Between the Booms: AI in Winter – Communications of the ACM
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Isn't it enough that clueless marketers who get their Tech knowledge from businessinsider and bloomberg are constantly harping on about AI.
Seems we as a community have resigned or given up in this battle against common sense. Maybe long ago. Still there should be some form of moderation penalizing these shill posts that only glorify AI as being the future, ... the same way that not everything about crypto or the blockchain ended up on the FP. Seems with AI we're looking the other way and are OK with it?
Or maybe it's me.
Outside of pure tech companies, there's a lot of "Head of AI" hiring by CTOs to show "we are doing AI" regardless of if they have found any application for it yet.
I've also seen a lot of product pivots to AI where they don't really have a need or explanation for the use case that AI helps with.
Further I've seen a number of orgs that were laggards in their internal technology become incredibly distracted thinking AI will solve for them not having even a proper rudimentary 2010s class IT org.
I think the comedown from this will be worse than crypto as while there will be more real use cases, there is far more hype based "we have to do something" adoption that hasn't found a use yet. A lot of orgs that remained weary of crypto got fully on the AI bandwagon. Investment must be an order of magnitude more.
With this kind of thinking often comes being a laggard in technology as you put it - engineers are a "forced necessary cost" because competitors are forcing us to keep up; not because we actually value it.
AI in their minds has vindicated their thinking hence the excitement about it. As a product it is very easy to "sell/fluff" to these kinds of people; it really excites them. They think engineers are now the expendable people they always wanted them to be rather than the people they had to put up with to get what they wanted. They were now justified in being "laggards" - they now have AI to do it cheaper than they would of had to pay an engineer before.
Yes there's a lot wrong with the thinking above, overestimation of current capabilities, etc and real innovative growth leading companies don't think this way. But the decision makers in these companies don't have that perspective. Much of technology trends, corporate hype is around things you can sell to these decision makers who often overpay for the wrong kind of technologies if you sell to them right (think typical RFQ/RFP corporate processes) - AI is an easy sell/dream to these people.
Of course they probably aren't thinking through how AI will allow their leading competitors to maintain or expand their lead if it is any good anyway.
Interestingly I was in a meeting with our firms IT org recently where they were describing some of the "upgrades" they are making across systems, some of which were going to degrade service. Upon enough prodding they conceded the reasoning was not value, or even cost, but cost attribution. That is, it was too hard to figure out how to meter usage & charge back to business lines, so they are essentially going to discontinue those services and make business lines self manage. Crazy.
Isn't this true of every boom? Like A.C. Clarke said, you find the limits of the possible by venturing into the impossible.
This feels way more like the 90s IT offshoring wave where it was forced bluntly, top down because they thought it would save money.
Things like crypto or cloud or big data had a much longer and measured adoption cycle.
The AI discussions can indeed be repetitive and tiresome here, especially for regulars, but they already seem to be downweighted and clear off the front page quite fast.
But it's a major focus of the industry right now, involving a genuinely novel and promising new class of tools, so the posts belong here and the high engagement that props them up seems expected.
Not just him.
> But it's a major focus of the industry right now, involving a genuinely novel and promising new class of tools, so the posts belong here and the high engagement that props them up seems expected.
In your opinion (and admittedly others), but that doesn't make the overhype any less tiresome. Yes it is novel technology, but there's alway novel technology, and it isn't all in one area, but you wouldn't know it by what hits the front page these days.
Anyway, it's useless to shake fists at the clouds. This hype will pass, just like all the others before it, and the discussion can again be proportional to the relevance of the topic.
I use Claude and Chatgpt EVERY DAY.
Those services help me run out scripts for data munging, etc etc very quickly. I don't use it for high expertise writing, as I find it takes more than I get back, but I do use it to put words on a page for more general things. If your deep expertise is programming, you may not use it much either for that. But man oh man has it magnified my output on the constellation of things I need to get done.
What other innovation in the last decade has been this disruptive? Two years ago, I didn't use this. Now I do as part of my regular routine, and I am more valuable for it. So yes, there is hype, but man oh man, is the hype deserved. Even if AI winter started right now, the productivity boom from Claude level LLMs is nothing short of huge.
We use several tools derived from "AI research" every single day in our lives.
They are tools and, at every cycle, we gain new tools. They hype is the issue.
I think the issue is whether you think that HN posts on AI are basically marketing, or about sharing new advances with a community that needs to be kept on top of new advances. Some posts are from a small startup trying something, or from a person sharing a tool. I think these are generally valuable. I might benefit from a RAG, but won't build one from scratch. In terms of this crowd, I can't think of advances that in other areas that are as impactful as machine learning lately. Its not like crypto. Crypto was an interesting innovation, but one in which mostly sought a market instead of the a market seeking an innovation. There is no solid "just use a database" analogical response here like was the well used refrain to attempt at practical uses of cryptocurrency tech. Sure, AI companies built on selling something silly like "the perfect algorithm to find you a perfect date!" is pure hackery, but even at the current level of llm, I don't think we are any where near understanding its full potential/application. So even if we are on the brink of an AI winter, its in the Bahamas.
Also, looking at the most popular stories with AI in the title over the last month show quite a varied array of topics. https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=fa...
If HN readers feel that AI-related articles are showing up too much, then I'd say it would be on them to find articles on topics that interest them and post them to HN.
I use some sort of IDE everyday. Previously at my early days, I was a “true-hacker” and using Vim in console to type out massive code bases, we had waterfall development practices, I would fumble through source codes of various poorly documented features of the language or libraries for hours to figure out about needed function/method/attribute and how anything really worked and the quirks of strange error messages needing to call up the vendor or buy a book on the topic and hope it had answers… and of course, I practiced typing every weekend to speed up my typing speed.
Now, I just type something and the IDE reads my mind and shows appropriate suggestions and also helpfully imports the packages for me while also constantly formatting my codebase on save and raising red/yellow squigglies to suggest my mistakes. I copy paste any quirky errors in a search engine and immediately find other human beings reporting the problem and solutions, I can happily continue developing on the same codebase and parallel features while other teams can continue with their features and we’ll know soon if we have stepped on each others’ toes shortly in CI pipeline. What took me weeks now takes like few hours and if someone told me to do the same in Vim, I’d be blankly looking at them because that is arcane. Of course my IDE misguesses sometimes and I can correct it, but I am insanely productive now compared to decades back. What other innovation has made this kind of gains?
Also I could take a horse and go to a duty travel in another continent for a several month or even year journey, but now I can take a flight and be there in hour and I am saving insane amount of time.
The examples can go on, we have new novelties which are ground breaking, but AI is too much hype, and it is not well deserved. All the hype comes because the VC money burning on it and needs the prep the market for massive return. Too much of hype can turn sour if that topic had been seen to rise and die a fee times, hence it is natural that a lot of HN audience do not feel great to look at this anymore.
> The examples can go on
Since the examples never started not sure how they could go on.
I don't doubt that you are more productive with an IDE than without, but I personally think the magnitude is reflective of poor language and system design rather than the magic of IDEs (which I believe is relatively minor compared to using a fast compiler with good error reporting). In fact, I sort of think IDEs lead to a kind of trap where people design systems that require their use to be effective which then makes it seem as though the features of the IDE are essential rather than perhaps a source of complexity that is actually making the system worse.
I also will say that your horse vs flight example raises something for me. It's a bit like saying I could drive the Camino de Santiago in a day which saves me an insane amount of time. Sure, it's true, but it misses the entire point of the journey. I basically think the vast majority of programming efficiency boosting tools (ides and llms alike) are mainly just taking us faster on a road to nowhere. I live in San Francisco, supposedly the mecca of technology, and almost never encounter anyone working on anything of truly significant value (according to my personal value system). But I do find a lot of people slinging code for cash, which is a fine and understandable choice, but deeply uninspiring to me. Which also reflects how I feel about LLMs and the like.
I disagree.
One of my biggest irritations with HN comment sections is how frequently people seem to want to ignore the specific interesting thing an article is about and just express uninteresting and repetitive generic opinions about the general topic area instead.
CACM was totally complicit in spreading the blockchain hype: https://cacm.acm.org/?s=blockchain
That said, I'm not hating the player, people gotta eat. But I totally lack appreciation for the game.
AI is really neat. I don’t understand how a business model that makes money pops out on the other end.
At least crypto cashed out on NFTs for a while.
Tractors and farming.
By turning what is traditionally a labour intensive product into a capital intensive one.
For now, the farmers who own tractors will beat the farmers who need to hire, house and retain workers (or half a dozen children).
This goes well for quite some time, where you can have 3 people handle acres & acres.
I'll be around explaining how coffee beans can't be picked by a tractor or how vanilla can't be pollinated with it.
Capital intensive industries require low crime and geopolitical stability. Strongman politics means that investors who buy such equipment will simply be robbed at literal gunpoint by local gangs.
Edit: Also, 3 people can handle 100 acres of land, given the crop. That happens today.
Edit: Crop-type was specified, I was incorrect.
What issues do you see?
I pay for ChatGPT and for cursor and to me that's money very well spent.
I imagine tools like cursor will become common for other text intensive industries, like law, soon.
Agreed that the hype can be over the top, but these are valuable productivity tools, so I have some trouble understanding where you're coming from.
[1]: https://www.fooddive.com/news/sprig-is-the-latest-meal-deliv...
[2]:https://techcrunch.com/2019/01/21/munchery-shuts-down/?gucco...
Does that aspect differ from this other emerging market?
It seems with crypto the business "benefits" were mostly adversarial (winners were those doing crimes on the darknet, or to allow ransomware operators to get paid). The underlying blockchain Tech itself though failed to replace transactions in a database.
The main value for AI today seems to be generative Tech to improve the quality of Deepfakes or to help everyone in Business write their communication with an even more "neutral" non-human like voice, free of any emotion, almost psychopathic. Like the dudes who are writing about their achievements on LinkedIn in 3rd person, ... Only now it's psychopathy enabled by the machine.
Also I've seen people who, without AI are barely literate, are now sending emails that look like they've been penned by a post-doc in English literature. The result is it's becoming a lot harder to separate the morons, and knuckle-draggers from those who are worth reaching out and talking to.
yes old man yelling at cloud.
Also, given the saturation of STEM graduates now, you have proven group of juniors who can learn themselves over expensive lottery of bootcampers who might bail out the moment it is no longer the surface level React anymore.
With AI, more tiny businesses can launch into market and hire juniors and part time expertise to guide the product slowly without the massive VC money requirement.
On a quick count it seems to be more like 1/10. Maybe just ignore them and read something else?
I'm interested in the AI stuff personally.
Now, they are good text interfaces. They're good for parsing and creating text. There even seems to be very, very basic thought and maybe even creativity (at a very, very basic level). At this point though, I can't see them improving much more without a major change in technology, techniques, something. The first time I saw them I thought they were just regression analysis on steroids, and not going to lie, they still have that vibe considering tech companies have clusters up to 350k H100s and LLMs still are dumber than the average person for most tasks.
I'm currently creating an app that uses an LLM as an interface and it's definitely interesting, but most of the heavy lifting of the app will be the functions it calls and a knowledge database since it needs to have more concrete and current knowledge. But hey, it's nicer than implementing search from scratch I guess.
2020-2022 HN front page was full of crypto news, mostly in negative light, but still. And before that there was more hot bubble topics. It's very usual.
In the 1980s, AI was a few people at Stanford, a few people at CMU, a few people at MIT, and a scattering of people elsewhere. There were maybe a half dozen startups and none of them got very big.
The industry as a whole was smaller though.
The word sense disambiguation problem did kill a lot of it pretty quickly though.
There were a lot of places that tried a bit of '80s "AI", but didn't accomplish much.
I don't know how that can be dismissed as nothing.
Maybe that's the view from the US. In the '70s, '80s and '90s, ymbolic and logic-based AI flourished in Europe, in the UK and France with seminal work on program verification and model checking, with rich collaborations on logic programming between mainly British and French institutions, in japan with the 5th Generation Computer project, and in Australia with the foundational work of J. Ross Quinlan and others on machine learning, which at the time (late 8'0s and early 90's) meant primarily symbolic approaches, like decision tree learners.
But, as usual, the US thinks progress is only what happens in the US.
I've wondered for a while if Artificial Life is in its own winter, waiting for someone to apply the lessons of scale we learned from neural nets.