> E.g. If I ever see a monetary value stored in something else than integers I'm going to run away screaming (thank you Rust decimals represented as JSON floats). It's always integers unless you have a VERY good reason to do otherwise (though exported view can be in anything, even in weird bitcoded formats).
That really overstates the issue. Whole domains of finance run just fine on doubles.
If you're doing Monte Carlo options pricing over interest rate paths, and you're interested in the risk metrics, like durations, convexity, vega, and so on, no one cares what your rounding convention is. doubles are just fine, thank you. How are you going to force `exp(-rt)cashflow` to be an integer? Or the normal CDF?
Yes, there are domains where ints make sense. But it's certainly not universal, you just need to make the right engineering choice.
I've found differential forms to be more useful than GA, but that might just be that I was brought up in the MTW tradition and don't quite get GA.
Whenever I look at GA, I try to figure out where the metric comes in, and I just don't see it.
For context, way back when I did astro theory and wanted to do things like figure out things like the magnetic field structure in the curved spacetime near highly-magnetized rotating conducting spheres, and then do some basic plasma physics in that environment.
The differential geometry approach at least gives the structure to think about that, then you can go down to the index-style notation to actually get the differential equations you need to solve. The GA approach, I'm not even sure how to frame the problem.
VSCode binds a lot of basic commands to function keys, so I'm always doing Fn-F12. That seems like a weird choice, and if it really bothered me, I could remap it, but so far I haven't.
I'm sorry, it's a really inefficient format. I don't want to sit and listen for two hours to what's most likely half an hour of content by reading. Just write down what you have to say already!
I guess you could do double-speed, but I find that somehow stressful.
Edit: I just read the paper. It took me 21 minutes. It's not long, only 11 pages.
It's worth it whenever you have a reasonable amount of training data. You can get substantial quality improvements automatically. Unless you're doing some kind of prompt-optimization, prompt-tuning is a lot of random guessing and trial-and-error. It's also most necessary when you have a smaller base model, as opposed to one of the big ones.
Wouldn't a vector database just get you nearest-neighbors on the embeddings? How would that answer a generative or extractive question? I can see it might get you sentiment, but would it help with "tell me all the places that are mentioned in this review"?
That really overstates the issue. Whole domains of finance run just fine on doubles.
If you're doing Monte Carlo options pricing over interest rate paths, and you're interested in the risk metrics, like durations, convexity, vega, and so on, no one cares what your rounding convention is. doubles are just fine, thank you. How are you going to force `exp(-rt)cashflow` to be an integer? Or the normal CDF?
Yes, there are domains where ints make sense. But it's certainly not universal, you just need to make the right engineering choice.