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TimesFM: Time Series Foundation Model for time-series forecasting
- uoaei 2y ago"Time series" is such an over-subscribed term. What sorts of time series is this actually useful for? For instance, will it be able to predict dynamics for a machine with thousands of sensors?
- techwizrd 2y agoSpecifically, its referring to univariate, contiguous point forecasts. Honestly, I'm a little puzzled by the benchmarks.
- sarusso 2y agoEven if it was for multivariate time series, the model would first need to infer what machine are we talking about, then its working conditions, and only then make a reasonable forecast based on an hypothesis of its dynamics. I don’t know, seems pretty hard.
- uoaei 2y agoIndeed. An issue I ran into over and over while doing research for semiconductor manufacturing. My complaint was more illustrative than earnest.
- iamgopal 2y agoHow can time series model be pre-trained ? I think I’m missing something.
- melenaboija 2y agoThird paragraph of the introduction of the mentioned paper[1] in the first paragraph of the repo. [1] https://arxiv.org/abs/2310.10688 https://arxiv.org/abs/2310.10688
- jurgenaut23 2y agoI guess they pre-trained the model to exploit common patterns found in any time-series (e.g., seasonalities, trends, etc.)... What would be interesting, though, is to see if it spots patterns that are domain-specific (e.g., the ventricular systole dip in an electrocardiogram), and possibly transfer those (that would be obviously useless in this specific example, but maybe there are interesting domain transfers out there)
- malux85 2y agoIf you have a univariate series, just single values following each other - [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
- sarusso 2y agoMy understating is that, while your eye can naturally spot a dependency over time in time series data, machines can’t. So as we did for imaging, where we pre-trained models to let machines easily identify objects in pictures, now we are doing the same to let machines “see” dependencies over time. Then, how these dependencies work, this is another story.
- nwoli 2y agoSeems 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)
- jarmitage 2y agoWhat is the latency?
- throwtappedmac 2y agoCurious George here: why are you trying to predict where the mouse is going? :)
- nwoli 2y agoJust to see how good the model is (maybe it’s creepily good in a fun way)
- Timon3 2y agoThere's a fun game idea in there! Imagine having to outmaneuver a constantly learning model. Not to mention the possibilities of using this in genres like bullet hell...
- teaearlgraycold 2y agoThink of the sweet sweet ad revenue!
- throwtappedmac 2y agoHaha as if advertisers don't know me better than I know me
- tasty_freeze 2y agoGame developers are constantly trying to minimize lag. I have no idea if computers are so fast these days that it is a "solved" problem, but I knew a game developer ages ago who used a predictive mouse model to reduce the apparent lag by guessing where the mouse would be at the time the frame was displayed (considering it took 30 ms or whatever to render the frame).
- dangerclose 2y agois it better than prophet from meta?
- VHRanger 2y agoI imagine they're both worse than good old exponential smoothing or SARIMAX.
- Pseudocrat 2y agoDepends on use case. Hybrid approaches have been dominating the M-Competitions, but there are generally small percentage differences in variance of statistical models vs machine learning models. And exponentially higher cost for ML models.
- VHRanger 2y agoAt the end of the day, if training or doing inference on the ML model is massively more costly in time or compute, you'll iterate much less with it. I also think it's a dead end to try to have foundation models for "time series" - it's a class of data! Like when people tried to have foundation models for any general graph type. You could make foundation models for data within that type - eg. meteorological time series, or social network graphs. But for the abstract class type it seems like a dead end.
- rockinghigh 2y agoThese models may be helpful if they speed up convergence when fine tuned on business-specific time series.
- dangerclose 2y agoso this TimesFM is also in the same category as TimeGPT from nixtlaverse?
- SpaceManNabs 2y agois there a ranking of the methods that actually work on benchmark datasets? Hybrid, "ML" or old stats? I remember eamonnkeogh doing this on r/ML a few years ago.
- l2dy 2y agoBlog link (Feb 2024): https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ https://research.google/blog/a-decoder-only-foundation-model... Previous discussion: https://news.ycombinator.com/item?id=39235983 https://news.ycombinator.com/item?id=39235983
- whimsicalism 2y agoI'm curious why we seem convinced that this is a task that is possible or something worthy of investigation. 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.
- sarusso 2y ago+1 for “any underlying process”. It would be interesting what use case they had in mind.
- baq 2y agowell... if you look at a language in a certain way, it is just a way to put bits in a certain order. if you forget about the 'language' part, it kinda makes sense to try because why shouldn't it work?
- IshKebab 2y agoWhy not? There are plenty of time series that have underlying patterns which means you can do better than a total guess even without any knowledge of what you are predicting. Think about something like traffic patterns. You probably won't predict higher traffic on game days, but predicting rush hour is going to be pretty trivial.
- smokel 2y agoThe things that we are typically interested in have very clear patterns. In a way, if we find that there are no patterns, we don't even try to do any forecasting. "The Unreasonable Effectiveness of Mathematics in the Natural Sciences" [1] hints that there might be some value here. [1] https://en.m.wikipedia.org/wiki/The_Unreasonable_Effectiveness_of_Mathematics_in_the_Natural_Sciences https://en.m.wikipedia.org/wiki/The_Unreasonable_Effectivene...
- yonixw 2y agoExactly, so for example, I think the use of this model is in cases where you want user count to have some pattern around timing. And be alerted if it has spike. But you wouldn't want this model for file upload storage usage which only increases, where you would put alerts based on max values and not patterns/periodic values.
- polskibus 2y agohow good is it on stocks?
- svaha1728 2y agoThe next index fund should use AI. What could possibly go wrong?
- whimsicalism 2y agoI promise you your market-making counterparties already are.
- hackerlight 2y agoWhat kind of things are they doing with AI?
- whimsicalism 2y agoPredicting price movements, finding good hedges, etc.
- claytonjy 2y agoif I knew it was good, why would I tell you that?
- fedeb95 2y agoit doesn't apply. Checkout the Incerto by Nassim Nicholas Taleb.
- esafak 2y agoIs anyone using neural networks for anomaly detection in observability? If so, which model and how many metrics are you supporting per core?
- leeoniya 2y agoLSTM is common for this. also https://facebook.github.io/prophet/ https://facebook.github.io/prophet/
- morkalork 2y agoHow data hungry is it, or what is the minimum volume of data needed before its worth investigating?
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- viraptor 2y agoThe more complex the data is, the more you need. If your values are always 5, then you need only one data point.
- morkalork 2y agoIf your values were always 5,you wouldn't use an LSTM to model it either. So presumably there's a threshold for when LSTM becomes practical and useful, no?
- viraptor 2y agoSure, that was an extreme example. The point was that the minimum of data is 1 point, maximum is "all of it". It entirely depends on your use case.
- sarusso 2y agoWhat do you mean by “observability”?
- optimalsolver 2y agoWhen it comes to time series forecasting, if the method actually works, it sure as hell isn't being publicly released.
- baq 2y agoand yet we have those huge llamas publicly available. these are computers that talk, dammit
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- speedgoose 2y agoSome times series are more predictable than others. Being good at predicting the predictable ones is useful. For example you can easily predict the weather with descent accuracy. Tomorrow is going to be about the same than today. From there you can work on better models. Or predicting a failure in a factory because a vibration pattern on an industrial machine always ended up in a massive failure after a few days. But I agree that if a model is good at predicting the stock market, it’s not going to be released.
- mhh__ 2y agoDear googler or meta-er or timeseries transformer startup something-er: Please make a ChatGPT/chat.lmsys.org style interface for one of these that I can throw data at and see what happens. This one looks pretty easy to setup, in fairness, but some other models I've looked at have been surprisingly fiddly / locked behind an API. Perhaps such a thing already exists somewhere?
- wuj 2y agoOn a related note, Amazon also had a model for time series forecasting called Chronos. https://github.com/amazon-science/chronos-forecasting https://github.com/amazon-science/chronos-forecasting
- toasted-subs 2y agoSomething I've had issues with time series has been having to use relatively custom models. It's difficult to use off the shelf tools when starting with math models.
- claytonjy 2y agoAnd like all deep learning forecasting models thus far, it makes for a nice paper but is not worth anyone using for a real problem. Much slower than the classical methods it fails to beat.
- belter 2y agoThey also have Amazon Forecast with different algos - https://aws.amazon.com/forecast/ https://aws.amazon.com/forecast/
- aantix 2y agoWould this be useful in predicting lat/long coordinates along a path? To mitigate issues with GPS drift. If not, what would be a useful model?
- smokel 2y agoMap matching to a road network might be helpful here. For example, a Hidden Markov Model gives good results. See for instance this paper: "Hidden Markov map matching through noise and sparseness" (2009) https://www.microsoft.com/en-us/research/wp-content/uploads/2016/12/map-matching-ACM-GIS-camera-ready.pdf https://www.microsoft.com/en-us/research/wp-content/uploads/...
- bbstats 2y agoKalman filter
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- chaos_emergent 2y ago"Why would you even try to predict the weather if you know it's going to be wrong?" - most OCs on this thread
- david_shi 2y agoI have a few qualms with this app: 1. For a Linux user, you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem. From Windows or Mac, this FTP account could be accessed through built-in software. 2. It doesn't actually replace a USB drive. Most people I know e-mail files to themselves or host them somewhere online to be able to perform presentations, but they still carry a USB drive in case there are connectivity problems. This does not solve the connectivity issue. 3. It does not seem very "viral" or income-generating. I know this is premature at this point, but without charging users for the service, is it reasonable to expect to make money off of this?
- viraptor 2y agoI'm not sure I understand two things here. Could someone clarify: 1. This is a foundation model, so you're expected to fine tune for your use case, right? (But readme doesn't mention tuning) 2. When submitting two series, do they impact each other in predictions?
- hm-nah 2y agoAnyone have insights working with Ikigai’s “Large Graphical Model” and how well it does on time-series? It’s proprietary, but I’m curious how well it performs.
- celltalk 2y agoIf I give this model the first 100 prime numbers, does it give me back the rest of it? If so what is the circuit?
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- DeathArrow 2y agoIt seems to me that predicting something based on time is rarely accurate and meaningful. Suppose you want to buy stocks? Would you look on a time based graph and buy according to that? Or you rather look at financial data, see earnings, profits? Wouldn't a graph that has financial performance on x-axis be more meaningful that one that has time? What if you research real estate in a particular area? Wouldn't be square footage a better measure than time?
- Terretta 2y ago> Would you look on a time based graph and buy according to that? Or you rather look at financial data, see earnings, profits? Things affecting financials happen through time.
- DeathArrow 2y agoAll things happen through time, but my argument is that time might not be the best parameter to model relations.
- htrp 2y agoProphet 2.0