AI Hype Is Cooling – New survey
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My 2024 stance is "buy every AI add-on and decide whether to keep it next year"
So our team has access to Enterprise ChatGPT, Gemini, Notion AI, Slack AI, and basically every AI add-on in every SaaS platform that offers it as an upsell (Github Copilot, ReadMe AI, etc).
2024 is the year of "I don't know what the hell these AI tools are going to be useful for, so let's buy them all"
2025 will be the year of "Ok, we spent $xxx on all these AI tools last year, is anyone actually using them?"
I predict we'll be canceling a lot of those subscriptions. Which all in cost us over $100/mo per employee.
You need to be extremely well capitalised and have a good answer about how to compete against the cloud providers as well as OpenAI, Anthropic etc.
That would be 72k USD which is a salary. Admittedly not a software engineer salary, but a significantly above average US salary. Selling the idea of getting another employee is a big deal for most businesses of 30 people.
like, it's a rounding error as IT budgets go, but throwing a bunch of money at something that's already considered dubious is silly. That's 36k in bonuses for Juniors, or a X-Mas party, licenses for software that you'll actually use.
2025 is the pick the winners and drop the losers.
And use money for a different experiment.
Investor pitches are the other way round - all we are going to grow 50x, no we're going to have layoffs.
I wouldn’t trust that everyone correctly opts out. If they don’t, the X months from now “tell me about Foo company’s strategic plans” could regurgitate their internal docs.
And as far as strategic plans, I don't think it regurgitates novel, one source information does it? Isn't the regurgitation more like boilerplate, seen many times type stuff?
Has anyone actually been able to prompt a password out of an LLM? That kind of thing should be ignored because it's high entropy and rare afaik. For example, my name is bongodongobob and my password=hunter17. Do you really think someone will be able to pull this fact out of an LLM at some point? That doesn't seem to be the way they work as I understand it.
https://chatgpt.com/share/673431d5-b278-8004-ad16-10529788f5...
are already stored on someone else's computer already, at 99% of organizations. Every cloud offering comes with business data privacy guarantees.
Most training data is synthetic now.
I just saw a mention about how a homework help company called Chegg has had their stock drop 99% because everyone is just using ChatGPT.
They were a real functioning company, with hundreds or thousands of employees and contractors. All of whom are basically going to be laid off because some company burned through a bunch of VC money to lure everyone away with “the new thing“.
All the artists who lost jobs or commissions. All the companies who ended up wasting a ton of time trying to build AI or integrate AI features that aren’t actually useful. And maybe they’ll end up in a product in two years and by then no one will care or want them.
All the electricity, the silicon, the water for cooling, the new data center is being built that won’t be needed.
Just tons and tons of waste everywhere.
ChatGPT is neat. For all we know we’re near a local maxima of what we’re capable of achieving without another completely new approach that will take 10 or 15 years to figure out. There’s no proof that the acceleration and capabilities we’ve seen over the last 2 to 3 years will continue like that.
I know my company has been asked about adding AI into The main product I work on. I don’t see any benefit. I’ve been told when they ask the customers what it would do for them, they can’t say either. But they seem to have been trained to ask for it by the hype.
Remind me of all the nonsense about chat bots being integrated into every company’s webpage five or six years ago. They’re not helpful. But they were the thing.
ChatGPT has some uses, but is also way more expensive/wasteful.
I hope the hype moves on fast. I’d like this stuff that shakes out to stick around but what’s going on right now is just way too wasteful for my taste.
Feels like almost everyone is trying to build the biggest Z-Ray they can because they’ve been told it’s an amazing discover. No one actually knows what it is, or how to build one, but that hasn’t stopped trillions of dollars from being poured into it. And if we get there, it may not be worth anywhere near what was paid.
I’m sure there are plenty of good places that were destroyed. I just don’t have verifiable anecdotes for any others at hand.
They had no real original content of their own, just worked solutions to homework problems they pulled from textbooks. They were good at SEO and would appear at the top. You clicked on it because it lied to you: showing you part of the content you wanted. Just enough for the search engine preview. That probably boosted them further, wasting more time by others tricked by the same fake results.
To see the rest of the answer, they wanted you to pay money and hope it was what you wanted. Who would subscribe to that other than students desperate for homework answers?
Then ChatGPT comes in without any of the scammy tactics. Sure, it's often wrong, but so are Chegg and Quora.
Two issues here:
1) we are only about ~10 years into the deep learning boom
2) we've seen deep learning scale with compute over this 10 years, not only over the last 2-3 years.
It could be we've reached the end of the road for NLP, no one really knows. But generally we see breakthroughs in lockstep with big jumps in compute capability (typically, GPU releases, occasionally with architecture changes).
I was listening to the recent interviews with Sam Altman and the Anthropic guy who are familiar with current research and they are very not like that. It's more wow we've got so much to build, AGI in a couple of years. (For it seems to me a rather limited version of AGI - more can code well rather than can fix your plumbing.)
They are CEOs, half the job is public cheerleading.
this will be the new "fusion in 10 years", but with the added downside of expending a small-country's worth of carbon per day while not actually getting us there.
like, of course sam altman is going to talk about how close they are and how they need more money.
Yeah, we don’t know for sure. But it seems like there are signs the easy gains may be over.
One product worked and made money.
The other is (effectively) being dumped on the market by VCs in hopes of being a valuable unicorn.
It may never turn a profit.
My argument is that that VC bet on something that may not work out may have destroyed lots of real jobs. It wasn’t harmless, even if you ignore all the other externalities about resource usage.
It’s not OK in my mind for VC to just stand-up companies that destroy parts of the economy and then go out of business because it turns out they were never profitable in the first place.
It would be insane for that to be considered good economic policy.
Edit: Also, the VCs that are just GPT wrappers deserve to die. The only people it hurts are the investors with more money than sense.
It’s their massive money injections that allows these distortions to happen.
If people had been having to pay for the resources ChatGPT (etc) uses to use it then they wouldn’t have had the deleterious effects they have.
One definition of dumping: “Selling goods at less than their normal price, especially in the export market as a means of securing a monopoly.”
Isn’t that exactly what’s going on? Grow too big to fail fast so you’re the winner and people have to use you?
Is this a real thing that happens? Can you name some historical examples? What is stopping from destroyed businesses from being rebuilt pretty quickly? Uber subsidized taxi rides for millions of people for years, but if Uber went out of business, legacy taxis would come right back. And even if they didn't for X amount of time, X would have to be > the amount of subsidy that was received in the meantime. And if the legacy business was so vulnerable that people were willing to try and replace it with some big matrixes, the replacement company might still escape the local maximum that the previous company was trapped in.
I don’t understand, this seems like the opposite of an example of “hype” causing damage. These customers found a better/cheaper alternative.
There are tons of business that probably went through this.
This is going to happen to so many businesses and industries that a universal basic income will become a necessity if we don't want revolts.
There was value in the market. VCs destroyed it through dumping. And for all we know they’ll give up in a year and we’ll have nothing. No jobs and no existing solution.
On the other hand I think arts and entertainment is where AI will likely still survive scrutiny, as imprecision is tolerated reasonably.
That's a very charitable take on that site. I'd call it a site where people pay money for solutions to assignments they can't be assed to complete themselves.
Because you can no longer be a cheap artist, because you can no longer help students on easy problems en masse, because family businesses no longer need a webmaster.
That's a step in the right direction, maybe even towards UBI.
On growth, I disagree that we reached the plateau already. We won't fundamentally change things but larger context windows, speed, compute and cost? Obviously.
That in itself is a major evolution.
It looks like it is fading out of hype maybe, but that's just like all things. LLMs aren't going anywhere, just like Rails got version 8 out and it's better than ever.
You express a lot of concern that these are just "VC pumped up companies" or something, as if that negates the technology. But it doesn't! The technology has already been developed because of these VC investments, and much of it is public.
Moreover, even if these companies go out of business tomorrow and aren't replaced, having years of consumers paying less money and getting a better product is a good unto itself. Yes, a company that made something inferior went out of business in the process - but if, after the big companies are shut down, there really is somehow no alternative - a new company based on the old method can always start again.
I just don't understand how you can spin as bad the idea that VCs are spending billions on unprofitable companies, meaning that they are spending billions that go straight into either innovation, or consumer's pockets. Who loses out here except for the VCs?
And while I have empathy and respect for people who lose their jobs, companies going out of business is an everyday occurrence. We should wish it only happened because better-for-consumers solutions came along.
> Just tons and tons of waste everywhere.
I worry about this not just for AI, but in general. That's capitalism right there, profit now - who cares later. And I am becoming radicalized against it.
Reminds me of a PG essay about a "Dunning-Kruger pass". [0]
When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers (unless you're also a teenager). Maybe it's a good idea, but you can't trust your judgment about that, so ignore it. There have to be other ideas that involve databases, and whose quality you can judge. Do you find it hard to come up with good ideas involving databases? That's because your expertise raises your standards. Your ideas about chat apps are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain.
To some extent we have already developed some filtering against Reddit et al to protect our bayesian priors, but many who lack those filters could suffer greatly from encountering the internet.
The rest of it? Mostly useless.
Do people not use Apple Maps because it came out years after Google Maps?
Don't forget Nvidia...
The former is mostly a parlor trick, while the latter is a massive improvement over Confluence and Sharepoint's search. That's not so much AI win as it is how crappy their built-in search is.
With Crypto it was the idea of micro payments. I want to pay to read news articles, or watch a movie, or tip someone I value online, but I don't want to sign up to some monthly subscription or give over my card details. It seemed to offer a viable alternative to the advertising economy which drives everything now.
With LLMs it was the idea that I no longer have to trawl through marketing websites or endless social media posts to find the nugget of information I'm interested in. As a dev, I shouldn't have to care about responsive designs or tech stacks or accessibility or versions of node libraries, all to provide a website. Instead just pump the data directly to the AI and call it a day.
The 2 concepts could even work together so my "original thoughts" can be monetised so I can be paid royalties for my "art", like musicians are today.
This sounds like, “As a carpenter, I shouldn’t have to care about types of wood, or saws, or cuts, or ergonomics, all to make a chair.”
I've sat on plenty of couches where the person who made it didn't care - so there is probably a world where this makes sense
What if you weren't making a chair, but a hammock. They can both do the same thing, but are very different approaches and requirements.
Same with websites. They are a medium for conveying information. You don't need (traditional) websites or apps to do that. I can even ask for information and receive information completely independently of a website.
The only reason devs need to care about all these things is because of the medium being used.
First, I love that so many are uncomfortable, and that there are limits to the LLM cheating frenzy.
Second, I wonder whether there are additional big reasons (perhaps conflated with the above reasons):
* Not wanting to be seen as performing low quality work.
* Not wanting to suggest that their job can be replaced by AI tools.
* Not wanting to get caught leaking company IP or client/customer/partner data to various services.
* Not wanting to attract attention to possible copyright infringement or plagiarism scandal by LLM or other model (whether the company has rules about that, or not).
Guess how you'll be seen when you get called out for pretending an AI hallucination was your own work. I've seen it happen a few times already.
My company was recently offered a $5k/mo package that would "supercharge our sales with AI." I don't think the presenter had anything material to offer besides some very basic workflow integrations that anyone who is using AI in their day to day has (mostly) already identified.
Zoom at least has had this feature for a while on enterprise plans.
Here:https://the-decoder.com/openais-new-orion-model-reportedly-s...
IMO, the "Find Out" is at least 1-2 years away.
Exactly what we've all been wanting.
I hope you don’t pay for that service, you could train and run it yourself in… a week?
Not a foundational model nor a coding helper.
- Language translation: is, in general, much better with the ML models than prior automated attempts.
- Internal search tools (GPT + all your internal docs, private)
- Voice-to-text transcription in lots of medical and medical adjacent fields. HN tends to be skeptical of this ("It's going to hallucinate diagnoses!"), but it has a lower error rate than traditional speech rec and human transcription. I met someone who built their own no-code speech to text for their partner's veterinary practice and saved them an hour a day of notetaking.
There's a bunch of businesses in all these areas.
the actual hard part of this which is searching for relevant stuff to feed the LLM, which it just formulates into a readable stuff has been around for years. vector databases have been around forever.
Alexa in the home is much better now than it used to be, but still way worse than voice chat with ChatGPT.
If it's not grounded in the right, updated contexts or provided tools to interact with the apps a user cares about... it's a glorified chatbot.
I expect what we'll see in the next 5 years for enterprise adoption is progress on both those fronts.
And by progress, I mean "supports interactions with that VB 6 app that's still a critical piece of a company's workflow." (Or SAP, Salesforce, Epic, etc.)
I think people affected, which is most of us, are really hurting and want this to be true.
Which means just like the last ML/AI/DS hype cycles we will be going through a winter until the next research breakthrough is invented.
[1] https://www.reddit.com/r/singularity/comments/1go6dq1/a_leak...
The orion model underperformed expectations by a lot, and even fell beh8nd chatgpt-4 in programing tasks.