'Overhyped' generative AI will get a 'cold shower' in 2024, analysts predict

https://www.cnbc.com/2023/10/10/generative-ai-will-get-a-cold-shower-in-2024-analysts-predict.html

by kylebenzle • 3 years ago

19 28 3 years ago

kylebenzle• 3 years ago

CCS Insight predicts a reality check for generative AI in 2024 due to increasing costs and complexity. The hype around this technology is expected to be replaced by a more sober understanding of the challenges it presents, particularly for smaller developers. Additionally, AI regulation in the EU is predicted to stall due to rapid technological advances

paulddraper• 3 years ago

That hasn't been my perception

DesertVarnish• 3 years ago

They really aren't the same.

Crypto didn't and still doesn't have the same immediate utility. The value proposition just wasn't there to justify the money and attention it was getting. Bitcoin in particular was a prototype that got mythologized into being "digital gold" despite it's many, many technical limitations.

Diffusion models and LLMs work today and make possible things that were science fiction five years ago, and have shown tremendous and exciting progress in the past 18 months.

ok_dad4• 3 years ago

Your last paragraph is the hype.

I haven’t seen any effective uses of the current AI tech that couldn’t have been done for the same cost by humans so far. Images, text, code; I haven’t seen anything but toys built yet. The coding tools might work okay for your average HTTP API, but it’s not going to develop novel algorithms to control building HVAC systems to reduce energy or demand, for example. It’s not going to code much more efficient search algorithms, or faster compression. Maybe someday, but so far everything produced by AI seems to have huge problems, whether it be drawing realistic hands, knowing the factual truth of certain questions, or introducing subtle bugs in complex code.

nabla9• 3 years ago

One of the best uses of generative AI is Gihub Copilot. Microsoft loses $20 per month for each Github Copilot user. Copilot should cost $40 - $50 per month to cover the cost of running it.

wokwokwok• 3 years ago

Yeah, this.

The tech is great, but it’s expensive to run, and it’s being given away basically for free at the moment.

…and hey, free stuff is great. Enjoy it while you can!

At some point, however, companies have to stop giving things away for free (or at a loss); it’s just a matter of what that looks like under sustainable pricing.

Closi• 3 years ago

Subsidise now, profit later.

If you have the cash, it’s probably better to burn some getting early user adoption if you believe the cost base will reduce in the future.

Inference costs are dropping fast, so you might as well subsidise now and get market share if you think future costs will drop below future revenue.

User aquisition will be much harder later when you lose first mover advantage.

mouzogu• 3 years ago

"pay us $40 - $50 a month to train your future replacement"

faeriechangling• 3 years ago

Overhyped how? Overhyped like self-driving, in terms of the timelines? Or overhyped in terms of the eventual societal impact?

I think people seriously underestimate how much of a struggle driving down the cost of compute/$ is going to be. Every incremental gain in memory and microprocessors is getting exponentially more expensive to develop. This is also a (relatively) high interest rate environment which do not tend to favour long term speculative investments. A lot of people aren't fully aware of how OpenAI and GitHub CoPilot are bleeding red ink from the get-go.

I honestly feel like people are really sleeping on the potential still. Most people I know tried it a few times around last Christmas and got bored with it and quit but I never stopped using it.

brucethemoose22• 3 years ago

struggle driving down the cost of compute/$

Actually I feel that utilization of existing hardware is very poor.

For instance, in LLM land, continuous batching is a thing that just starting to proliferate (at least in open source). Many are still doing training/inference in vanilla pipes in PyTorch eager mode, without even a simple `torch.compile` or aggressive quantization, much less a more advanced ML compiler. Architecture optimizations beyond llama's base architecture (like newer attention schemes used during training) are not really picked up yet.

I can go on and on, and go on about Stable Diffusion as well, but what I am saying is there is tons of unpicked low hanging fruit, that's unexploited because... everyone is in a rush to just publish or deploy something, I guess?

Also, Nvidia's margins are insane. The voltage/clock band they run in is insanely inefficient. I hope that is not sustainable, because sane margins/clocks with no code/hardware advancement would bring costs down a ton.

npsomaratna2• 3 years ago

Can you explain more about the voltage/clock band please? Do you mean that they are very energy inefficient?

tomohelix3• 3 years ago

Well, this was already pointed out a long time ago during the peak hype of AI earlier this year. Something about we overhype the effect of the technology in the short term and underestimate the impact long term.

One thing that is undeniable is that AIs have actual productive use cases. Some of the previous fads did not actually have any major real applications even years after its introduction. Meanwhile, AI technology, specifically the transformer tech, has already revolutionized biotech, art, and NLP fields. Even if all progress on AI hit a stop today, people will still use alphafold, diffusion, and chatgpt for their intended purposes. So I am sure we can agree that AI isn't going down the road of things like NFT or bitcoins.

Next few years would be the optimization and mass adoption steps. Big tech companies are probably plucking all the low hanging fruit already. The hard parts are probably what make it more useful, i.e. cheaper and in a format that can be used easily. Those take time, but 15 years ago, I would be dreaming if I think I can play Crysis on a handheld device. Now I can for a measly $400. So in the next 10 years, it isn't impossible to have something on the level of chatgpt running in real time on something like a phone or smartglass.

And that is discounting the possibility of any major breakthrough or genius application like the GUI to computer interface or the iphone to personal computer. Something like that can pop up and change the world as we know it.

az09mugen• 3 years ago

One other thing is worth mentioning, is also the negative impact of AI to take into account. It helps everything to get done easier, but it includes good things and bad things.

Did you see AI is also trained to make pentests ? Or create malwares ? Or a model with almost no restrictions is released in the wild (Mistral) ? Or any other bad stuff I can't imagine ?

Do people even imagine how it can become easy to do evil things ? No, because they're overhyped by AI. Not everyone, but still.

AraceliHarker2• 3 years ago

In the end, it's the same story as automating warehouse delivery, where it turns out that it's actually cheaper to have humans do it. AI is no different. Moreover, the recent restrictions on AI-generated content have caused inconveniences even in ordinary use that is not socially harmful, and expectations for AI have been greatly damaged.

patrickhogan1• 3 years ago

Says the analyst who will be replaced by ChatGPT in 2024.

singularity2001• 3 years ago

Given the results of the latest midjourney version I feel it's even underhyped: https://reddit.com/r/midjourney/s/ODnwsKazlo

I don't know about the valley but where I am people are unexcited about AI, when they should be

'Overhyped' generative AI will get a 'cold shower' in 2024, analysts predict

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