> We can’t hire analysts to watch every match and enter data manually.
I'm surprised there's not enough fans willing to do that if you could gamify it.
Building an AI that watches rugby
11–20 of 52 posts
Re: Building an AI that watches rugby
#12Why the focus on scorekeeping? I feel like an AI model is overkill here, when you have text-based sources readily available such as news apps, Twitter feeds, and apps such as Livescore which would be easier and cheaper to scrape. They probably cover more matches that aren't televised too. I'd be curious to see what useful insights could be gleamed from the match commentary. You have the main commentator giving play-b…
The only interesting part of the model's output was { "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 th…
ESPN has play by play stuff for free like this on their website for some other sports
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
Re: Building an AI that watches rugby
#13I don't quite get how diffing frames allows you to find the scores. 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?
I think the text is wrong, it's diffing two frames and the areas that are the same are where the scorebaord is as this doesn't change between frames but everything else does.
Re: Building an AI that watches rugby
#14Reading the scoreboard from a TV screen and selling that data is restricted in many jurisdictions.
This work is pretty naive I think.
Re: Building an AI that watches rugby
#15Why the focus on scorekeeping? I feel like an AI model is overkill here, when you have text-based sources readily available such as news apps, Twitter feeds, and apps such as Livescore which would be easier and cheaper to scrape. They probably cover more matches that aren't televised too. I'd be curious to see what useful insights could be gleamed from the match commentary. You have the main commentator giving play-b…
The AI's job as described in this article is two-fold:
- 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.
Re: Building an AI that watches rugby
#16Reading the scoreboard from a TV screen and selling that data is restricted in many jurisdictions. This work is pretty naive I think.
Has there ever been a hacker whose top priority is ensuring compliance with every regulation in every jurisdiction worldwide?
Re: Building an AI that watches rugby
#17Why the focus on scorekeeping? I feel like an AI model is overkill here, when you have text-based sources readily available such as news apps, Twitter feeds, and apps such as Livescore which would be easier and cheaper to scrape. They probably cover more matches that aren't televised too. I'd be curious to see what useful insights could be gleamed from the match commentary. You have the main commentator giving play-b…
The AI's job as described in this article is two-fold: - 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…
Perhaps the most surprising thing about the whole LLM revolution is how quickly attitudes about IP have shifted in the HN and similar communities.
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.
Re: Building an AI that watches rugby
#18Earlier quoted context omitted.
The only interesting part of the model's output was { "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 th…
ESPN has play by play stuff for free like this on their website for some other sports 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
If this is the final product, not much difference at all.
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.
Re: Building an AI that watches rugby
#19Earlier quoted context omitted.
The AI's job as described in this article is two-fold: - 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…
Perhaps the most surprising thing about the whole LLM revolution is how quickly attitudes about IP have shifted in the HN and similar communities. 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 p…
How do you know you're seeing peoples' opinions change, and not just a change in which people express their opinions?
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.
Re: Building an AI that watches rugby
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