It’s so funny how all this is only a problem within a capitalist frame of reference.
The hype should go the other way. Instead of bigger and bigger models that do more and more - have smaller models that are just as effective. Get them onto personal computers; get them onto phones; get them onto Arduino minis that cost $20 - and then have those models be as good as the big LLMs and Image gen programs.
This has already started to happen. The new llama3.2 model is only 3.7GB and it WAAAAY faster than anything else. It can thow a wall of text at you in just a couple of seconds. You’re still not running it on $20 hardware, but you no longer need a 3090 to have something useful.
That would be innovation, which I’m convinced no company can do anymore.
It feels like I learn that one of our modern innovations was already thought up and written down into a book in the 1950s, and just wasn’t possible at that time due to some limitation in memory, precision, or some other metric. All we did was do 5 decades of marginal improvement to get to it, while not innovating much at all.
This is why you’re seeing news articles from Sam Altman saying that AGI will blow past us without any societal impact. He’s trying to lessen the blow of the bubble bursting for AI/ML.
It’s been 5 minutes since the new thing did a new thing. Is it the end?
As I use copilot to write software, I have a hard time seeing how it’ll get better than it already is. The fundamental problem of all machine learning is that the training data has to be good enough to solve the problem. So the problems I run into make sense, like:
- Copilot can’t read my mind and figure out what I’m trying to do.
- I’m working on an uncommon problem where the typical solutions don’t work
- Copilot is unable to tell when it doesn’t “know” the answer, because of course it’s just simulating communication and doesn’t really know anything.
2 and 3 could be alleviated, but probably not solved completely with more and better data or engineering changes - but obviously AI developers started by training the models on the most useful data and strategies that they think work best. 1 seems fundamentally unsolvable.
I think there could be some more advances in finding more and better use cases, but I’m a pessimist when it comes to any serious advances in the underlying technology.
Not copilot, but I run into a fourth problem:
4. The LLM gets hung up on insisting that a newer feature of the language I’m using is wrong and keeps focusing on “fixing” it, even though it has access to the newest correct specifications where the feature is explicitly defined and explained.Oh god yes, ran into this asking for a shell.nix file with a handful of tricky dependencies. It kept trying to do this insanely complicated temporary pull and build from git instead of just a 6 line file asking for the right packages.
Theres no bracing for this, OpenAI CEO said the same thing like a year ago and people are still shovelling money at this dumpster fire today.
It’s had all the signs of a bubble for the last few years.
Huh?
The smartphone improvements hit a rubber wall a few years ago (disregarding folding screens, that compose a small market share, improvement rate slowed down drastically), and the industry is doing fine. It’s not growing like it use to, but that just means people are keeping their smartphones for longer periods of time, not that people stopped using them.
Even if AI were to completely freeze right now, people will continue using it.
Why are people reacting like AI is going to get dropped?
People are dumping billions of dollars into it, mostly power, but it cannot turn profit.
So the companies who, for example, revived a nuclear power facility in order to feed their machine with ever diminishing returns of quality output are going to shut everything down at massive losses and countless hours of human work and lifespan thrown down the drain.
This will have an economic impact quite large as many newly created jobs go up in smoke and businesses who structured around the assumption of continued availability of high end AI need to reorganize or go out of business.
Search up the Dot Com Bubble.
Because in some eyes, infinite rapid growth is the only measure of success.
Because novelty is all it has. As soon as it stops improving in a way that makes people say “oh that’s neat”, it has to stand on the practical merits of its capabilities, which is, well, not much.
I’m so baffled by this take. “Create a terraform module that implements two S3 buckets with cross-region bidirectional replication. Include standard module files like linting rules and enable precommit.” Could I write that? Yes. But does this provide an outstanding stub to start from? Also yes.
And beyond programming, it is otherwise having positive impact on science and medicine too. I mean, anybody who doesn’t see any merit has their head in the sand. That of course must be balanced with not falling for the hype, but the merits are very real.
There’s a pretty big difference between chatGPT and the science/medicine AIs.
And keep in mind that for LLMs and other chatbots, it’s not that they aren’t useful at all but that they aren’t useful enough to justify their costs. Microsoft is struggling to get significant uptake for Copilot addons in Microsoft 365, and this is when AI companies are still in their “sell below cost and light VC money on fire to survive long enough to gain market share” phase. What happens when the VC money dries up and AI companies have to double their prices (or more) in order to make enough revenue to cover their costs?
People pay real money for smartphones.
People pay real Money for AIaaS as well…
Hope?
Just put another number behind it. Luddites won’t know the difference.
yep Knew ai should die some day.
Until Open AI announces a new 5t model or something and then the hype refreshes
Sigh I hope LLMs get dropped from the AI bandwagon because I do think they have some really cool use cases and love just running my little local models. Cut government spending like a madman, write the next great American novel, or eliminate actual jobs are not those use cases.
I am so tired of the ai hype and hate. Please give me my gen art interest back please just make it obscure again to program art I beg of you
It’s still quite obscure to actually mess with AI art instead of just throwing prompts at it, resulting in slop of varying quality levels. And I don’t mean controlnet, but github repos with comfyui plugins with little explanation but a link to a paper, or “this is absolutely mathematically unsound but fun to mess with”. Messing with stuff other than conditioning or mere model selection.
I know, it’s actually still a beautiful community but much harder to talk to outsiders about
so long, see you all in the next hype. Any guesses?
AI vagina Fleshlight beds. You just find your sleep inside one and it will do you all night long! Telling you stories of any topic. Massaging you in every possible way. Playing your favorite music. It’s like a living room! Oh I’m sleeping in the living room again. Yeah I’m in the dog house. But that’s why you need an AI vagina Fleshlight bed!
Get a few more hours of sleep
I woke up at 4 this morning. The fridge made a big ice maker noise that sounded like a door getting slammed. Anyway here I am shit posting and reading shit posts.
Nice, looking forward to it! So much money and time wasted on pipe dreams and hype. We need to get back to some actually useful innovation.
