TBK
Well-Known Member
- Thread starter
- #1
So i've been working for a while on creating a tool that helps analyze datalogs. It has 2 intended audiences, and plays a different role for each one:
- The average person who doesn't know too much, and so the tool helps explain what they're looking at
- The person who knows their shit. Provide a better log analysis experience overall, as well as acts as a nice repository, log comparison tool etc...
Really wish i could rely on AI for the analysis (and to determine what to analyze), but you'll just get confident nonsense. You still need a lot of structured and contextual reasoning for something like this, and in ways AI just can't help too much.
Instead there's just a fair bit of data science powering the logic. I've also written nearly 11,000 lines of rules, weights, and inference logic. It's a framework built on multi-variate signal correlation. And that's where it gets REALLY challenging. All the context that needs to be added. And i've had help from a few people who are lot more knowledgeable than i am to refine the top end of those rules, and where the intersections get a bit tricky.
It's currently fully operational....you can upload a CSV log and it'll spit out a full analysis. But it still need work. The logic (the rules framework, which is almost 40 different tabs at this point) still needs to be refined. A small gap in 1 place creates a massive domino effect of wrong analysis.
I'm going to be occasionally sharing some (hopefully) cool things from the project here. Until Bryan comes in here and reminds me that i know nothing Jon Snow.
This is one of the cooler charts, if only because most people just don't look at this. Most logs are just WOT pulls. And most analysis is done with WOT data. This is ΔTorque/ΔPedal from an older (really terrible) tune i had.
Don't get to see how broken that is when you're looking at WOT data
- The average person who doesn't know too much, and so the tool helps explain what they're looking at
- The person who knows their shit. Provide a better log analysis experience overall, as well as acts as a nice repository, log comparison tool etc...
Really wish i could rely on AI for the analysis (and to determine what to analyze), but you'll just get confident nonsense. You still need a lot of structured and contextual reasoning for something like this, and in ways AI just can't help too much.
Instead there's just a fair bit of data science powering the logic. I've also written nearly 11,000 lines of rules, weights, and inference logic. It's a framework built on multi-variate signal correlation. And that's where it gets REALLY challenging. All the context that needs to be added. And i've had help from a few people who are lot more knowledgeable than i am to refine the top end of those rules, and where the intersections get a bit tricky.
It's currently fully operational....you can upload a CSV log and it'll spit out a full analysis. But it still need work. The logic (the rules framework, which is almost 40 different tabs at this point) still needs to be refined. A small gap in 1 place creates a massive domino effect of wrong analysis.
I'm going to be occasionally sharing some (hopefully) cool things from the project here. Until Bryan comes in here and reminds me that i know nothing Jon Snow.
This is one of the cooler charts, if only because most people just don't look at this. Most logs are just WOT pulls. And most analysis is done with WOT data. This is ΔTorque/ΔPedal from an older (really terrible) tune i had.
Don't get to see how broken that is when you're looking at WOT data
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