figured out a method using cross-query comparisons to assign an "ELO bias" to all document ELOs within a given query's candidate list. This normalizes it correctly such that when a candidate list is all bad, the ELOs shift low. And when the candidate list is all good, the ELOs shift high. Even when the relative ELOs are all the same.
Congrats! I've been wanting exactly this app. I paid $5.99 for HealthFit trying to get similar information, but it doesn't (afaik) show the weekly/daily zone summaries.
I'd really love to see last week's information. Especially since you launched on a Monday, I'd love to have a new-user experience that shows me last week's info.
Other misc feedback:
1. Upon launching the app, I didn't see any data. Had to go into the gear menu -> approve health data sharing. I think it'd be better to push the user to this approval flow on their first session? (Edit: Aha, after watching the video: settings -> time period -> last 7 days)
2. Neither here nor there, but I wanted to download this so searched the app store on my phone for "heart rate zones plus" and this app was #16. I'm curious if anyone in the discussion knows -- how is this search rating determined? Is there anything the author can do to improve the ranking?
This is a horrible abuse of computing power, but what I do is track my heart rate zones in Polar Beat (for my brand of heart rate monitor), and then I just screenshot the summary page for the workout. Then, once every week or two, I just dump my screenshots into Gemini and ask it to produce a report, where I get things like weekly averages, moving averages, highs & lows, etc.
Hi thanks for the feedback. I'm definitely thinking about adding some more historic data and also week over week comparison.
about 2. from my understanding good ratings and usage would help the ranking in app stores. But I don't expect some good positioning there (already) with an app being 4 days old.
> that's a great use case! the aria snapshot that browser mcp generates is enough to write tests for playwright using its role-based locators, but i may add a get_page_html tool in the same way that they're considering: https://github.com/microsoft/playwright-mcp/issues/103
You just check the Analysis/Interpreter box and tell it to how and when to use Python in the GPT instructions.
I put a mini Python lib for rolling dice and skill checks in the GPT instructions and just enabled the Analysis or whatever checkbox. And I told it to run the code in the beginning to initialize and use the functions for dice rolls etc.
It can write and call functions on the fly, but I wrote them ahead of time and have it call the library functions to reduce the amount of code needed to the minimum to try to speed things like dice rolls up.
Can’t find that post, but here is a breakdown of claims from an interview she conducted a few months ago: https://www.reddit.com/r/Supplements/comments/1jo8pk8/my_top...