While I generally agree (and that applies to almost all “an LLM can’t do that” discussions):
Head counts are not going to remain the same. Well, it might in writing, but there is a reason the WGA went on strike.
If you can apply effective filters/transforms to a base texture, you can now do the same work that would have taken you weeks in a day or two. If you aren’t “wasting time” writing unit tests or making utility functions, you no longer need junior developers to punt the Charlie Work to. And so forth.
In some fields? Being able to do more with less means you do a LOT more.
But, generally speaking, that means you need fewer people and you pay fewer people.
This is one of many many reasons that we need to have been exploring UBI decades ago. Because we are increasingly going to see a decrease in employment as technology is more and more able to “get the job done”. And unlike with farm work and factory work… there isn’t really anything on the horizon for all the “creative” workers to do.
kromem@lemmy.world 8 months ago
They largely are going to remain the same. Specific roles may shift around as specific workloads become obsolete, and you will have a handful of companies chasing quarterly returns at the cost of long term returns by trying to downsize keeping the product the same and reducing headcount.
But most labor is supply constrained not demand constrained, and the only way reduced headcounts would remain the status quo across companies is if all companies reduce headcounts without redirecting improved productivity back into the product.
You think a 7x reduction in texturing labor is going to result in the same amount of assets in game but 1/7th the billable hours?
No, that’s not where this is going. Again, a handful of large studios will try to get away with that initially, but as soon as competitors that didn’t go the downsizing route are releasing games with scene complexity and variety that puts their products to shame that’s going to bounce back.
If the market was up to executives, they’d have a single programmer re-releasing Pong for $79 a pop. But the market is not up to executives, it’s up to the people buying the products. And while AI will allow smaller development teams to produce games in line with today’s AAA scale products, tomorrow’s AAA scale products are not going to be possible with significantly reduced headcounts, as they are definitely not going to be the same scale and scope as today’s leading games.
A 10 or even 100 fold increase in worker productivity only means a similar cut in the number of workers as long as the product has hit diminishing returns on productivity investment, and if anything the current state of games development is more dependent on labor resources than ever before, so it doesn’t seem we’ve hit that inflection point or will anytime soon.
DrQuint@lemm.ee 8 months ago
I hear this, but then I also think of the “So… what hapenned to all the horses?” question
Their numbers went down. Drastically. That’s what hapenned. But that isn’t History when it happens to Horses.
kromem@lemmy.world 8 months ago
Do you think that same result would have happened if horses had other skills outside of the specific skill set that was automated?
If horses happened to be really good at pulling carts AND really good at driving, for instance, might we not instead have even more horses than we did at the turn of the 19th century, just having shifted from pulling carts to driving them?
I’m not sure the inability of horses to adapt to changing industrialization is the best proxy for what’s going to happen to humans.
wildginger@lemmy.myserv.one 8 months ago
How do you train AI to notice bugs humans notice? Kinda seems like thats the softwares exact weakness, is creating odd edge cases that make sense for the algorithym but not to the human eye
kromem@lemmy.world 8 months ago
Not really.
One of the big mistakes I see people make in trying to estimate capabilities is thinking of all in one models.
You’ll have one model that plays the game in ways that try a wider range of inputs and approaches to reach goals than what humans would produce (similar to the existing research like OpenAI training models to play Minecraft and mine diamonds off a handful of videos with input data and then a lot of YouTube videos).
Then the outputs generated by that model would be passed though another process that looks specifically for things ranging from sequence breaks to clipping. Some of those like sequence breaks aren’t even detections that need AI, and depending on just what data is generated by the ‘player’ AIs, a fair bit of other issues can be similarly detected with dumb approaches. The bugs that would be difficult for an AI to detect would be things like “I threw item A down 45 minutes ago but this NPC just had dialogue thanking me for bringing it back.” But even things like this are going to be well within the capabilities of multimodal AI within a few years as long as hardware continues to scale such that it doesn’t become cost prohibitive.
The way it’s going to start is that 3rd party companies dedicated to QA start feeding their own data and play tests into models to replicate and extend the behaviors, offering synthetic play testing as a cheap additional service to find low hanging fruit and cut down on human tester hours needed, and over time it will shift more and more towards synthetic testing.
You’ll still have human play testers around broader quality things like “is this fun” - but the QA that’s already being outsourced for bugs is going to almost certainly go the way of AI replacing humans entirely, or just nearly so.