Doesn't your advice contradict the BBC's phrasing? Collectively, the band lost its spot in the top ten. And, collectively, the crew has 35 seconds to prepare the stage for the next performer.
I think this is to some extent a British English vs US English thing; it's certainly more common to treat words like crew/company/etc as plural in British English. The linked article is being overly prescriptive, though. Both are basically fine.
I was mixing methods, sorry. My initial rendition for solving the cuts would initialise a somewhat sparse network from tree to ground, and solve for non-overlapping paths.
This became convoluted and I just opted for a far easier method of solving vector intersections.
Its also not perfect since I haven't factored in rotation origin very well, and I'm now pursuing a far simpler physics-based approach
Equivalence is too strong a word, but content produced by spotify where musicians (or AI prompters) are mere contractors comes to mind.
Getting back to "I don't even want virtuous algorithmic recommendation"… I like jazz rock/fusion, especially when it has a touch of bluesy/blues rock influence. There is probably a lifetime of listening time of that genre, and it takes no effort for me to appreciate anything that resemble this. Long guitar solos by a jazz-educated guitarist who happens to like Jimi Hendrix, sign me up.
But I do think there is value in getting out of my comfort zone, and listen to something drastically new, from time to time. It requires effort though. My first reflex when I hear synthetic drums or autotune, for instance, is to press "next". But it is through other humans being recommendation, that I sometimes make that effort, and actually learn to appreciate something else.
Call me an elitist prick, but I hate to think of music as a commodity for us consumers to consume. It is art. Art is not always pleasant. It sometimes becomes pleasant after overcoming an initial disgust.
Why 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-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 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.
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.
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.
I know people personally with strong gripes about AI "infringement" (in quotes because I believe people are just confused about how these models work), and every single one of them -100%- have a stash of pirated media they casually accumulated over the years.
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 know people personally with strong gripes about AI "infringement" (in quotes because I believe people are just confused about how these models work), and every single one of them -100%- have a stash of pirated media they casually accumulated over the years.
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.
Not commenting on general trends, but I don't think my opinion on IP shifted massively as a result of the rise of LLMs. I can summarize it as follows:
- 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.
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 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.
Multiple companies sell Rugby data of various levels of granularity. I don't know if rugby has all the toys (i.e. full tracking outside of wearables) that soccer or American football have because there's less money sloshing around.
Most pros now have the vests, but also they tend to have additional tech in their mouth guards. This is mostly for CTE monitoring, but I imagine that there's other data that can be extracted
> 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.
Humans can do _most_ of what you said in real time, both providers using bespoke software and club analysts using off the shelf stuff like Sportscode. For full positional data on every player, every frame then yes, computer vision is doing most of the work but the quality isn't always great. Providers with in-stadium multi-camera systems provide great data, but you don't necessarily have access to the size of dataset you'd want for recruitment, and so lower-quality broadcast tracking exists (with all the problems you can imagine like missing players, occlusions, crazy camerawork etc). Most clubs also have wearables for their own analysis. Almost every fully automated broadcast tracking solution has hit a wall (sometimes on the first day of a season) in terms of quality that is often only solved by human QA, or by just discarding some games, so this is far from a completely solved problem. Fun domain to work in, but lots of horrible edge cases.
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.
Not really, a Pi with 8GB RAM, case and Power Supply would be around $110 or so, right? With storage even more. And the mentioned PC is probably almost twice as fast as a Pi.
Got a link? The starter set with 32GB SD card and 8GB RAM is £112… so you still have to get an SSD and SATA hat, or the hat this post is about. Then you’re at atleast £125, and your performance will be much lower than the mentioned PC.
Conversely, I think this book is applicable to non-game software too. I could just as well have called this book More Design Patterns, but I think games make for more engaging examples. Do you really want to read yet another book about employee records and bank accounts?
That being said, while the patterns introduced here are useful in other software, I think they’re particularly well-suited to engineering challenges commonly encountered in games:
- Time and sequencing are often a core part of a game’s architecture. Things must happen in the right order and at the right time.
- Development cycles are highly compressed, and a number of programmers need to be able to rapidly build and iterate on a rich set of different behavior without stepping on each other’s toes or leaving footprints all over the codebase.
- After all of this behavior is defined, it starts interacting. Monsters bite the hero, potions are mixed together, and bombs blast enemies and friends alike. Those interactions must happen without the codebase turning into an intertwined hairball.
- And, finally, performance is critical in games. Game developers are in a constant race to see who can squeeze the most out of their platform. Tricks for shaving off cycles can mean the difference between an A-rated game and millions of sales or dropped frames and angry reviewers.
Performance part alone is worth reading about game development for non game developers.
Retail off the shelf machines these days are so powerful that it encourages sloppy design and development.
