Building an AI that watches rugby(nickjones.tech) |
Building an AI that watches rugby(nickjones.tech) |
In seriousness, this is a cool project and show how sophisticated analysis LLMs can do in a plug and play manner. They may not always be the best solution but a fantastic baseline that can be deployed and adapted to a usecase in less than an hour.
The scope is a bit different. The study uses an LLM to interpret pose estimation data and describe the behavior in each frame. The output is text which can be used to create embeddings of behavior. As someone who works in ethology, that's a clever (but maybe expensive) idea.
I think the author could use something similar. With multi-person pose estimation models.
Notice how they watched the game and got the statistics like that. The restrictions are about using the scoreboard and the data displays and reselling/commercialising that data. It is however legal to watch the game and compile and distribute your own stats due to the game entering public domain.
Due to this many betting companies and data collection companies have to pay people to watch the game vs just scraping the scoreboard (which is the context from which I learnt about this). ironically at venue OCR is a common way to get scoreboard data.
I'd be curious to see what useful insights could be gleamed from the match commentary. You have the main commentator giving play-by-play objective reporting and then a 'colour' commentator giving some subjective analysis during breaks in play. I bet there's a lot of interesting ways this could be used.
> The plan was simple.
You know you're in for a funny read.
More seriously though, the JSON example from a vision language model is interesting but does not take into account how much extrapolation (hallucination) the model will insert over time.
For instance, even if not visible in the image, your VLM will probably start inserting details (such as the color of the team's jersey) based on knowing the team's three-letter identifier.
So the reliability of the system will go down over time, and it probably compounds if you're using some of that info to feed further steps in the loop.
You really need to take a 'full pitch' feed directly from the venue, rather than what is broadcast.
TFA mentions comparing a frame with and without - but how do you generate that frame without? If you can already do it, what's useful about doing that?
And then he does a good ol' regular crop on the original image to get the UI excerpt to feed the vision model.
For now.
I'm surprised there's not enough fans willing to do that if you could gamify it.
I was hoping for more.
- The relatively trivial task of extracting textual data from the screen.
- The task of obfuscating that they're publishing other people's work as their own.
When I clicked the article I assumed they'd try to automatically construct analysis of the game by using AI to analyze frames of the game, but that's not what they are doing. They are extracting some trivial information from the frames, and then they process the audio of the referee mic and commentary.
In other words, the analysis has already been done by humans and they just want to re-publish this analysis as their own, without paying money for it. So they run it through an AI because in today's legal environment this seems to completely exempt you from copyright infringement or plagiarism laws.
A few years ago, media companies were rent-seeking parasites who leveraged the jack-booted thugs of law enforcement to protect an artificial monopoly using IP laws that were massive overreach and contrary to the interests of humanity.
Today, suddenly, media companies are pillars of society whose valuable contributions must be protected from the scourge of theft by everything from VC backed AI companies to armchair hackers who don’t respect the sanctity of IP.
It’s amazing how mutable these principles are. I’m sure plenty of people are somewhere between the two extreme, but the shift is so dramatic that I am 100% sure many individuals have completely revised their opinions of IP companies based largely on worries about their own work being disrupted.
At the very least it should create some empathy for the lawyers and business folk we all despised for their rent-seeking blah blah blah. They were just honestly espousing the positions their financial incentives aligned them to.
{ "current_play": "ruck", }
So the vision model can correctly identify that there's a ruck going on and that the ball is most likely in the ruck.
Why not build on this? Which team is in possession? Who was the ball carrier at the start of the ruck, and who tackled him? Who joined the ruck, and how quickly did they get there? How quickly did the attacking team get the ball back in hand, or the defending team turn over possession? What would be a good option for the outhalf if he got the ball right now?
All of these except the last would be straightforward enough for a human observer with basic rugby knowledge going through the footage frame by frame, and I bet it would be really valuable to analysts. It seems like computer vision technology is at a stage where this could be automated too.
not sure if it is done by a human or not
curious how “an AI can do it” yields much difference in terms of result for the casual watcher
An AI can do it in volume, and therefore cheaper. I don't think a human could do everything I said in real time - maybe with a lot of training and custom software.
A human could transcribe the scoreboard, but the article still thinks that's an interesting application of cutting-edge machine vision.
But where the human version is pretty much as far as it’s going to go, this is v0.01 of the AI version. Pretty soon the AI will be predicting what will happen next, commenting on whether this was a good idea (based on statistics), and letting the viewer ask questions about what exactly happened and why.
That said I'd personally be happy if LLMs cause the death (or drastic weakening) of copyright and IP laws, however as it is now, with no copyright for AIs but the same old copyright for humans, it's the worst of both worlds.
People are in it for themselves. When you are young everyone has righteous ideals, but then trends of society eventually ebb, and you realize that just about everyone was simply virtue signalling, and few people are committed even to their own detriment.
2005: "End copyright! Trash IP law! Liberate media!"
2025: "Strengthen Copyright! Extend IP Protection! Protect makers!"
I don't know them, of course, but it is a consistent and imho reasonable position to be against copyright yet, while we normal people live in fear of copyright, ask for it to be applied to AI as well.
It is even reasonable IMO to be against copyright for individuals but in favour of copyright for businesses. That's how it de facto works in a lot of places anyway.
- It seems desirable to have some system that allows creatives to be paid for their work.
- Whether current IP law is the best system we can come up with is highly debatable. But nevertheless it is the system we have, and its existence is to some extent justified.
- If we look at the "pefect case" where IP law functions as intended (for example, an author publishes a book in which they invested years of their life), then breaking IP law (sharing that author's work without their consent) in that instance seems, to me, immoral.
- Nevertheless there are plenty of excesses in the system where I would judge that the application of IP law is unjustified and breaking the law is morally justified (naturally I still don't recommend it). This includes, for example, paywalled papers from publicly-funded research, works that can no longer reasonably be purchased (for example games for old consoles), most if not all software patents, ...
So the question simply boils down to: is sports commentary justifiably protected under IP law? I think the answer is a pretty clear-cut "yes" here, I don't see how it falls under any case of IP law overreach.