11–20 of 123 posts
Seems like a pretty small (low latency) model. Would be interesting to hook up to mouse input (x and y) and see how well it predicts where I’m gonna move the mouse (maybe with and without seeing the predicted path)
Curious George here: why are you trying to predict where the mouse is going? :)
Seems like a pretty small (low latency) model. Would be interesting to hook up to mouse input (x and y) and see how well it predicts where I’m gonna move the mouse (maybe with and without seeing the predicted path)
Curious George here: why are you trying to predict where the mouse is going? :)
is it better than prophet from meta?
is it better than prophet from meta?
I imagine they're both worse than good old exponential smoothing or SARIMAX.
And exponentially higher cost for ML models.
Previous discussion: https://news.ycombinator.com/item?id=39235983
I've worked on language models since 2018, even then it was obvious why language was a useful and transferable task. I do not at all feel the same way about general univariate time series that could have any underlying process.
How can time series model be pre-trained ? I think I’m missing something.
[5, 3, 3, 2, 2, 2, 1, …]
What is the next number? Well let’s start with the search space - what is the possible range of the next number? Assuming unsigned 32bit integers (for explanation simplicity) it’s 0-(2^32-1)
So are all of those possible outputs equally likely? The next number could be 1, or it could be 345,654,543 … are those outputs equally likely?
Even though we know nothing about this sequence, most time series don’t make enormous random jumps, so no, they are not equally likely, 1 is the more likely of the two we discussed.
Ok, so some patterns are more likely than others, let’s analyse lots and lots of time series data and see if we can build a generalised model that can be fine tuned or used as a feature extractor.
Many time series datasets have repeating patterns, momentum, symmetries, all of these can be learned. Is it perfect? No, but what model is? And things don’t have to be perfect to be useful.
There you go - that’s a pre-trained time series model in a nutshell
Earlier quoted context omitted.
Curious George here: why are you trying to predict where the mouse is going? :)
Just to see how good the model is (maybe it’s creepily good in a fun way)