They're throwing billions upon billions into a technology with extremely limited use cases and a novelty, at best. My god, even drones fared better in the long run.
It's ironic how conservative the spending actually is.
Awesome ML papers and ideas come out every week. Low power training/inference optimizations, fundamental changes in the math like bitnet, new attention mechanisms, cool tools to make models more controllable and steerable and grounded. This is all getting funded, right?
No.
Universities and such are seeding and putting out all this research, but the big model trainers holding the purse strings/GPU clusters are not using them. They just keep releasing very similar, mostly bog standard transformers models over and over again, bar a tiny expense for a little experiment here and there. In other words, it’s full corporate: tiny, guaranteed incremental improvements without changing much, and no sharing with each other. It’s hilariously inefficient. And it relies on lies and jawboning from people like Sam Altman.
Deepseek is what happens when a company is smart but resource constrained. An order of magnitude more efficient, and even their architecture was very conservative.
Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed.
So they're not saying the entire industry is a dead end, or even that the newest phase is. They're just saying they don't think this current technology will make AGI when scaled. I think most people agree, including the investors pouring billions into this. They arent betting this will turn to agi, they're betting that they have some application for the current ai. Are some of those applications dead ends, most definitely, are some of them revolutionary, maybe
Thus would be like asking a researcher in the 90s that if they scaled up the bandwidth and computing power of the average internet user would we see a vastly connected media sharing network, they'd probably say no. It took more than a decade of software, cultural and societal development to discover the applications for the internet.
Technology in most cases progresses on a logarithmic scale when innovation isn't prioritized. We've basically reached the plateau of what LLMs can currently do without a breakthrough. They could absorb all the information on the internet and not even come close to what they say it is. These days we're in the "bells and whistles" phase where they add unnecessary bullshit to make it seem new like adding 5 cameras to a phone or adding touchscreens to cars. Things that make something seem fancy by slapping buzzwords and features nobody needs without needing to actually change anything but bump up the price.
I liked generative AI more when it was just a funny novelty and not being advertised to everyone under the false pretenses of being smart and useful. Its architecture is incompatible with actual intelligence, and anyone who thinks otherwise is just fooling themselves. (It does make an alright autocomplete though).
Meanwhile a huge chunk of the software industry is now heavily using this "dead end" technology 👀
I work in a pretty massive tech company (think, the type that frequently acquires other smaller ones and absorbs them)
Everyone I know here is using it. A lot.
However my company also has tonnes of dedicated sessions and paid time to instruct it's employees on how to use it well, and to get good value out of it, abd the pitfalls it can have
So yeah turns out if you teach your employees how to use a tool, they start using it.
I'd say LLMs have made me about 3x as efficient or so at my job.
Imo our current version of ai are too generalized, we add so much information into the ai to make them good at everything it all mixes together into a single grey halucinating slop that the ai ends up being good at nothing.
We need to find ways to specialize ai and give said ai a more consistent and concrete personality to move forward.
The problem is that those companies are monopolies and can raise prices indefinitely to pursue this shitty dream because they got governments in their pockets. Because gov are cloud / microsoft software dependent - literally every country is on this planet - maybe except China / North Korea and Russia. They can like raise prices 10 times in next 10 years and don't give a fuck. Spend 1 trillion on AI and say we're near over and over again and literally nobody can stop them right now.
Current big tech is going to keeping pushing limits and have SM influencers/youtubers market and their consumers picking up the R&D bill. Emotionally I want to say stop innovating but really cut your speed by 75%. We are going to witness an era of optimization and efficiency. Most users just need a Pi 5 16gb, Intel NUC or an Apple air base models. Those are easy 7-10 year computers. No need to rush and get latest and greatest. I’m talking about everything computing in general. One point gaming,more people are waking up realizing they don’t need every new GPU, studios are burnt out, IPs are dying due to no lingering core base to keep franchise up float and consumers can't keep opening their wallets. Hence studios like square enix going to start support all platforms and not do late stage capitalism with going with their own launcher with a store.
It’s over.
I think the first llm that introduces a good personality will be the winner. I don't care if the AI seems deranged and seems to hate all humans to me that's more approachable than a boring AI that constantly insists it's right and ends the conversation.
I want an AI that argues with me and calls me a useless bag of meat when I disagree with it. Basically I want a personality.
LLMs are fundamentally limited, the only interesting application with them is research more or less. There are some practical applications, but those are already being used in industry today, so meh.
Whether or not it's a dead end, is questionable, because scientific research is often met with many a dead end, that's just how it is.
Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed.
In no way does this imply that the "industry is pouring billions into a dead end". AGI isn't even needed for industry applications, just implementing current-level agentic systems will be more than enough to have massive industrial impact.
Worst case scenario, I don't think money spent on supercomputers is the worst way to spend money.
That in itself has brought chip design and development forward.
Not to mention ai is already invaluable with a lot of science research. Invaluable!
The funny thing is with so much money you could probably do lots of great stuff with the existing AI as it is. Instead they put all the money into compute power so that they can overfit their LLMs to look like a human.
Its not a dead end if you replace all big name search engines with this. Then slowly replace real results with your own. Then it accomplishes something.