The winner that deserved to win might turn into the complacent monopoly pf tomorrow. It might vow to Not Be Evil for a while, but the investors will demand that it does whatever it takes to grow.
To take, for example, calculators. I can't find any evidence of a massive influx of hyperbolic articles talking about how the calculator will change everything. With bikes, there were plenty of articles decrying how women would get "bicycle face" but very little in terms of endless coverage about them being miracle technology.
People adopted bikes and calculators and electricity because they were useful. Car manufacturers didn't have to force GPS into vehicles - customers demanded it.
The narrative I'm describing is how hype sometimes (possibly often) fizzles out. My contention is the more a technology is hyped, the less useful it will turn out to be.
Now, excuse me while I ride my Segway into the sunset while drinking a nice can of Prime.
You have gotta stop cherrypicking. The massive influx of hyperbolic articles about how electricity will change everything started in the 19th century. It became a common theme in fiction (including classics like Frankenstein) and became an enormous media hype war, which historians call the War of the Currents.
Yes, electricity was useful. And it had hyperbolic articles talking about how transformative it would be. Like all prognostication, some of those articles were overblown, but, in some ways, they understated the transformative effect electricity would have on human history.
And cars? Did you somehow miss the influx of hyperbolic articles about how cars will change everything? Like, the whole 20th century?
What was your approach to researching the history of media hype? You somehow overlooked the hype around air travel, refrigeration, and antibiotics…?
There was a great deal of hype around the atom changing everything, but electricity was just too slow to see such breathless anticipation takeoff.
200 years ago the was some hype around how electricity caused mussel contractions in dead flesh, but unless you consider Frankenstein part of the hype cycle it really doesn’t compare to how much people hyped social media etc etc.
Public street lights long predated light bulbs as did both indoor and outdoor Gas lighting 1802 vs 1880’s was just a long time. People were burn, grew up, had kids, and become old between the first electric lighting and the first practical electric bulb. People definitely appreciated the improvement to air quality etc, but the tech simply wasn’t that novel. Rural electrification was definitely promoted but not because what it did was some unknown frontier.
Similarly electric motors had a lot of competition, even today there’s people buying pneumatic shop tools.
> unless you consider Frankenstein part of the hype cycle
It absolutely is. Frankenstein is a seminal work of science-fiction horror, and the mysterious power of electricity to change everything is what made it so chilling to its readers in the 19th century.
> it really doesn’t compare to how much people hyped social media
The media is considerably different now from in 1818, thanks, in significant part, to the power of electricity. I assure you, when the electrical telegraph came on the scene, people were hyped.
Of course, much of that hype was on paper printed on printing presses, so it was, in some sense, "incomparable" to the hype possible on cable television, or the hype that's now possible with online social media.
But if your argument is "Yeah, electricity was kinda hyped, but, you know, not all that hyped, so it proves my point that the more the hype, the less the impact," you have some more research to do. Please just Google "War of the Currents" for a minute.
Calculators are a particularly bad example for your case. There was absolutely hyperbole against calculators when they were introduced. [1]
With similar sentiment as well
"They make us dumb"
"Machines doing the thinking for us"
Cars were definitely seen as a fad. More accurately a worse version of a horse [2]
If you looked through your other examples, you'd see the same for those as well.
Some things start as fads, but only time will tell if they gain a place in society.
Truthfully it's too early to tell for AI, but the arguments you're making, calling it a fad already don't stand up to reason
The personal computer, laptops, web browsers, cell phones, smartphones, AJAX/DHTML, digital cameras, SSDs, WiFi, LCD displays, LED lightbulbs. At some point, all of these things were "overhyped" and "didn't live up to the promise." And then they did.
Electricity bros want to put a socket on every wall. That is such a non-starter from a safety POV. It's a fundamentally unsafe technology and it can never be made safe.
To my mind at least, it is different. I lean heavily on AI for both admin and coding tasks. I just filled out a multipage form to determine my alimony payments in Germany. Gemini was an absolute godsend, helping answer questions in, translate to English, draft explanations, emails requesting time extensions to the Jugendamt case worker.
This is super scary stuff for an ADHDer like me.
I have an idea for a programming language based on asymmetric multimethods and whitespace sensitive, Pratt-parsing powered syntax extensibility. Gemini and Claude are going to be instrumental in getting that done in a reasonable amount of time.
My daily todos are now being handled by NanoClaw.
These are already real products, it's not mere hype. Simply no comparison to blockchain or NFTs or the other tech mentioned. Is some of the press on AI overly optimistic? Sure.
But especially for someone who suffers from ADHD (and a lot of debilitating trauma and depression), and can't rely on their (transphobic) family for support -- it's literally the only source of help, however imperfect, which doesn't degrade me for having this affliction. It makes things much less scary and overwhelming, and I honestly don't know where I'd be without it.
Second, asymmetric multimethods give something up: symmetry is a desirable property -- it's more faithful to mathematics, for instance. There's a priori no reason to preference the first argument over the second.
So why do I think they are promising?
1. You're not giving up that much. These are still real multimethods. The papers above show how these can still easily express things like multiplication of a band diagonal matrix with a sparse matrix. The first paper (which focuses purely on binary operators) points out it can handle set membership for arbitrary elements and sets.
2. Fidelity to mathematics is a fine thing, but it behooves us to remember we are designing a programming language. Programmers are already familiar with the notion that the receiver is special -- we even have a nice notation, UFCS, which makes this idea clear. (My language will certainly have UFCS.) So you're not asking the programmer to make a big conceptual leap to understand the mechanics of asymmetric multimethods.
3. The type checking of asymmetric multimethods is vastly simpler than symmetric multimethods. Your algorithm is essentially a sort among the various candidate multimethod instances. For symmetric multimethods, choosing which candidate multimethod "wins" requires PhD level techniques, and the algorithms can explode exponentially with the arity of the function. Not so with asymmetric multimethods: a "winner" can be determined argument by argument, from left to right. It's literally a lexicographical sort, with each step being totally trivial -- which multimethod has a more specific argument at that position (having eliminated all the candidates given the prior argument position). So type checking now has two desirable properties. First, it design principle espoused by Bjarne Stroustroup (my personal language designer "hero"): the compiler implementation should use well-known, straightforward techniques. (This is listed as a reason for choosing a nominal type system in Design And Evolution of C++ -- an excellent and depressing book to read. [Because anything you thought of, Bjarne already thought of in the 80s and 90s.]) Second, this algorithm has no polynomial or exponential explosion: it's fast as hell.
4. Aside from being faster and easier to implement, the asymmetry also "settles" ambiguities which would exist if you adopted symmetric multimethods. This is a real problem in languages, like Julia, with symmetric multimethods. The implementers of that language resort to heuristics, both to avoid undesired ambiguities, and explosions in compile times. I anticipate that library implementers will be able to leverage this facility for disambiguation, in a manner similar to (but not quite the same) as C++ distinguishes between forward and random access iterators using empty marker types as the last argument. So while technically being a disadvantage, I think it will actually be a useful device -- precisely because the type checking mechanism is so predictable.
5. This predictability also makes the job of the programmer easier: they can form an intuition of which candidate method will be selected much more readily in the case of asymmetric multimethods than symmetric ones. You already know the trick the compiler is using: it's just double-dispatch, the trick used for "hit tests" of shapes against each other. Only here, it can be extended to more than two arguments, and of course, the compiler writes the overloads for you. (And it won't actually write overloads, it will do what I said above: form a lexicographical sort over the set of multimethods, and lower this into a set of tables which can be traversed dynamically, or when the types are concrete, the compiler can leverage monomorphize -- the series of "if arg1 extends Tk" etc. is done in the compiler instead of at runtime. (But it's the same data structure.)
6. It's basically impossible to do separate compilation using symmetric multimethods. With asymmetric multimethods, it's trivial. To form an intuition, simply remember that double-dispatch can easily be done using separate compilation. Separate compilation is mentioned as a feature in both the cited papers. This is, in my view, a huge advantage. I admit, this I haven't quite figured out generics will fit into this -- at least if you follow C++'s approach, you'll have to give up some aspects of separate compilation. My bet is that this won't matter so much; the type checking ought to be so much faster that even when a template needs to be instantiated at a callsite, the faster and simpler algorithm will mean the user experience will still be very good -- certainly faster than C++ (which uses a symmetric algorithm for type checking of function overloads).
To go a bit more into my "vision" -- the papers were written during a time when object-orientation was the dominant paradigm. I'd like to relax this somewhat: instead of classes, there will only be structs. And there won't be instance methods, everything will be a multimethods. So instead of the multimethods being "encapsulated" in their classes, they'll be encapsulated in the module in which they're defined. I'll adopt the Python approach where everything is public, so you need to worry about accessibility. Together with UFCS, this means there is no "privileging" of the writer of a library. It's not like in C++ or Java, where only the writer of the library can leverage the succinct dot notation to access frequently used methods. An extension can import a library, write a multimethod providing new functionality, and that can be used -- using the exact same notation as the methods of the library itself. (I always sigh when I read languages, having made the mistake of distinguishing between free functions and instance methods, "fix" the problem that you can only extend a library from the outside using free functions -- which have a less convenient syntax -- by adding yet another type of function, an "extension function. In my language, there are only structs and functions -- it has the same simplicity as Zig and C in this sense, only my functions are multimethods.)
Together with my ideas for how the parser will work, I think this language will offer -- much like Julia -- attractive opportunities to extend libraries -- and compose libraries that weren't designed to work "together".
And yeah, Claude Code and Gemini are going to implement it. Probably in Python first, just for initial testing, and then they'll port it to C++ (or possibly self-host).
"This time is different" has been correct for every major technological shift in history. Electricity was different. Antibiotics were different. Semiconductors were different.
Gen AI reached 39% adoption in two years (internet took 5, PCs took 12). Enterprise spend went from $1.7B to $37B since 2023. Hyperscalers are spending $650B this year on AI infra and are supply-constrained, not demand-constrained. There is no technology in history with these curves.
The real debate isn't whether AI is transformative. It's whether current investment levels are proportionate to the transformation. That's a much harder and more interesting question than reflexively citing a phrase that pattern-matches to past bubbles.
> The real debate isn't whether AI is transformative.
No, the debate is very much whether AI is transformative. You don't get to smuggle your viewpoint as an assumption as if there was consensus on this point. There isn't consensus at all.
The problem is in the middle of such a change it's hard to recognize if this is a real change or if this is another Wankel motor.
Plenty a visual programming language has tried to toot their own horns as being the next transformative change in everything, and they are mostly just obscure DSLs at this point.
The other issue is nobody knows what the future will actually look like and they'll often be wrong with their predictions. For example, with the rise of robotics, plenty of 1950s scifi thought it was just logical that androids and smart mechanic arms would be developed next year. I mean, you can find cartoons where people envisioned smart hands giving people a clean shave. (Sounds like the making of a scifi horror novel :D Sweeney Todd scifi redux)
I think AI is here to stay. At very least it seems to have practical value in software development. That won't be erased anytime soon. Claims beyond that, though, need a lot more evidence to support them. Right now it feels like people just shoving AI into 1000 places hoping that they can find an new industry like software dev.
> Plenty a visual programming language has tried to toot their own horns as being the next transformative change in everything, and they are mostly just obscure DSLs at this point.
But how many of your non-nerdy friends were talking about them, let alone using them daily?
Yeah that's another rub. The current price is basically there in the hopes that in the future they can find revenue streams to maintain their current pace.
But even if the big companies ultimately go belly up, I think the open models are good enough that we'll likely see pretty cheap AI available for a while, even if it's not as good as the STOA when the bankruptcies roll through.
> Gen AI reached 39% adoption in two years (internet took 5, PCs took 12)
You're comparing a service that mostly costs a free account registration and is harder to avoid than to use, with devices that cost thousands of dollars in the early days.
There's another perspective you can see in the comparison with the dot com boom. The web is here to stay, but a lot of ideas from the beginning didn't work out and a lot of companies turned bankrupt.
The original concept of the web, hyperlinked documents originating from high-quality institutions, is pretty much dead. Now we have an application platform that happens to have adopted some similar protocols and is 99% slop
The four technologies I look at are 3D televisions, VR, tablets, and the electric car. 3D televisions and VR have yet to find their moment. Judging tablets by the Apple Newton and electric cars by the EV1, this time is different turns out to be the correct model looking at the iPad and Tesla, but not for 3d televisions or VR (yet). So, it could be, but my time machine is as good as yours (mine goes 1 minute per minute, and only forwards, reverse is broken right now.), so unless you've got money on it, we'll just have to wait and see where it goes.
When I look at LLMs as an interface, I'm reminded of back when speech-to-text first became mainstream. So many promises about how this is the interface for how we'll talk to computers forevermore.
Here we are a few decades later, and we don't see business units using Word's built-in dictation feature to write documents, right? Funny how that tech seems to have barely improved in all that time. And, despite dictation being far faster than typing, it's not used all that often because.. the error rate is still too high for it to be useful, because errors in speech-to-text are fundamentally an unsolvable problem (you can only get so far with background noise filtering and accounting for accents etc).
I see the parallel in how LLM hallucinations are fundamentally an unsolvable component of transformers-based models, and I suspect LLM usage in 20 years will be around the level of speech-to-text today: ubiquitously in the background, you use it here and there to set a timer or talk to a device, but ultimately not useful for any serious work.
I'd say speech to text is unsolvable for a more fundamental reason that it's hard to actually speak out an entire document flawlessly in one take.
Spoken language is very different to written language, which is why for example you can easily tell when an article is transcribing a spoken interview.
I think there is a second reason people still type, and it's relevant to LLMs. Typing forces you to slow down and choose your words. When you want to edit, you are already typing, so it doesn't break the flow. In short, it has a fit to the work that speech-to-text doesn't.
LLMs create a new workflow wherever they are employed. Even if capable, that is not always a more desirable/efficient experience.
Yeah this is exactly my view. We've had several years of work on the tech, and LLMs are just as prone to randomly spitting out garbage as they were the first day. They are not a tool which is fit for any serious work, because you need to be able to rely on your tools. A tool which is sometimes good and sometimes bad is worse than having no tool at all.
Probably. According to the paper, 83.82% of automated commits were already made by algorithmic tools (non-LLM). For the remainder, a three-phase LLM approach was tried, and achieved a success rate of 30%. Based on these numbers, it probably would have been faster, cheaper, and more efficient to just enhance their current strategy rather than screwing around with text generators.
If you're not seeing the hallucinations, I'd assert you're either not using it enough, or (more likely) you don't have enough knowledge in the subject matter to notice when it's hallucinating.
I'm not interested in getting into some argument about who has "more knowledge in the subject matter". I'm genuinely curious: do you think Opus 4.6 hallucinates just as much as GPT-3.5?
I'm curious about the statement that hallucinations are "fundamentally unsolvable". I don't think an AI agent has left a hallucination in my code - by which I mean a reference to something which doesn't exist at all - in many months. I have had great luck driving hallucinations to effectively 0% by using a language with static typechecking, telling LLMs to iterate on type errors until there are none left, and of course having a robust unit and e2e test suite. I mean, sure, I run into other problems -- it does make logic errors at some rate, but those I would hardly categorize the same as hallucinations.
So type errors are not hallucinations in your book, but "a reference to something which doesn't exist at all" is?
In the context of AI most people I know tend to mean wrong output, not just hallucinations in the literal sense of the word or things you cannot catch in an automated way.
My statement is that if your only hallucinations are type errors, that can be solved by simply wrapping the LLM in a harness that says "Please continue working until `yarn run tsc` is clean". Yes, the LLM still hallucinates, but it doesn't affect me, because by the time I see the code, the hallucinations are gone.
This is something I do every day; to be quite honest, it's a fairly mundane use of AI and I don't understand why it's controversial. To give context, I've probably generated somewhere on the order of 100k loc of AI generated code and I can't remember the last time I have seen a hallucination.
ChatGPT 5.2 kept gaslighting me yesterday telling me that LLMs were explainable with Shapley values, and it kept referencing papers which talk about LLMs, and about SHAP, but talk about LLMs being used to explain the SHAP values of other ML models.
I encounter stuff like this every week, I don't know how you don't. I suppose a well-structured codebase in a statically typed language might not provide as much of a surface for hallucinations to present themselves? But like you say, logical problems of course still occur.
>> I don't think an AI agent has left a hallucination in my code
I literally just went on Gemini, latest and best model and asked it "hey can you give me the best prices for 12TB hard drives available with the British retailer CeX?" and it went "sure, I just checked their live stock and here they are:". Every single one was made up. I pointed it out, it said sorry, I just checked again, here they are, definitely 100% correct now. Again, all of them were made up. This repeated a few times, I accused it of lying, then it went "you're right, I don't actually have the ability to check, so I just used products and values closest to what they should have in stock".
So yeah, hallucinations are still very much there and still very much feeding people garbage.
Not to mention I'm a part of multiple FB groups for car enthusiasts and the amount of AI misinformation that we have to correct daily is just staggering. I'm not talking political stuff - just people copy pasting responses from AI which confidently state that feature X exists or works in a certain way, where in reality it has never existed at all.
The hype around AI is admittedly annoying - especially from the Wall St crowd who don't know how to pronounce 'Nvidia' correctly, and who haven't managed to internalize the fact that the chatbots they use hallucinate.
It really is 'different', though, in the same way the Internet was.
It took about 20 years (ie: since The World ISP) for the Internet to work its way into every facet of life. And the dot com bubble popped half-way through that period of time.
AI might 'underwhelm' for another five or ten years. And then it won't. Whether that's good or bad, I don't know.
The only people underwhelmed by AI in February 2026 are people who have formed an identity around being AI skeptics over the last couple years and are struggling to shed it. I haven't met anyone who has seriously used the new models who isn't a at least a bit awed and disturbed.
That's very true in terms of how capable these chatbots clearly are, but I believe the author was using 'underwhelming' to refer to the societal impact.
So far, life goes on roughly the same as it did five years ago. This can feel 'underwhelming' in contrast to the onslaught of public discussion about, and huge investments in, AI.
Most of us here on HN are programmers, and we all know how radically LLMs have changed our code projects. Even so, the change to our everyday lives (aside from our work or hobby project) is not, just yet, glaringly obvious. This year, it's mainly... every website shoves an AI box on its site that nobody seems to want!
There is also that contrast about it being genuinely useful for work/programming and the fact that, for now, it changes the rest of my life in a negative way - by making PC hardware unavailable, by hearing every day I'll be out of work in 6-24 months, and by having to deal with people taking the information from Chat for granted.
Not true. I'm a really heavy user of AI. And it's improved my productivity dramatically as a developer, but it doesn't work in every situation even in programming. I see it as an indispensible tool, but its not, right now, a tool that will replace me as a programmer or product manager or salesperson, or marketer. or (in my case) an owner and investor.
Will that happen in the future, maybe. but I don't have enough insight into how AI is evolving in the labs to make a judgement on that.
This statment is really annoying and getting boring. There are A LOT of us who have built careers evaluating technology with healthy skepticism, finding where it works and were it doesn't, excited to share & learn - and we've heard "this time it's different" many times. Now because we refuse to jump in without that same nuance and thought, and proclaim "everything's different over night!" we're branded as ludites when we're really trying find a balance.
I don't hear people saying "nothing is going to change", but I do hear questions about the timeline and if the current levels of investment match returns. Branding these people as stuck in some sort of negative identity is bullshit.
in a nutshell: AI - even if transformative and in the future a widely used general-purpose technology - is normal technology. I reject the technological determinism that is being fed to us, especially the idea that AI itself is an agent in defining its own future. I think adoption and the post-adoption spread will be slow & uncertain (relative to the current messaging) regardless of where it ultimately takes us. I think the absolute societal impact is grossly overstated, and the roles of institutions shaping the path underestimated or ignored.
You’re creating a false dichotomy to alienate perceived opponents. Frankly, it’s really annoying and close-minded, and you haven’t contributed anything to the conversation.
Few seem to understand that both of the above can be true. The parallel you draw to the internet revolution is apt; dot-coms were both a bubble and changed everything.
it literally describes the gartnerhype cycle. this article is pointless, the only thing that matters is what survives it with over 1m users. AI will have billions of users when GHC is on the back end.
I think a good analogy will be the way word processors changed printing. Suddenly anyone with access to a computer had the ability to do professional level editing and layout. Most of them didn’t have the taste or skills to use the tools to the fullest, but it still opened up a ton of possibilities that weren’t available before because it was never practical to hire an actual professional to do a poster for a dinky church bake sale before. But now, church bake sales can have pretty slick looking posters (and websites) depending on whether any of the volunteers cares enough to get.
The stuff LLMs will democratize will be a lot more impactful than nice posters for car wash fundraisers though. So in that sense it will be different, but I don’t think it will crack the market for proficient experts in the field in the same way photoshop didn’t destroy graphic design and CAD didn’t destroy drafting. It may get rid of the market for a lot of the second-tier bootcamp grad talent though, so I wouldn’t be getting into that right now if I could help it.
I think this is exactly right. I've been thinking of "this time" as similar to the advent of digital spreadsheets. Spreadsheets existed for thousands of years but spreadsheet programs transformed spreadsheet work that took hours or weeks into seconds. You still had to know what you were doing, and if you knew what you were doing you were easily 10x faster than those that didn't.
I think we are in a similar situation with code generation now, then only difference in my mind is that LLMs come with a massive platform risk. Who's to say that one day anthropic decides my company is too much of a competitor to use their tool (like they've already done with openai) or what if they decide that instead of pulling their product from my use they just make it generate worse code, or even insert malicious payloads. A dependence on these tools is wildly more risky than dependency on a word processor or a spreadsheet program. It reminds me of the arguments around net neutrality and I cannot fathom how people building on top of, and with, these tools do not see the mountain of risks around them.
>Blockchain... NFTs
>The problem is, the same dudes who were pumped for all of that bollocks now won't stop wanging on about Artificial Intelligence.
I was firmly in the camp that blockchain was not a viable solution to any problem, and that NFTs sound stupid. I think AI is much different than that list. So, there goes your argument?
> I was firmly in the camp that blockchain was not a viable solution to any problem, and that NFTs sound stupid. I think AI is much different than that list. So, there goes your argument?
Squares are rectangles. The existence of rectangles that aren't squares doesn't negate that.
You need to re-evaluate your logic here; if you were a Blockchain / NFT booster who doesn't believe AI is different you could argue you've disproved their argument. You have not.
Yeah that comparison doesn't pass the smell test. Blockchain/crypto were purely financial instruments and for better or worse, a new financial instrument is very different than a new tech innovation; tbh there was a thin veneer of tech when it comes to crypto/blockchain, but the magic was because of the money, not because of the tech.
AI is different because the magic clearly is because of the tech. The fact that we get this emergent behavior out of (what essentially amounts to) polynomial fitting is pretty surprising even for the most skeptical of critics.
I think the author is saying that a specific crowd, which happened to be very vocal and excited about web3 and NFTs, is also very vocal and excited about AI. In my personal experience they are right, a lot of the hustler types around me who were trying to get everyone to "invest" in digital land are now doomposting about AI.
It's not a very legible situation for people outside of the profession, and a lot of them believe it's just another grift that will blow up in a few years.
By the looks of it, 2026 might be the year where reality and fiction will finally collide with AI and we'll be able to see if all the hype was warranted.
But like all the previous hype, most of the people that were the loudest won't say they were wrong, and they'll move to the next thing, pretending like they never were the one that portrayed AI as the holy Graal.
There are all sorts of algorithms in use that were once thought of as AI, but transitioned to being mere algorithms well before they entered public awareness, if they did that at all. Some are still useful and used everywhere, but they have never been thought of as AI by the public. For them, AI is a term that has long been reserved for some far-off, sci-fi future.
LLM's are not artificial general intelligence (i.e. not sci-fi AI). Why haven't they transitioned to being mere algorithms by now? Why is the public being told AI is finally arriving when it's really just another algorithm?
We have some truly slick and shady corporations involved in the bubble right now and they're marketing LLM's like tobacco. LLM's have been pushed out, at immense cost, to the public in a way that makes them more directly accessible to average people than any past algorithm. Young children can ask a LLM to do their homework for them. Middle managers can ask a LLM to create a (shitty) ad campaign for them. Corporations have gone to tremendous expense to make that widely available and, for the moment, mostly free. They seem to be following the Joe Camel school of marketing. Get them hooked while they're young so they come to you first when they're older! The only difference is that nobody is stepping in to stop the new Joe Camel from handing out free samples to kids.
Then there's the "go big" aspects of the bubble. The major competitors are trying to out-spend each other to dominance, but the suckers are so colossally big that their bubble is affecting global GPU, memory, and storage prices. This bubble is going to stress power grids wherever it operates and do considerable environmental harm. The financial games being played behind the bubble are absolutely stupid. The results, so far, are tantalizing for billionaires. LLM's offer the promise of being able to fire all their pesky and annoying human workers. It won't deliver on that, and none of these companies is ever going to make enough to pay their debts. There might be "too big to fail" government bailouts, but there are going to be some big bankruptcies too.
Useful algorithms will come out of all this, a lot of tears too, but not "AI".
AI is real but the socio-political environment is far from conductive to some form of productive use of it - as opposed to using it as a war-machine - AI isn't going to fail in that role but very few will be happy about it.
I mean, disillusionment is the least of my worries.
> and we'll be able to see if all the hype was warranted.
Umm, what? For the past 3 years, every year I've said something along the lines of "even if models stop improving now, we'll be working on this for years, finding new ways to use it and make cool stuff happen". The hype is already warranted. To have used these tools and not be hyped is simply denial at this point.
Maybe AI is useful to you, but the US economy is currently buoyed by promises of AI replacing the workforce across the board.
Most of Mag-7 are planning to spend over 500B on capex this year alone on building out datacenters for AI pipelines that have yet to prove that it can generate a sustainable profit. Yes, AI is useful in some environments, but the current pricing is heavily subsidized. So my point stand, the hype is not warranted.
> but the US economy is currently buoyed by promises of AI replacing the workforce across the board.
Still don't understand what's the end goal here. Assuming they don't deliver, then there are billions of investments that will go bust. Assuming they deliver, millions lose their jobs and there's going to be a bloodbath on the streets.
the end goal is productivity growth, aka the point of nearly every technology ever invented. The human story is about how we learn to do more with less.
> Assuming they don't deliver, then there are billions of investments that will go bust. Assuming they deliver, millions lose their jobs and there's going to be a bloodbath on the streets.
There is a third outcome that combines both of these.
LLMs can massively displace the workforce (and cause widespread social instability) AND the companies pouring hundreds of billions into them right now could, at the same time, fail to capture significant amounts of the labor savings value as late-mover alternatives run the race drafting their progress without the massive spend.
I'd honestly be surprised if this double-whammy isn't the outcome at this point. AI is going to have a massive impact on everything, but there is still no moat in sight.
I think our little corner of the world has a distorted view of AI in that it is actually proving useful for us. Once they passed a certain level of usefulness... I remember when they were still struggling just to output syntactically correct code, you know, like, 18 months ago or so... they became a useful tool that we can incorporate.
But there's a lot of things playing out to our advantage. Vast swathes of useful and publicly available training data. The rigorous precision of said data. Vast swathes of data we can feed it as input to our queries from our own codebases. While we never attained the perfect ideal we dreamed of, we have vast quantities of documentation at differing levels of abstraction that the training can compare to the code bases. We've already been arguing in our community about how design patterns were just level of abstraction our coding couldn't capture and AI has access now to all sorts of design patterns we wouldn't have even called design patterns because they still take lots of code to produce, but now for example, if I have a process that I need to parallelize it can pretty much just do it in any of several ways depending on what I need at that point.
It is easy to get too overexcited about what it can do and I suspect we're going to see an absolute flood of "We let AI into our code base and it has absolutely shredded it and now even the most expensive AI can't do anything with it anymore" in, oh, 3 to 6 months. Not that everyone is going to have that experience, but I think we're going to see it. Right now we're still at the phase where people call you crazy for that and insist it must have been you using the tool wrong. But it is clearly an amazing tool for all sorts of uses.
Nevertheless, despite my own experiences, I persist in believing there is an AI bubble, because while AI may replace vast swathes of the work force in 5-20 years, for quite a lot of the workforce, it is not ready to do it right this very instant like the pricing on Wall Street is assuming. They don't have gigabytes of high-quality training data to pour in to their system. They don't have rigorous syntax rules to incorporate into the training data. They don't have any equivalent of being guided by tests to keep things on the rails. They don't have large piles of professionally developed documentation that can be cross-checked directly against the implementation. It's going to be a slower, longer process. As with the dot-com bubble, it isn't that it isn't going to change the world, it is simply that it isn't going to change the world quite that fast.
Leaving aside the economic shitshow and other things.
I think you're right but for the wrong reasons wrt sustainable profit.
Specifically, overcounting how much it will cost in 5 years to run AI because you're extrapolating current high prices, and at the same time undercounting how the demand will drive efficiency gains.
i think the point is AI has to go much further and faster than it has in the past 3 years to justify the investments being made from the hype. The hype did its job now the AI industry has to execute and create the returns they promised. That is still very much up in the air, if they can't then the tech was over hyped.
It's high time to stop accumulating debt while providing free picture of pelicycles, just charge the full cost for them - enough to generate profits and pay back debt.
What we see now is literally burning money and energy to generate hype. The only true measures of success are financial and macroeconomic. If the hype is real, there should be no problem for the mighty AI to generate debt-free profits for its providers while the overall price level in the US goes down.
We observe the exact opposite which makes the AI hype act only as market manipulation for capital misallocation.
unlike the old hpc, where we only burned hundreds of millions for machines that were 80% efficient to get a 5 year lead, we are burning hundreds of billions on machines that are 30% efficient to get a 1 year lead.
> most of the people that were the loudest won't say they were wrong
I was so expecting to find this wind-up aimed at those peddling the "AI is hype" laziness.
It's laziness because they have little CS fundamentals to base such claims on, and the deductions can be made, just not clearly to people who need to study a lot more.
It's like watching an invisible train (visible to those with strong CS) rolling down the tracks at a leisurely pace. Those sitting in their stalled car on the tracks are busy tweeting about "AI HPY PE TRAIN." Until it wrecks their car, the gimmick is free oxygen. It's a lot easier to write articles than it is to build GPUs and write programs.
> It's laziness because they have little CS fundamentals to base such claims on
So, what CS fundamentals do you need to evaluate if AI is the real thing, or will disappoint in the future? Until a few months ago, coding agents were met with skepticism, until Anthropic introduced their new model and, with it, a hype train that cannot be rationally justified. Look, SOTA LLMs, and coding agents in particular, are impressive. However, current predictions about the future of software development (and the world in general) are speculative. There is little to no data showing whether AI can deliver on its promises. How could there be in this short time frame? No one knows what the future will hold, no one knows how coding agents will be integrated into our work life and everyday life in the long run, or what hard limitations they will reveal. No one can tell you how professions will change in the coming years; every prediction is purely speculative, and anyone making prophecies is either trying to cope with the uncertainty themselves or has some stakes in the AI bet. It would be nice if people were actually humble enough to admit that they have no idea what will happen in the future, instead of writing the hundredth doom and gloom post.
> However, current predictions about the future of software development (and the world in general) are speculative.
It's amazing to me how those willing to seize on the speculative nature of any ANY uncertainty cannot recognize the inherent uncertainty of the inverse.
And a lot of exposure to deductive reasoning, vague ideas of automated theorem proving and formalization.
I won't pretend its easy, but let's be clear, a small fraction of people who know things are being forced to entertain the hysteria of a vast majority who are unwilling to know things and just go around beating their chests and will continue doing so until the train hits them.
There are 2-3 minor architectural changes in between now and what I would identify as a completely unbounded AGI with clearly discernible dynamic, self-defined objective functions and self-defined procedures for training and inference. It can be done in megabytes. Oh god. Get me out of this forum. I wish to return to my code editor.
What exactly are you claiming here? That a handful of theorems about the limits of mathematics and provability somehow combine to show that the current LLM-based AI developments will inevitably live up to what is expected of them? And that this is obvious to a select few? That all seems unlikely, to say the least.
I’m doing enterprise coding tasks that used to take a month of whole team coordination from mockups to through development and testing in 3 days now. It’s all test driven development, codex 5.3 and a small team of two people who know how to hold it right orchestrating the agents. There’s no reason not to work this way. The sociotechnical engineering aspects of this change are fascinating and rewarding to solve.
I work for an old enterprise, so far rather conservative with LLM/AI usage. However the copilot cli adoption in the last 2 weeks is spreading light wild fire. Codex 5.3, a good instructions file and it works. Features are getting done and delivered in days, proper test coverage is done, proper documentation in place. Onboarding to it is also very fast.
Porting tons of untyped js legacy front end code to vue with typescript and figma designs. Highly configurable business to business app (i.e lots of permutations). Everyone seems to have a “system”. I recommend looking at the OpenAI Cookbook for long running plans and do TDD to the extreme. https://developers.openai.com/cookbook/articles/codex_exec_p...
Many of my industry friends and I were skeptics about all the things the OP mentions, still am. And yet, I am able to push 30-40K lines of nearly perfect code a day now.
It's different just like the steam engine was different, except technology moves much 100x faster now than it did then. It's different and the same.
The 40k lines of code a day crows are amusing. In solving any problem solvable by code, there's a ratio of non-coding work to coding work, and codex et al all help immensely with the coding work but help less with the non-coding work.
Non-coding work is thinking about the system architecture, thinking about how data should flow, thinking about the problem to be solved, talking with people who will use it, discovering what their objectives are.
Producing 40k lines a code per day simply means you're not doing any of that work: the work that ensures you're building something worth building.
Which is why the result is massive, pointless things that don't do the things people actually need, because you've not taken any time to actually identify the problems worth solving or how to solve them.
It's a form of mania that recalls Kafka's The Burrow, where an underground creature builds and builds an endless series of catacombs without much purpose or coherence. When building becomes so easy when it was so hard -- and when it becomes more fun to build and watch codex's streams of diffs fly by, than to plan -- we forget the purpose of building, and building becomes its own purpose, which is why we usually so little actual productive impact on the world from the "40k lines of code a day" cohort.
Just because tests pass does not mean that they're testing the right thing to begin with. Reviewing tests is as important, if not even more important than reviewing code.
I agree with your point that the original claim is unlikely to be true (and would be extremely foolish behavior even if it were true). I don't think it's good to flame people though, even if they did say something unreasonable.
> "I am able to push 30-40K lines of nearly perfect code a day now."
It is physically and physiologically impossible for anyone to be reviewing "30-40K lines of nearly perfect code a day" to the extent needed to push it with confidence in a sensible development process.
Why do you and many of your industry friends conveniently never actually post their 'perfect code' when asked for proof? I've asked like five different people now that make these claims and they just vanish into the ether.
LLMs have not radically transformed the world yet because the number of people capable of solving problems by typing into a blinking cursor on a blank screen is actually quite small. Take that subset of the population and reduce it to those that can effectively write communicative prose, and its even smaller still.
It's just an interface problem. The VT100 didn't change the world overnight either.
There's another point, too. Detractors say LLMs will never advance to whatever threshold they consider meaningful. Fine. We're working on other paradigms, too, though. Just because a lot of o people are productizing LLMs doesn't mean the state of the art isn't advancing in parallel and AGI isn't in the cards.
Agree, LLMs are just another tool. Treating them as chatbots is a very basic way of using them. The future is intelligent engineers embedding them in traditional systems and having them perform specific roles.
Their Ninebot escooters are pretty damn good, far better than most random brands.
I spent most of Covid in VRChat and met my current live-in gf, so the metaverse was real for me too.
I also made decent money selling crypto, so that part was real for me too.
And AI coding, for as dumb as even the best models are, still enabled me to create things that I wanted to, but wouldn't have had time or gotten nearly as far without.
I dunno if the author realizes, but all the things they mentioned did materialize in one way or another, just not exactly how the hype described it.
Maybe if they could let go of some of the cynicism, they could find something to be optimistic about. Nothing ever goes exactly as planned, but that doesn't mean nothing is good.
> I dunno if the author realizes, but all the things they mentioned did materialize in one way or another, just not exactly how the hype described it.
From the post, which is not a very long one: "All of the above technologies are still chugging along in some form or other (well, OK, not Quibi). Some are vaguely useful and others are propped up by weirdo cultists"
Fair, I read the whole post but I guess that part didn't register, maybe because I never fullheartedly believe marketing fluff to begin with. Maybe this person has too much contact with "AI will fix everything" types, and not enough with actual scientists who are really developing novel methods better than anything before, piece by piece.
I also found the "it's almost always dudes" line a bit strange, because I've seen plenty of women doing marketing for startups running on hype.
But there's a spectrum of responses to these technologies, from knee-jerk cynicism to genuine moral disgust. "Useful" and "good for people/society/humanity" don't always go hand-in-hand, particularly if you take origins and power into account.
The guy who died on one was Jimi Heselden, who was a British entrepreneur who bought the company from the American inventor, Dean Kamen. Dean is alive, however he was recently found to have hung out with the "disgraced financier".
...conveniently doesn't list a bunch of hyped tech that hasn't failed:
> microchips, PCs, the internet, ecommerce, cloud, EVs, 5G
...and presents this as evidence that the current hyped tech (AI) will fail:
> Seems like you say that about every passing fancy - and they all end up being utterly underwhelming.
When the article needs to construct disingenious arguments, I'm not interested in its conclusion.
But wait! If you actually read to the end, there's a plot twist!
> The ideology of "winner takes all" is unsustainable and not supported by reality.
Who said anything about winner takes all? You just burned a "this time is different" straw man and then conclude that "winner takes all" is not realistic?
At this moment I'm wondering if the article was in fact written by a quantized 8B LLM. Surely people don't do such non-sequiturs and then expect to be taken seriously.
But of course not. This is not an argument. This is preaching to the choir.
Exactly! If this post had been written 20 years ago it would have started with
Internet, handheld computers, electric cars...The problem is the same dudes.
Putting beanie babies in with Quantum Computing and Nuclear Power completely ignores the potential life changing elements of some technologies, even if they don't work.
Oh, and smart glasses he put in there, so he'll be eating his words in 2 years.
You may remember this video featuring Facebook with a ridiculously high $15B valuation, Skype, YouTube and other failures: https://m.youtube.com/watch?v=I6IQ_FOCE6I
I’ve never heard half of the things and the other half is mostly consumer electronics or specific product names. The closest example here is Quantum Computing, which is also a serious technology in development. I think for the OP these are all tech buzzwords that he invests in without understanding what they really are. That’s why he thinks all these unrelated things are the same.
I'd say AR & VR were hyped to be as big as AI is now, but just haven't fully delivered on the promise yet. 3D printing was similarly hyped for a time. Same with blockchain. Nuclear power in the 50s was hyped to be the future of energy.
The point is to take the hype with a grain of salt and knowledge that not all hyped technologies transformed the world as promised. Maybe AI is like the internet or electricity. But maybe the claims about AGI/ASI and full automation are just hype.
I always figured AI would be a big deal from childhood onwards and wrote about it for my college entrance exam in 1980 or so. That doesn't apply to any of
"All of the above technologies are still chugging along in some form or other (well, OK, not Quibi). Some are vaguely useful and others are propped up by weirdo cultists. I don't doubt that AI will be a part of the future - but it is obviously just going to be one of many technology which are in use.
> No enemies had ever taken Ankh-Morpork. Well technically they had, quite often; the city welcomed free-spending barbarian invaders, but somehow the puzzled raiders found, after a few days, that they didn't own their horses any more, and within a couple of months they were just another minority group with its own graffiti and food shops.
I get that everyone has a strong opinion on whats-going-to-happen-with-AI, but I really think nobody knows.
We're in that part of turbulence where we don't know if the floating leaf is going to go left or right.
The people who will have the hardest time with this transition are those who go all in on a specific prediction and then discover they were wrong.
If you want to avoid that, you can try very very hard to just not be wrong, but as I said, I don't think that's possible.
Instead, we need to be flexible and surf the wave as it comes. Maybe AI fades away like VR. Or maybe it reshapes the world like the internet/smartphones. The hardest thing to do right now, when everyone is yelling, is to just wait and see what happens. But maybe that's the right thing to do.
[p.s.: None of this means don't try to influence events. If you've got a frontier model you've been working on, please try to steer us safely.]
I got my first tech job in 2001. I've been doing this a while and ridden all the waves.
There are two kinds of waves. The ones that don't require collective belief in them to succeed, and those that do.
The latter are kinds like crypto and social media. The former is mobile...and AI.
If no one else in the world had access to AI except me, I would appear superhuman to everyone in the world. People would see my level of output and be utterly shocked at how I can do so much so quickly. It doesn't matter if others don't use AI for me to appreciate AI. In fact, the more other people don't use AI, the better it works out for me.
I'm sympathetic to people who feel like they are against it on principle because scummy influencers are talking about it, but I don't think they're doing themselves any favors.
Everything is the same until it's not, good luck predicting when "until it's not" is on the horizon though. Isn't technology innovation a power law thing? Everything hums along fairly regular and then, out of the blue, there's a massive impact. Personally, I think AI has made a pretty large impact in software dev and overall tech industry but I don't see AGI any time soon (and that hype has died down) and therefore I don't see the economics working out. The coding tools, API integrations, chatbots, those are great but I don't see them producing the returns required to keep companies like OpenAI running unless OpenAI takes all the customers and all the ad clicks from everyone else ( Athropic, Alhphabet, X, Amazon, Meta, even Microsoft ). I just don't see that happening.
Perhaps this is the failure to understand the distinction between a technology and a meta-technology. Upgrading the factory that builds the robots is much different than upgrading the robots.
A technology is a set of methods and tools for achieving the desired results (generally in a reliable and reproducible way). Or, in a broader sense of the word, it's the idea of applying scientific knowledge to solving practical problems, and the process of such application.
Or (taking the other side) failure to notice the distinction between a technology and a pump-and-dump. The technology (attention/diffusion) is awesome. The hype is unbelievable. Literally.
Actually IT IS different. Actually if they manage to create a viable small nuclear reactors or Quantum computers the world will change like it changed with the Watt thermal engine.
Why he is not talking about the Internet, trains, electricity, nuclear bombs, rockets,aviation or engines? Because they worked, like AI works today.
All of them were bubbles at the time and they changed the world forever. AI is changing the world AND it is a bubble.
AI is here to stay. It will improve and it will have consequences. The fact that a robot could do things with its hands is actually significant, whenever you like it or not.
"Today, I'm speaking with Stephen C. Meyer, Director of The Discovery Institute's Center for Science and Culture, and and George D. Montañez, Director of the AMISTAD Lab at Harvey Mudd College–both of whom are extremely knowledgable on the topic of artificial intelligence. During the course of our conversation, they discuss the asymmetry between human intelligence & AI, the inability of AI to ascribe meaning to raw data, and the limitations of large language models. The real question though is: are we screwed? Let's find out."
Honestly, the remixes this generation suck compared to priors.
"This time will be different," they said about the Metaverse, ignoring the vast tranches of MUCKs, MUDs, MMOs, LSGs, and repeated digital real estate gold rushes of the past half-century. Billions burned on something anyone who played Second Life, Entropia, FFXIV, EQ2, VRChat, or fucking Furcadia could've told you wasn't going to succeed, because it wasn't different, it just had more money behind it this time.
"NFTs are different", as collectors of trading cards, art prints, coins, postage stamps, and an infinite glut of collectibles looked at each other with that knowing, "oh lord, here we go" glance.
"Crypto is different", as those who paid attention to history remembered corporate scrip, gift cards, hedge funds, the S&L crisis, Enron, the MBS crisis, and the multitude of prior currency-related crises and grifts bristled at the impending glut of fraud and abuse by those too risky to engage in traditional commerce.
And thus, here we are again. "This time is different", as those of us who remembered the code generators of yore pollute our floppy drives and salesgrifts convinced our bosses that their program could replace those expensive programmers roll our eyes at the obvious bullshit on naked display, then vomited from stress as over a trillion dollars was diverted from anything of value into their modern equivalent - with all the same problems as before.
I truly hate how stupidly people with money actually behave.
This lazy kind of post annoys me because it sort of groups any of us saying that this technology is profoundly different in with all the town criers who have said this kind of thing before — even if we have never said it before and were even skeptical of past declarations
Effectively, it’s a statement saying nothing can ever be profoundly different, because people have said it before and been wrong.
LLMs are really a marvel, GPT 2 actually inspired me to go back to college (not directly, rather I needed to understand how it worked).
I have unlimited derision for morally spineless worms who disingenuously make it out to be more than it is-- looking at Dario, Sam, and the silly CEO of Control AI. Also, I hate to say it but Andrej Karpathy on twitter-- he's a worthless follow now. I can't blame, but am daily exasperated by media figures who can't help but go with what they hear prominent individuals in the field say.
If I were a junior now, and less confident, I would be abandoning my career in this climate.
LLMs are not going away. They will get a little better than they are now, and new model paradigms will come around at some point. But this tale of massive redundancy and skyrocketing unemployment is not going to come from LLMs.
This is the only reason why I cannot wait for a pop, and pray to God that it comes sooner than later. I just want to feel good about technology again. I want to tinker, to feel positivity, to know how sustainable the tools I'm using actually are.
I don't want to be reminded daily of the disgusting reality of unbridled capitalism.
OP here. Unless you're still watching Quibi on your curved TV, delivered via WiMax then, yeah, I'd say it was pretty bloody substantiated.
I like technology. I made a decent living from it. But if I had chased every hyped fad that was promised as the next big thing, I doubt I'd be as happy as I am now.
You claim to cite 'technologies' but include a few brands and companies for some reason.
The one you keep citing, here and in the article, Quibi, lives on in technology-form (the spirit of your article we must presume) as an 8 billion dollar business in China and is rapidly upending every Hollywood film studio.
So, arguments about substantiation or even 'this time' fall flat in the face of not even understanding your own message.
Just chiming in to say thanks for the Pratchett quote! I dare say he's about to beat out Douglass Adams for my top author. Feets of Clay and Hogfather should be must reads for people dealing with AI right now imo.
You're not really saying anything, though. For every tech hype that has failed, there is another that's changed the world. This IS changing the world and our industry, regardless of whether it reaches the heights of the hypers.
I mean you're just stating that sometimes tech doesn't meet it's hype. What's insightful about that? It's a given; cherry-picking examples doesn't prove your case.
The thing is, the successful tech rarely get the excessive hype.
MRNA vaccines. Where are the countless breathless articles about these literal life saving tech? A few, maybe, but very few dudes pumping out asinine "white papers" and trying to ride the hype train.
Solar and battery. Again, lots of real world impact but remarkably few unhinged blowhards writing endless newsletters about how this changes everything.
I'm struggling to think of a tech from the last 20 years which has lived up to its hype.
Not everything is written to be insightful. Some things are just written to get them out of my head.
I personally see plenty of hype but I've also been following the trends and using the tools "on the ground". At least in terms of software these tools are a substantial shift. Will they replace developers? No idea, but their impacts are likely to be felt for a very long time. Their rate of improvement in programming is growing rapidly.
Do feel AI is overall just hype? When did you last try AI tools and what about their use made you conclude they will likely be forgotten or ignored by the mainstream?
I spent an hour with Gemini this morning trying to get instructions to compile a common open source tool for an uncommon platform.
It was an hour of pasting in error messages and getting back "Aha! Here's the final change you need to make!"
Underwhelming doesn't even begin to describe it.
But, even if I'm wrong, we were told that COBOL would make programming redundant. Then UML was going to accelerate development. Visual programming would mean no more mistakes.
All of them are in the coding mix somewhere, and I suspect LLMs will be.
That's the most recent time. But I've bounced around all the LLMs - they're all superficially amazing. But if you understand their output they often wrong in both subtle and catastrophic ways.
As I said, maybe I'm wrong. I hope you have fun using them.
Yes. And, again, they look amazing and make you feel like you're 10x.
But then I look at the code quality, hideous mistakes, blatant footguns, and misunderstood requirements and realise it is all a sham.
I know, I know. I'm holding it wrong. I need to use another model. I have to write a different Soul.md. I need to have true faith. Just one more pull on the slot machine, that'll fix it.
Why do you think that solar+battery technology or MRNA vaccines haven't been written about in excited, hype-filled ways? If a technology is successful, then looking at past accounts of that technology and why it will change the world don't come across to you reading it now as hype, they come across as a description of something normal about the world.
The web? GLP-1s? 5G? The newton was mega-hyped, failed but Apple came back with the iPhone. All the dot com failures that eventually became viable businesses (so viable in-fact that sfgate has to reach back 26 years to write their stinkpiece [1])
Hype is often early, in 10-20 years we'll start seeing the value as the rest of the world catches up
It's not unsubstantiated though. The claim is "People frequently assert that 'this time is different' and they are almost always wrong" and it proceeded to provide a reasonable list of analogous manias.
This only doesn't feel like substantiation if you reject the notion that these cases are analogous.
"You shouldn't eat that."
"Why not?"
"Everyone else who's eaten it has either died or gotten really sick."
"But I'm different! Why should I listen to your unsubstantiated claims?"
"(lists names of prior victims)"
"That doesn't mean anything. I'm different. You're just making vague and dismissive unsubstantiated claims."
The claim isn't "AI bad" the claim is more along the lines of "there's a lot of money changing hands and this has all the earmarks of a classic hype cycle; while attention/diffusion models may amount to something the claims of their societal impacts are almost certainly being exaggerated by people with a financial stake in keeping the bubble inflated as long as possible, to pull in as many suckers as possible."
If you want another example (which you won't find analogous if you've already drunk the koolaid):
What is the point being made here? Some past technologies were overhyped, therefore AI is overhyped? Well, some past consumer technologies did change the world (smartphones, texting, video streaming, dating apps, online shopping, etc), so where's the argument that AI doesn't belong to this second group?
Also, every single close friend of mine makes some use of LLMs, while none of them used any the overhyped technologies listed. So you need a specially strong argument to group them together.
For all of those, there is a gartner hype cycle. The thing that matters is when it comes out the back end, is 1m, 1b, 6b people using it?
for all the things you listed, less than 1000 people are using it, with AI we're clearly not finished with the gartner hype cycle, but the back end is going to be over a billion users.
If you can't distinguish the actual utility and progress of AI from it's annoying hype-men then it's hard to take your dismissal of AI seriously.
Failure to appreciate changes in AI will have left you calling every shot wrong over the past 5 years. While AI models continue to improve at an exponential rate, you'll cling to your facile maxims like "dude it's just predicting the next token it isn't real intelligence".
I invested in Tesla extremely early (2011) because electric cars, if built correctly, would obviously make great cars, and Elon was one of the few people I actually thought had a shot at doing it.
I was right that blockchain was BS and all the "not sure about Bitcoin, but blockchain will be big" people were idiots.
I've been right for the last couple of years on AI and that people were vastly underestimating it when it came to it's coding potential. And I put my money where my mouth was here. In 2021 when GPT-3 came out I decided almost immediately I needed to invest a significant amount of my net worth in Google simply as hedge against AI destroying knowledge work jobs. Which at the time I thought was probably going to happen around 2030 not realising how far LLMs could go with reasoning.
I'm not particularly intelligent ("only" top 1-2% IQ), but my ability to predict the future is very good. If you have a skill you're unusually good you might relate to how it's strange other people find it so hard to do that thing you find kinda easy. For me that's predicting things and computers.
Since I was a young teen I have been worrying about AI. Most of my IRL best friends I have made from talking about AI risk in 2010s when I was studying AI.
Admittedly I got some of the details wrong back then. In 2010 I thought a lot of manual labour jobs would be easier to automate first – warehouse work, mail, taxis, buses, trains, etc. I worried primarily about the economic and political ramifications, and much less about ASI scenario (at least in this half of the century). But I think still I got the general timeframes and direction right. This was the decade I was concerned about.
I'm so scared right now... My whole life I've had nightmares about AI. I know there are some people who talk about how AI is an existential risk, but it feels like they don't internalise it like I do. They're not prepping like me for one, not that you really can prep for what's coming. If they're concerned why don't they have the nightmares of the omnipresent AI which you can't out think or punch to protect those you love? AI is so powerful in the scariest ways. Super viruses, mass surveillance and control, mind reading, unimaginable sci-fi weapons. It's like a horror story, but suddenly real.
I am an OG AI doomer, but until the last few months I've at least always had some doubt in my mind about whether I'm right, perhaps not about the risk of AI broadly, but about whether we'd actually be able to develop highly capable AIs while I still have a lot of my life ahead of me.
In my opinion this time is different, and what I've been worrying about for the last couple of decades is now here.
We are collectively the indigenous peoples of America and the Europeans have just arrived in the new world. The risk vectors are now endless and how this all plays out is hard to know exactly. What we do know is that the majority of ways this will play out are bad, and some are incomprehensibly bad. Some may achieve status and wealth in the near-term, but longer-term we're all dead, or worse.
I always worry these comments make me sound like a lunatic, I think I am, but I hope I am. I hope you will all forgive me, but I just need to shout about this tonight while I still can. We need to stop this insanity. Data centers need to be nuked. You may doubt me now, but in time you will understand. Hopefully I won't be around to say I told you so. Please make the best of the time we have left.
> I needed to invest a significant amount of my net worth in Google simply as hedge against AI destroying knowledge work jobs
I felt similarly, and did similarly, with both GOOGL and MSFT. I'm not an AI "doomer" in the Yudkowski/LolzWrong sense, but I do think it's quite sad that generative AI is first branch of the AI "tech tree" we raced up. AI art, especially, is tragic.
this just looks like someone hearing about tons of hyped things from people across the internet (which almost by definition, is full of false signals and grifters), imagining they are coming from the same person, then arguing with how wrong that person always is. how is that interesting?
I hoped the article would be be a meta-discussion of "time" and perhaps relativity or some other phenomenon. Sigh, it's an investment thesis saying "This Time is Different" is a risky bet.
Maybe I'm only noticing the times when it messes things up, but it kinda seems like these auto-edits cause a lot of confusion that could be avoided if they were shown up-front to submitters, who would then have the option to undo them.
Or maybe judicious use of an LLM here could be helpful. Replace the auto-edits with a prompt? Ask an LLM to judge whether the auto-edited title still retains its original meaning? Run the old and new titles through an embedding model and make sure they still point in roughly the same direction?
oh interesting, TIL I can go edit my submission titles! That's useful, I've definitely submitted stuff and gotten a less-good title due to the automated fixes, so I'll have to pay attention to this next time
> 3D TV, AMP, Augmented Reality, Beanie Babies, Blockchain, Cartoon Avatars, Curved TVs, Frogans, Hoverboards, iBeacons, Jetpacks, Metaverse, NFTs, Physical Web, Quantum Computing, Quibi, Small and Safe Nuclear Reactors, Smart Glasses, Stadia, WiMAX.
Agreed, these things all failed to live up to the hype.
But these didn't:
Electricity, cheap computing, calculators, photography, the internet, the steam engine, the printing press, tv, cars, gps, bicycles...
So you can't really start an article by picking inventions that fit your narrative and ignoring everything else.
Exactly my thoughts. Selective whinging indeed.
Also meta-platitude whinging like
> The ideology of "winner takes all" is unsustainable and not supported by reality.
Sometimes the winner deserves to win, AND that's a good thing even at scale. It kindof depends.
The winner that deserved to win might turn into the complacent monopoly pf tomorrow. It might vow to Not Be Evil for a while, but the investors will demand that it does whatever it takes to grow.
OP here! Thanks for replying.
To take, for example, calculators. I can't find any evidence of a massive influx of hyperbolic articles talking about how the calculator will change everything. With bikes, there were plenty of articles decrying how women would get "bicycle face" but very little in terms of endless coverage about them being miracle technology.
People adopted bikes and calculators and electricity because they were useful. Car manufacturers didn't have to force GPS into vehicles - customers demanded it.
The narrative I'm describing is how hype sometimes (possibly often) fizzles out. My contention is the more a technology is hyped, the less useful it will turn out to be.
Now, excuse me while I ride my Segway into the sunset while drinking a nice can of Prime.
You have gotta stop cherrypicking. The massive influx of hyperbolic articles about how electricity will change everything started in the 19th century. It became a common theme in fiction (including classics like Frankenstein) and became an enormous media hype war, which historians call the War of the Currents.
Yes, electricity was useful. And it had hyperbolic articles talking about how transformative it would be. Like all prognostication, some of those articles were overblown, but, in some ways, they understated the transformative effect electricity would have on human history.
And cars? Did you somehow miss the influx of hyperbolic articles about how cars will change everything? Like, the whole 20th century?
What was your approach to researching the history of media hype? You somehow overlooked the hype around air travel, refrigeration, and antibiotics…?
There was a great deal of hype around the atom changing everything, but electricity was just too slow to see such breathless anticipation takeoff.
200 years ago the was some hype around how electricity caused mussel contractions in dead flesh, but unless you consider Frankenstein part of the hype cycle it really doesn’t compare to how much people hyped social media etc etc.
Public street lights long predated light bulbs as did both indoor and outdoor Gas lighting 1802 vs 1880’s was just a long time. People were burn, grew up, had kids, and become old between the first electric lighting and the first practical electric bulb. People definitely appreciated the improvement to air quality etc, but the tech simply wasn’t that novel. Rural electrification was definitely promoted but not because what it did was some unknown frontier.
Similarly electric motors had a lot of competition, even today there’s people buying pneumatic shop tools.
> unless you consider Frankenstein part of the hype cycle
It absolutely is. Frankenstein is a seminal work of science-fiction horror, and the mysterious power of electricity to change everything is what made it so chilling to its readers in the 19th century.
> it really doesn’t compare to how much people hyped social media
The media is considerably different now from in 1818, thanks, in significant part, to the power of electricity. I assure you, when the electrical telegraph came on the scene, people were hyped.
Of course, much of that hype was on paper printed on printing presses, so it was, in some sense, "incomparable" to the hype possible on cable television, or the hype that's now possible with online social media.
But if your argument is "Yeah, electricity was kinda hyped, but, you know, not all that hyped, so it proves my point that the more the hype, the less the impact," you have some more research to do. Please just Google "War of the Currents" for a minute.
Calculators are a particularly bad example for your case. There was absolutely hyperbole against calculators when they were introduced. [1]
With similar sentiment as well "They make us dumb" "Machines doing the thinking for us"
Cars were definitely seen as a fad. More accurately a worse version of a horse [2]
If you looked through your other examples, you'd see the same for those as well.
Some things start as fads, but only time will tell if they gain a place in society. Truthfully it's too early to tell for AI, but the arguments you're making, calling it a fad already don't stand up to reason
[1]: https://www.newspapers.com/article/the-item/160697182/ [2]: https://www.saturdayeveningpost.com/2017/01/get-horse-americ...
The personal computer, laptops, web browsers, cell phones, smartphones, AJAX/DHTML, digital cameras, SSDs, WiFi, LCD displays, LED lightbulbs. At some point, all of these things were "overhyped" and "didn't live up to the promise." And then they did.
The first few paragraphs are all you need to see that the author is writing a propaganda piece. It's not meant to be truthful, it's meant to convince.
I think this is what is meant by "bullshit".
The article is trash. The only reason it got voted to the front page is because the author is salty about AI.
Electricity bros want to put a socket on every wall. That is such a non-starter from a safety POV. It's a fundamentally unsafe technology and it can never be made safe.
To my mind at least, it is different. I lean heavily on AI for both admin and coding tasks. I just filled out a multipage form to determine my alimony payments in Germany. Gemini was an absolute godsend, helping answer questions in, translate to English, draft explanations, emails requesting time extensions to the Jugendamt case worker.
This is super scary stuff for an ADHDer like me.
I have an idea for a programming language based on asymmetric multimethods and whitespace sensitive, Pratt-parsing powered syntax extensibility. Gemini and Claude are going to be instrumental in getting that done in a reasonable amount of time.
My daily todos are now being handled by NanoClaw.
These are already real products, it's not mere hype. Simply no comparison to blockchain or NFTs or the other tech mentioned. Is some of the press on AI overly optimistic? Sure.
But especially for someone who suffers from ADHD (and a lot of debilitating trauma and depression), and can't rely on their (transphobic) family for support -- it's literally the only source of help, however imperfect, which doesn't degrade me for having this affliction. It makes things much less scary and overwhelming, and I honestly don't know where I'd be without it.
This comment is scary. You don’t control these technologies, you are growing dependent on stilts that could disappear any moment.
The good thing is that local models are catching up very fast.
What if they’re just good for a while and then you go back to the old way?
Can you elaborate your choice about asymmetric multimethods? I also tinker with my PL and wanted to hear your reasonings and ideas
Sure! First, here are references, in case you want to deep dive:
1. http://lucacardelli.name/Papers/Binary.pdf
2. https://www.researchgate.net/publication/221321423_Parasitic...
Second, asymmetric multimethods give something up: symmetry is a desirable property -- it's more faithful to mathematics, for instance. There's a priori no reason to preference the first argument over the second.
So why do I think they are promising?
1. You're not giving up that much. These are still real multimethods. The papers above show how these can still easily express things like multiplication of a band diagonal matrix with a sparse matrix. The first paper (which focuses purely on binary operators) points out it can handle set membership for arbitrary elements and sets.
2. Fidelity to mathematics is a fine thing, but it behooves us to remember we are designing a programming language. Programmers are already familiar with the notion that the receiver is special -- we even have a nice notation, UFCS, which makes this idea clear. (My language will certainly have UFCS.) So you're not asking the programmer to make a big conceptual leap to understand the mechanics of asymmetric multimethods.
3. The type checking of asymmetric multimethods is vastly simpler than symmetric multimethods. Your algorithm is essentially a sort among the various candidate multimethod instances. For symmetric multimethods, choosing which candidate multimethod "wins" requires PhD level techniques, and the algorithms can explode exponentially with the arity of the function. Not so with asymmetric multimethods: a "winner" can be determined argument by argument, from left to right. It's literally a lexicographical sort, with each step being totally trivial -- which multimethod has a more specific argument at that position (having eliminated all the candidates given the prior argument position). So type checking now has two desirable properties. First, it design principle espoused by Bjarne Stroustroup (my personal language designer "hero"): the compiler implementation should use well-known, straightforward techniques. (This is listed as a reason for choosing a nominal type system in Design And Evolution of C++ -- an excellent and depressing book to read. [Because anything you thought of, Bjarne already thought of in the 80s and 90s.]) Second, this algorithm has no polynomial or exponential explosion: it's fast as hell.
4. Aside from being faster and easier to implement, the asymmetry also "settles" ambiguities which would exist if you adopted symmetric multimethods. This is a real problem in languages, like Julia, with symmetric multimethods. The implementers of that language resort to heuristics, both to avoid undesired ambiguities, and explosions in compile times. I anticipate that library implementers will be able to leverage this facility for disambiguation, in a manner similar to (but not quite the same) as C++ distinguishes between forward and random access iterators using empty marker types as the last argument. So while technically being a disadvantage, I think it will actually be a useful device -- precisely because the type checking mechanism is so predictable.
5. This predictability also makes the job of the programmer easier: they can form an intuition of which candidate method will be selected much more readily in the case of asymmetric multimethods than symmetric ones. You already know the trick the compiler is using: it's just double-dispatch, the trick used for "hit tests" of shapes against each other. Only here, it can be extended to more than two arguments, and of course, the compiler writes the overloads for you. (And it won't actually write overloads, it will do what I said above: form a lexicographical sort over the set of multimethods, and lower this into a set of tables which can be traversed dynamically, or when the types are concrete, the compiler can leverage monomorphize -- the series of "if arg1 extends Tk" etc. is done in the compiler instead of at runtime. (But it's the same data structure.)
6. It's basically impossible to do separate compilation using symmetric multimethods. With asymmetric multimethods, it's trivial. To form an intuition, simply remember that double-dispatch can easily be done using separate compilation. Separate compilation is mentioned as a feature in both the cited papers. This is, in my view, a huge advantage. I admit, this I haven't quite figured out generics will fit into this -- at least if you follow C++'s approach, you'll have to give up some aspects of separate compilation. My bet is that this won't matter so much; the type checking ought to be so much faster that even when a template needs to be instantiated at a callsite, the faster and simpler algorithm will mean the user experience will still be very good -- certainly faster than C++ (which uses a symmetric algorithm for type checking of function overloads).
To go a bit more into my "vision" -- the papers were written during a time when object-orientation was the dominant paradigm. I'd like to relax this somewhat: instead of classes, there will only be structs. And there won't be instance methods, everything will be a multimethods. So instead of the multimethods being "encapsulated" in their classes, they'll be encapsulated in the module in which they're defined. I'll adopt the Python approach where everything is public, so you need to worry about accessibility. Together with UFCS, this means there is no "privileging" of the writer of a library. It's not like in C++ or Java, where only the writer of the library can leverage the succinct dot notation to access frequently used methods. An extension can import a library, write a multimethod providing new functionality, and that can be used -- using the exact same notation as the methods of the library itself. (I always sigh when I read languages, having made the mistake of distinguishing between free functions and instance methods, "fix" the problem that you can only extend a library from the outside using free functions -- which have a less convenient syntax -- by adding yet another type of function, an "extension function. In my language, there are only structs and functions -- it has the same simplicity as Zig and C in this sense, only my functions are multimethods.)
Together with my ideas for how the parser will work, I think this language will offer -- much like Julia -- attractive opportunities to extend libraries -- and compose libraries that weren't designed to work "together".
And yeah, Claude Code and Gemini are going to implement it. Probably in Python first, just for initial testing, and then they'll port it to C++ (or possibly self-host).
"This time is different" has been correct for every major technological shift in history. Electricity was different. Antibiotics were different. Semiconductors were different.
Gen AI reached 39% adoption in two years (internet took 5, PCs took 12). Enterprise spend went from $1.7B to $37B since 2023. Hyperscalers are spending $650B this year on AI infra and are supply-constrained, not demand-constrained. There is no technology in history with these curves.
The real debate isn't whether AI is transformative. It's whether current investment levels are proportionate to the transformation. That's a much harder and more interesting question than reflexively citing a phrase that pattern-matches to past bubbles.
> The real debate isn't whether AI is transformative.
No, the debate is very much whether AI is transformative. You don't get to smuggle your viewpoint as an assumption as if there was consensus on this point. There isn't consensus at all.
No one is smuggling this in. The debate is over. It's transformative. We're in the midst of transformation.
The problem is in the middle of such a change it's hard to recognize if this is a real change or if this is another Wankel motor.
Plenty a visual programming language has tried to toot their own horns as being the next transformative change in everything, and they are mostly just obscure DSLs at this point.
The other issue is nobody knows what the future will actually look like and they'll often be wrong with their predictions. For example, with the rise of robotics, plenty of 1950s scifi thought it was just logical that androids and smart mechanic arms would be developed next year. I mean, you can find cartoons where people envisioned smart hands giving people a clean shave. (Sounds like the making of a scifi horror novel :D Sweeney Todd scifi redux)
I think AI is here to stay. At very least it seems to have practical value in software development. That won't be erased anytime soon. Claims beyond that, though, need a lot more evidence to support them. Right now it feels like people just shoving AI into 1000 places hoping that they can find an new industry like software dev.
> Plenty a visual programming language has tried to toot their own horns as being the next transformative change in everything, and they are mostly just obscure DSLs at this point.
But how many of your non-nerdy friends were talking about them, let alone using them daily?
The practical value is there, if they managed to keep the price at the current levels or lower.
But if they don't and if I have to think twice about how much every request's going to cost, the cost-benefit analysis will look differently fast.
Yeah that's another rub. The current price is basically there in the hopes that in the future they can find revenue streams to maintain their current pace.
But even if the big companies ultimately go belly up, I think the open models are good enough that we'll likely see pretty cheap AI available for a while, even if it's not as good as the STOA when the bankruptcies roll through.
I once owned a Maxda RX2 ... my second car, IIRC. The Wankel motor wasn't revolutionary, but it was pretty good.
> Gen AI reached 39% adoption in two years (internet took 5, PCs took 12)
You're comparing a service that mostly costs a free account registration and is harder to avoid than to use, with devices that cost thousands of dollars in the early days.
There's another perspective you can see in the comparison with the dot com boom. The web is here to stay, but a lot of ideas from the beginning didn't work out and a lot of companies turned bankrupt.
The original concept of the web, hyperlinked documents originating from high-quality institutions, is pretty much dead. Now we have an application platform that happens to have adopted some similar protocols and is 99% slop
> Gen AI reached 39% adoption in two years
Source?
https://www.stlouisfed.org/on-the-economy/2024/sep/rapid-ado...
So about 10%, using it less than once per day means you didn't find it useful for most tasks.
Yeah, what's counting as "adoption" here?
The four technologies I look at are 3D televisions, VR, tablets, and the electric car. 3D televisions and VR have yet to find their moment. Judging tablets by the Apple Newton and electric cars by the EV1, this time is different turns out to be the correct model looking at the iPad and Tesla, but not for 3d televisions or VR (yet). So, it could be, but my time machine is as good as yours (mine goes 1 minute per minute, and only forwards, reverse is broken right now.), so unless you've got money on it, we'll just have to wait and see where it goes.
When I look at LLMs as an interface, I'm reminded of back when speech-to-text first became mainstream. So many promises about how this is the interface for how we'll talk to computers forevermore.
Here we are a few decades later, and we don't see business units using Word's built-in dictation feature to write documents, right? Funny how that tech seems to have barely improved in all that time. And, despite dictation being far faster than typing, it's not used all that often because.. the error rate is still too high for it to be useful, because errors in speech-to-text are fundamentally an unsolvable problem (you can only get so far with background noise filtering and accounting for accents etc).
I see the parallel in how LLM hallucinations are fundamentally an unsolvable component of transformers-based models, and I suspect LLM usage in 20 years will be around the level of speech-to-text today: ubiquitously in the background, you use it here and there to set a timer or talk to a device, but ultimately not useful for any serious work.
I'd say speech to text is unsolvable for a more fundamental reason that it's hard to actually speak out an entire document flawlessly in one take.
Spoken language is very different to written language, which is why for example you can easily tell when an article is transcribing a spoken interview.
I type faster than I think, and being able to edit gives the edge over text to speech. I don't believe this is a fundamentally comparable analogy.
I think there is a second reason people still type, and it's relevant to LLMs. Typing forces you to slow down and choose your words. When you want to edit, you are already typing, so it doesn't break the flow. In short, it has a fit to the work that speech-to-text doesn't.
LLMs create a new workflow wherever they are employed. Even if capable, that is not always a more desirable/efficient experience.
Yeah this is exactly my view. We've had several years of work on the tech, and LLMs are just as prone to randomly spitting out garbage as they were the first day. They are not a tool which is fit for any serious work, because you need to be able to rely on your tools. A tool which is sometimes good and sometimes bad is worse than having no tool at all.
Did google not rely on Gemini to do their ISA changeover?
https://arxiv.org/abs/2510.14928
Was Gemini worse than no tool at all there?
Probably. According to the paper, 83.82% of automated commits were already made by algorithmic tools (non-LLM). For the remainder, a three-phase LLM approach was tried, and achieved a success rate of 30%. Based on these numbers, it probably would have been faster, cheaper, and more efficient to just enhance their current strategy rather than screwing around with text generators.
Do you really think that Opus 4.6 hallucinates to exactly the same degree as GPT-3.5? I am mystified how you can hold this perspective.
If you're not seeing the hallucinations, I'd assert you're either not using it enough, or (more likely) you don't have enough knowledge in the subject matter to notice when it's hallucinating.
I'm not interested in getting into some argument about who has "more knowledge in the subject matter". I'm genuinely curious: do you think Opus 4.6 hallucinates just as much as GPT-3.5?
LMFAO does it hallucinate to the same degree as GPT 3?
Which is what was questioned.
The completely different way people are experiencing AI is fascinating.
In my world AI is already far more influential than text to speech.
People on here act like we don’t know if AI will be useful. And I’m sitting over here puzzled because of how fucking useful it is.
Very strange.
I'm curious about the statement that hallucinations are "fundamentally unsolvable". I don't think an AI agent has left a hallucination in my code - by which I mean a reference to something which doesn't exist at all - in many months. I have had great luck driving hallucinations to effectively 0% by using a language with static typechecking, telling LLMs to iterate on type errors until there are none left, and of course having a robust unit and e2e test suite. I mean, sure, I run into other problems -- it does make logic errors at some rate, but those I would hardly categorize the same as hallucinations.
So type errors are not hallucinations in your book, but "a reference to something which doesn't exist at all" is?
In the context of AI most people I know tend to mean wrong output, not just hallucinations in the literal sense of the word or things you cannot catch in an automated way.
My statement is that if your only hallucinations are type errors, that can be solved by simply wrapping the LLM in a harness that says "Please continue working until `yarn run tsc` is clean". Yes, the LLM still hallucinates, but it doesn't affect me, because by the time I see the code, the hallucinations are gone.
This is something I do every day; to be quite honest, it's a fairly mundane use of AI and I don't understand why it's controversial. To give context, I've probably generated somewhere on the order of 100k loc of AI generated code and I can't remember the last time I have seen a hallucination.
Maybe you're lucky. I had Opus 4.6 hallucinate a non-existing configuration key in a well known framework literally a few hours ago.
Granted, it fixed the problem in the very next prompt.
Couldn’t that problem be solved with static typechecking?
ChatGPT 5.2 kept gaslighting me yesterday telling me that LLMs were explainable with Shapley values, and it kept referencing papers which talk about LLMs, and about SHAP, but talk about LLMs being used to explain the SHAP values of other ML models.
I encounter stuff like this every week, I don't know how you don't. I suppose a well-structured codebase in a statically typed language might not provide as much of a surface for hallucinations to present themselves? But like you say, logical problems of course still occur.
I mean to say that code generation never hallucinates. I suppose that was unclear.
>> I don't think an AI agent has left a hallucination in my code
I literally just went on Gemini, latest and best model and asked it "hey can you give me the best prices for 12TB hard drives available with the British retailer CeX?" and it went "sure, I just checked their live stock and here they are:". Every single one was made up. I pointed it out, it said sorry, I just checked again, here they are, definitely 100% correct now. Again, all of them were made up. This repeated a few times, I accused it of lying, then it went "you're right, I don't actually have the ability to check, so I just used products and values closest to what they should have in stock".
So yeah, hallucinations are still very much there and still very much feeding people garbage.
Not to mention I'm a part of multiple FB groups for car enthusiasts and the amount of AI misinformation that we have to correct daily is just staggering. I'm not talking political stuff - just people copy pasting responses from AI which confidently state that feature X exists or works in a certain way, where in reality it has never existed at all.
My comment was about code, not fact checking - that’s why I said they were a solved problem provided you use static typechecking and tests.
The hype around AI is admittedly annoying - especially from the Wall St crowd who don't know how to pronounce 'Nvidia' correctly, and who haven't managed to internalize the fact that the chatbots they use hallucinate.
It really is 'different', though, in the same way the Internet was.
It took about 20 years (ie: since The World ISP) for the Internet to work its way into every facet of life. And the dot com bubble popped half-way through that period of time.
AI might 'underwhelm' for another five or ten years. And then it won't. Whether that's good or bad, I don't know.
The only people underwhelmed by AI in February 2026 are people who have formed an identity around being AI skeptics over the last couple years and are struggling to shed it. I haven't met anyone who has seriously used the new models who isn't a at least a bit awed and disturbed.
That's very true in terms of how capable these chatbots clearly are, but I believe the author was using 'underwhelming' to refer to the societal impact.
So far, life goes on roughly the same as it did five years ago. This can feel 'underwhelming' in contrast to the onslaught of public discussion about, and huge investments in, AI.
Most of us here on HN are programmers, and we all know how radically LLMs have changed our code projects. Even so, the change to our everyday lives (aside from our work or hobby project) is not, just yet, glaringly obvious. This year, it's mainly... every website shoves an AI box on its site that nobody seems to want!
There is also that contrast about it being genuinely useful for work/programming and the fact that, for now, it changes the rest of my life in a negative way - by making PC hardware unavailable, by hearing every day I'll be out of work in 6-24 months, and by having to deal with people taking the information from Chat for granted.
Not true. I'm a really heavy user of AI. And it's improved my productivity dramatically as a developer, but it doesn't work in every situation even in programming. I see it as an indispensible tool, but its not, right now, a tool that will replace me as a programmer or product manager or salesperson, or marketer. or (in my case) an owner and investor.
Will that happen in the future, maybe. but I don't have enough insight into how AI is evolving in the labs to make a judgement on that.
This statment is really annoying and getting boring. There are A LOT of us who have built careers evaluating technology with healthy skepticism, finding where it works and were it doesn't, excited to share & learn - and we've heard "this time it's different" many times. Now because we refuse to jump in without that same nuance and thought, and proclaim "everything's different over night!" we're branded as ludites when we're really trying find a balance.
I don't hear people saying "nothing is going to change", but I do hear questions about the timeline and if the current levels of investment match returns. Branding these people as stuck in some sort of negative identity is bullshit.
What is your position on AI?
in a nutshell: AI - even if transformative and in the future a widely used general-purpose technology - is normal technology. I reject the technological determinism that is being fed to us, especially the idea that AI itself is an agent in defining its own future. I think adoption and the post-adoption spread will be slow & uncertain (relative to the current messaging) regardless of where it ultimately takes us. I think the absolute societal impact is grossly overstated, and the roles of institutions shaping the path underestimated or ignored.
You’re creating a false dichotomy to alienate perceived opponents. Frankly, it’s really annoying and close-minded, and you haven’t contributed anything to the conversation.
You're likely to find more nuance in opposing views than your "underwhelmed by AI" generalisation could represent.
"AI is a bubble!"
"AI will change everything!"
Few seem to understand that both of the above can be true. The parallel you draw to the internet revolution is apt; dot-coms were both a bubble and changed everything.
it literally describes the gartnerhype cycle. this article is pointless, the only thing that matters is what survives it with over 1m users. AI will have billions of users when GHC is on the back end.
What world are you living in where AI is underwhelming currently? I can’t even comprehend this. Are you just not using it or something?
I think a good analogy will be the way word processors changed printing. Suddenly anyone with access to a computer had the ability to do professional level editing and layout. Most of them didn’t have the taste or skills to use the tools to the fullest, but it still opened up a ton of possibilities that weren’t available before because it was never practical to hire an actual professional to do a poster for a dinky church bake sale before. But now, church bake sales can have pretty slick looking posters (and websites) depending on whether any of the volunteers cares enough to get.
The stuff LLMs will democratize will be a lot more impactful than nice posters for car wash fundraisers though. So in that sense it will be different, but I don’t think it will crack the market for proficient experts in the field in the same way photoshop didn’t destroy graphic design and CAD didn’t destroy drafting. It may get rid of the market for a lot of the second-tier bootcamp grad talent though, so I wouldn’t be getting into that right now if I could help it.
I think this is exactly right. I've been thinking of "this time" as similar to the advent of digital spreadsheets. Spreadsheets existed for thousands of years but spreadsheet programs transformed spreadsheet work that took hours or weeks into seconds. You still had to know what you were doing, and if you knew what you were doing you were easily 10x faster than those that didn't.
I think we are in a similar situation with code generation now, then only difference in my mind is that LLMs come with a massive platform risk. Who's to say that one day anthropic decides my company is too much of a competitor to use their tool (like they've already done with openai) or what if they decide that instead of pulling their product from my use they just make it generate worse code, or even insert malicious payloads. A dependence on these tools is wildly more risky than dependency on a word processor or a spreadsheet program. It reminds me of the arguments around net neutrality and I cannot fathom how people building on top of, and with, these tools do not see the mountain of risks around them.
>Blockchain... NFTs >The problem is, the same dudes who were pumped for all of that bollocks now won't stop wanging on about Artificial Intelligence.
I was firmly in the camp that blockchain was not a viable solution to any problem, and that NFTs sound stupid. I think AI is much different than that list. So, there goes your argument?
> I was firmly in the camp that blockchain was not a viable solution to any problem, and that NFTs sound stupid. I think AI is much different than that list. So, there goes your argument?
Squares are rectangles. The existence of rectangles that aren't squares doesn't negate that.
You need to re-evaluate your logic here; if you were a Blockchain / NFT booster who doesn't believe AI is different you could argue you've disproved their argument. You have not.
Yeah that comparison doesn't pass the smell test. Blockchain/crypto were purely financial instruments and for better or worse, a new financial instrument is very different than a new tech innovation; tbh there was a thin veneer of tech when it comes to crypto/blockchain, but the magic was because of the money, not because of the tech.
AI is different because the magic clearly is because of the tech. The fact that we get this emergent behavior out of (what essentially amounts to) polynomial fitting is pretty surprising even for the most skeptical of critics.
I think the author is saying that a specific crowd, which happened to be very vocal and excited about web3 and NFTs, is also very vocal and excited about AI. In my personal experience they are right, a lot of the hustler types around me who were trying to get everyone to "invest" in digital land are now doomposting about AI.
It's not a very legible situation for people outside of the profession, and a lot of them believe it's just another grift that will blow up in a few years.
By the looks of it, 2026 might be the year where reality and fiction will finally collide with AI and we'll be able to see if all the hype was warranted.
But like all the previous hype, most of the people that were the loudest won't say they were wrong, and they'll move to the next thing, pretending like they never were the one that portrayed AI as the holy Graal.
There are all sorts of algorithms in use that were once thought of as AI, but transitioned to being mere algorithms well before they entered public awareness, if they did that at all. Some are still useful and used everywhere, but they have never been thought of as AI by the public. For them, AI is a term that has long been reserved for some far-off, sci-fi future.
LLM's are not artificial general intelligence (i.e. not sci-fi AI). Why haven't they transitioned to being mere algorithms by now? Why is the public being told AI is finally arriving when it's really just another algorithm?
We have some truly slick and shady corporations involved in the bubble right now and they're marketing LLM's like tobacco. LLM's have been pushed out, at immense cost, to the public in a way that makes them more directly accessible to average people than any past algorithm. Young children can ask a LLM to do their homework for them. Middle managers can ask a LLM to create a (shitty) ad campaign for them. Corporations have gone to tremendous expense to make that widely available and, for the moment, mostly free. They seem to be following the Joe Camel school of marketing. Get them hooked while they're young so they come to you first when they're older! The only difference is that nobody is stepping in to stop the new Joe Camel from handing out free samples to kids.
Then there's the "go big" aspects of the bubble. The major competitors are trying to out-spend each other to dominance, but the suckers are so colossally big that their bubble is affecting global GPU, memory, and storage prices. This bubble is going to stress power grids wherever it operates and do considerable environmental harm. The financial games being played behind the bubble are absolutely stupid. The results, so far, are tantalizing for billionaires. LLM's offer the promise of being able to fire all their pesky and annoying human workers. It won't deliver on that, and none of these companies is ever going to make enough to pay their debts. There might be "too big to fail" government bailouts, but there are going to be some big bankruptcies too.
Useful algorithms will come out of all this, a lot of tears too, but not "AI".
AI is real but the socio-political environment is far from conductive to some form of productive use of it - as opposed to using it as a war-machine - AI isn't going to fail in that role but very few will be happy about it.
I mean, disillusionment is the least of my worries.
> and we'll be able to see if all the hype was warranted.
Umm, what? For the past 3 years, every year I've said something along the lines of "even if models stop improving now, we'll be working on this for years, finding new ways to use it and make cool stuff happen". The hype is already warranted. To have used these tools and not be hyped is simply denial at this point.
Maybe AI is useful to you, but the US economy is currently buoyed by promises of AI replacing the workforce across the board.
Most of Mag-7 are planning to spend over 500B on capex this year alone on building out datacenters for AI pipelines that have yet to prove that it can generate a sustainable profit. Yes, AI is useful in some environments, but the current pricing is heavily subsidized. So my point stand, the hype is not warranted.
> but the US economy is currently buoyed by promises of AI replacing the workforce across the board.
Still don't understand what's the end goal here. Assuming they don't deliver, then there are billions of investments that will go bust. Assuming they deliver, millions lose their jobs and there's going to be a bloodbath on the streets.
the end goal is productivity growth, aka the point of nearly every technology ever invented. The human story is about how we learn to do more with less.
https://archive.org/details/JacquesEllulTheTechnologicalSoci...
There isn't a unifying end goal, each individual actor has the goal of getting more money.
> Assuming they don't deliver, then there are billions of investments that will go bust. Assuming they deliver, millions lose their jobs and there's going to be a bloodbath on the streets.
There is a third outcome that combines both of these.
LLMs can massively displace the workforce (and cause widespread social instability) AND the companies pouring hundreds of billions into them right now could, at the same time, fail to capture significant amounts of the labor savings value as late-mover alternatives run the race drafting their progress without the massive spend.
I'd honestly be surprised if this double-whammy isn't the outcome at this point. AI is going to have a massive impact on everything, but there is still no moat in sight.
I think our little corner of the world has a distorted view of AI in that it is actually proving useful for us. Once they passed a certain level of usefulness... I remember when they were still struggling just to output syntactically correct code, you know, like, 18 months ago or so... they became a useful tool that we can incorporate.
But there's a lot of things playing out to our advantage. Vast swathes of useful and publicly available training data. The rigorous precision of said data. Vast swathes of data we can feed it as input to our queries from our own codebases. While we never attained the perfect ideal we dreamed of, we have vast quantities of documentation at differing levels of abstraction that the training can compare to the code bases. We've already been arguing in our community about how design patterns were just level of abstraction our coding couldn't capture and AI has access now to all sorts of design patterns we wouldn't have even called design patterns because they still take lots of code to produce, but now for example, if I have a process that I need to parallelize it can pretty much just do it in any of several ways depending on what I need at that point.
It is easy to get too overexcited about what it can do and I suspect we're going to see an absolute flood of "We let AI into our code base and it has absolutely shredded it and now even the most expensive AI can't do anything with it anymore" in, oh, 3 to 6 months. Not that everyone is going to have that experience, but I think we're going to see it. Right now we're still at the phase where people call you crazy for that and insist it must have been you using the tool wrong. But it is clearly an amazing tool for all sorts of uses.
Nevertheless, despite my own experiences, I persist in believing there is an AI bubble, because while AI may replace vast swathes of the work force in 5-20 years, for quite a lot of the workforce, it is not ready to do it right this very instant like the pricing on Wall Street is assuming. They don't have gigabytes of high-quality training data to pour in to their system. They don't have rigorous syntax rules to incorporate into the training data. They don't have any equivalent of being guided by tests to keep things on the rails. They don't have large piles of professionally developed documentation that can be cross-checked directly against the implementation. It's going to be a slower, longer process. As with the dot-com bubble, it isn't that it isn't going to change the world, it is simply that it isn't going to change the world quite that fast.
Leaving aside the economic shitshow and other things.
I think you're right but for the wrong reasons wrt sustainable profit.
Specifically, overcounting how much it will cost in 5 years to run AI because you're extrapolating current high prices, and at the same time undercounting how the demand will drive efficiency gains.
i think the point is AI has to go much further and faster than it has in the past 3 years to justify the investments being made from the hype. The hype did its job now the AI industry has to execute and create the returns they promised. That is still very much up in the air, if they can't then the tech was over hyped.
This.
It's high time to stop accumulating debt while providing free picture of pelicycles, just charge the full cost for them - enough to generate profits and pay back debt.
What we see now is literally burning money and energy to generate hype. The only true measures of success are financial and macroeconomic. If the hype is real, there should be no problem for the mighty AI to generate debt-free profits for its providers while the overall price level in the US goes down.
We observe the exact opposite which makes the AI hype act only as market manipulation for capital misallocation.
unlike the old hpc, where we only burned hundreds of millions for machines that were 80% efficient to get a 5 year lead, we are burning hundreds of billions on machines that are 30% efficient to get a 1 year lead.
> most of the people that were the loudest won't say they were wrong
I was so expecting to find this wind-up aimed at those peddling the "AI is hype" laziness.
It's laziness because they have little CS fundamentals to base such claims on, and the deductions can be made, just not clearly to people who need to study a lot more.
It's like watching an invisible train (visible to those with strong CS) rolling down the tracks at a leisurely pace. Those sitting in their stalled car on the tracks are busy tweeting about "AI HPY PE TRAIN." Until it wrecks their car, the gimmick is free oxygen. It's a lot easier to write articles than it is to build GPUs and write programs.
> It's laziness because they have little CS fundamentals to base such claims on
So, what CS fundamentals do you need to evaluate if AI is the real thing, or will disappoint in the future? Until a few months ago, coding agents were met with skepticism, until Anthropic introduced their new model and, with it, a hype train that cannot be rationally justified. Look, SOTA LLMs, and coding agents in particular, are impressive. However, current predictions about the future of software development (and the world in general) are speculative. There is little to no data showing whether AI can deliver on its promises. How could there be in this short time frame? No one knows what the future will hold, no one knows how coding agents will be integrated into our work life and everyday life in the long run, or what hard limitations they will reveal. No one can tell you how professions will change in the coming years; every prediction is purely speculative, and anyone making prophecies is either trying to cope with the uncertainty themselves or has some stakes in the AI bet. It would be nice if people were actually humble enough to admit that they have no idea what will happen in the future, instead of writing the hundredth doom and gloom post.
> However, current predictions about the future of software development (and the world in general) are speculative.
It's amazing to me how those willing to seize on the speculative nature of any ANY uncertainty cannot recognize the inherent uncertainty of the inverse.
> what CS fundamentals do you need
1. Tarski's undefinability theorem 2. Gödel's incompleteness theorems 3. Curry Howard correspondence
And a lot of exposure to deductive reasoning, vague ideas of automated theorem proving and formalization.
I won't pretend its easy, but let's be clear, a small fraction of people who know things are being forced to entertain the hysteria of a vast majority who are unwilling to know things and just go around beating their chests and will continue doing so until the train hits them.
There are 2-3 minor architectural changes in between now and what I would identify as a completely unbounded AGI with clearly discernible dynamic, self-defined objective functions and self-defined procedures for training and inference. It can be done in megabytes. Oh god. Get me out of this forum. I wish to return to my code editor.
What exactly are you claiming here? That a handful of theorems about the limits of mathematics and provability somehow combine to show that the current LLM-based AI developments will inevitably live up to what is expected of them? And that this is obvious to a select few? That all seems unlikely, to say the least.
This just sounds like the "nothing ever happens" theorem slightly rephrased, of which Scott Alexander did a great refutation here: https://www.astralcodexten.com/p/heuristics-that-almost-alwa...
I’m doing enterprise coding tasks that used to take a month of whole team coordination from mockups to through development and testing in 3 days now. It’s all test driven development, codex 5.3 and a small team of two people who know how to hold it right orchestrating the agents. There’s no reason not to work this way. The sociotechnical engineering aspects of this change are fascinating and rewarding to solve.
I work for an old enterprise, so far rather conservative with LLM/AI usage. However the copilot cli adoption in the last 2 weeks is spreading light wild fire. Codex 5.3, a good instructions file and it works. Features are getting done and delivered in days, proper test coverage is done, proper documentation in place. Onboarding to it is also very fast.
Can you give an example of such features?
Porting tons of untyped js legacy front end code to vue with typescript and figma designs. Highly configurable business to business app (i.e lots of permutations). Everyone seems to have a “system”. I recommend looking at the OpenAI Cookbook for long running plans and do TDD to the extreme. https://developers.openai.com/cookbook/articles/codex_exec_p...
What's the feature that was built though? This sounds like low-value refactoring. They are fundamentally different development workflows.
Yes porting and also implementation of new features. Typical client requests for new functionality in business to business software.
Many of my industry friends and I were skeptics about all the things the OP mentions, still am. And yet, I am able to push 30-40K lines of nearly perfect code a day now.
It's different just like the steam engine was different, except technology moves much 100x faster now than it did then. It's different and the same.
The 40k lines of code a day crows are amusing. In solving any problem solvable by code, there's a ratio of non-coding work to coding work, and codex et al all help immensely with the coding work but help less with the non-coding work.
Non-coding work is thinking about the system architecture, thinking about how data should flow, thinking about the problem to be solved, talking with people who will use it, discovering what their objectives are.
Producing 40k lines a code per day simply means you're not doing any of that work: the work that ensures you're building something worth building.
Which is why the result is massive, pointless things that don't do the things people actually need, because you've not taken any time to actually identify the problems worth solving or how to solve them.
It's a form of mania that recalls Kafka's The Burrow, where an underground creature builds and builds an endless series of catacombs without much purpose or coherence. When building becomes so easy when it was so hard -- and when it becomes more fun to build and watch codex's streams of diffs fly by, than to plan -- we forget the purpose of building, and building becomes its own purpose, which is why we usually so little actual productive impact on the world from the "40k lines of code a day" cohort.
What job are you in where you can even come up with problems that -need- 30-40k lines of code a day?
And how do you know they are nearly perfect?
The unit tests written by the LLM all pass!
My 20k lines of unit tests say so?
Just because tests pass does not mean that they're testing the right thing to begin with. Reviewing tests is as important, if not even more important than reviewing code.
If you are pushing 40k lines of code per day you are an idiot and should be fired.
I agree with your point that the original claim is unlikely to be true (and would be extremely foolish behavior even if it were true). I don't think it's good to flame people though, even if they did say something unreasonable.
yeah... maybe he is working alone or bootstrapping a brand new thing?
Otherwise his entire team must collectively groan when a Slack message appears: "Got a new PR ready for review everybody!"
Do you actually think they're reviewing anything? It's vibe coded tests validating vibe coded impls and then pushed straight to production.
> "I am able to push 30-40K lines of nearly perfect code a day now."
It is physically and physiologically impossible for anyone to be reviewing "30-40K lines of nearly perfect code a day" to the extent needed to push it with confidence in a sensible development process.
Are you really reviewing 30-40k lines of code a day?
Why do you and many of your industry friends conveniently never actually post their 'perfect code' when asked for proof? I've asked like five different people now that make these claims and they just vanish into the ether.
Note that when code is shown, like the "browser" that was recently put on blast, it's often terrible.
Are we experiencing a huge influence campaign on HN?
do you understand every line of code you churn out?
>3D TV, AMP, Augmented Reality, Beanie Babies, Blockchain, Cartoon Avatars, Curved TVs, Frogans, Hoverboards, iBeacons, Jetpacks, Metaverse, NFTs, Physical Web, Quantum Computing, Quibi, Small and Safe Nuclear Reactors, Smart Glasses, Stadia, WiMAX.
For what it’s worth, not a single other technology in the list made any sort of impact on my work. For better or worse, LLMs did.
Well, okay, quantum computing actually affected me a lot because I worked at a quantum hardware manufacturer, but that’s different.
LLMs have not radically transformed the world yet because the number of people capable of solving problems by typing into a blinking cursor on a blank screen is actually quite small. Take that subset of the population and reduce it to those that can effectively write communicative prose, and its even smaller still.
It's just an interface problem. The VT100 didn't change the world overnight either.
There's another point, too. Detractors say LLMs will never advance to whatever threshold they consider meaningful. Fine. We're working on other paradigms, too, though. Just because a lot of o people are productizing LLMs doesn't mean the state of the art isn't advancing in parallel and AGI isn't in the cards.
Agree, LLMs are just another tool. Treating them as chatbots is a very basic way of using them. The future is intelligent engineers embedding them in traditional systems and having them perform specific roles.
Author forgot Segway. Remember when it was going to fundamentally change humanity?
Their Ninebot escooters are pretty damn good, far better than most random brands.
I spent most of Covid in VRChat and met my current live-in gf, so the metaverse was real for me too.
I also made decent money selling crypto, so that part was real for me too.
And AI coding, for as dumb as even the best models are, still enabled me to create things that I wanted to, but wouldn't have had time or gotten nearly as far without.
I dunno if the author realizes, but all the things they mentioned did materialize in one way or another, just not exactly how the hype described it.
Maybe if they could let go of some of the cynicism, they could find something to be optimistic about. Nothing ever goes exactly as planned, but that doesn't mean nothing is good.
> I dunno if the author realizes, but all the things they mentioned did materialize in one way or another, just not exactly how the hype described it.
From the post, which is not a very long one: "All of the above technologies are still chugging along in some form or other (well, OK, not Quibi). Some are vaguely useful and others are propped up by weirdo cultists"
Fair, I read the whole post but I guess that part didn't register, maybe because I never fullheartedly believe marketing fluff to begin with. Maybe this person has too much contact with "AI will fix everything" types, and not enough with actual scientists who are really developing novel methods better than anything before, piece by piece.
I also found the "it's almost always dudes" line a bit strange, because I've seen plenty of women doing marketing for startups running on hype.
But there's a spectrum of responses to these technologies, from knee-jerk cynicism to genuine moral disgust. "Useful" and "good for people/society/humanity" don't always go hand-in-hand, particularly if you take origins and power into account.
Heh - that went right off the cliff, when... well, I will let the reader research that themselves...
The guy who died on one was Jimi Heselden, who was a British entrepreneur who bought the company from the American inventor, Dean Kamen. Dean is alive, however he was recently found to have hung out with the "disgraced financier".
That’s dark. But.. accurate.
I see hoverboards everywhere, which are the self balancing scooter tech from the Segway. Many little ebikes as well making deliveries.
75% of restaurant orders are delivery now due to widespread personal electric transportation. It already has fundamentally changed humanity.
https://youtu.be/KOSUEFqszK8
The post nicely lists a bunch of failed hyped tech:
> 3D TV, AMP, Augmented Reality, Beanie Babies, Blockchain, Cartoon Avatars, Curved TVs, Frogans, Hoverboards, iBeacons, Jetpacks, Metaverse, NFTs, Physical Web, Quantum Computing, Quibi, Small and Safe Nuclear Reactors, Smart Glasses, Stadia, WiMAX.
...conveniently doesn't list a bunch of hyped tech that hasn't failed:
> microchips, PCs, the internet, ecommerce, cloud, EVs, 5G
...and presents this as evidence that the current hyped tech (AI) will fail:
> Seems like you say that about every passing fancy - and they all end up being utterly underwhelming.
When the article needs to construct disingenious arguments, I'm not interested in its conclusion.
But wait! If you actually read to the end, there's a plot twist!
> The ideology of "winner takes all" is unsustainable and not supported by reality.
Who said anything about winner takes all? You just burned a "this time is different" straw man and then conclude that "winner takes all" is not realistic?
At this moment I'm wondering if the article was in fact written by a quantized 8B LLM. Surely people don't do such non-sequiturs and then expect to be taken seriously.
But of course not. This is not an argument. This is preaching to the choir.
Preach, brother, preach.
Exactly! If this post had been written 20 years ago it would have started with
Internet, handheld computers, electric cars...The problem is the same dudes.
Putting beanie babies in with Quantum Computing and Nuclear Power completely ignores the potential life changing elements of some technologies, even if they don't work.
Oh, and smart glasses he put in there, so he'll be eating his words in 2 years.
OP here. If you're interested, here are my thoughts on Google Glass from 12 years ago.
https://shkspr.mobi/blog/2014/04/quick-thoughts-on-google-gl...
I am looking forward to 2028 matching the hype of 2014.
No-one thought the internet was a failed technology in 2006. It was a vital tool by then.
Handheld computers were an expanding market, dominated by Blackberry.
EVs were an immature technology but hybrids like the Prius were selling.
You may remember this video featuring Facebook with a ridiculously high $15B valuation, Skype, YouTube and other failures: https://m.youtube.com/watch?v=I6IQ_FOCE6I
> 3D TV, AMP, Augmented Reality, Beanie Babies, Blockchain, Cartoon Avatars, Curved TVs, Frogans, Hoverboards, iBeacons, Jetpacks, Metaverse, NFTs, Physical Web, Quantum Computing, Quibi, Small and Safe Nuclear Reactors, Smart Glasses, Stadia, WiMAX.
I’ve never heard half of the things and the other half is mostly consumer electronics or specific product names. The closest example here is Quantum Computing, which is also a serious technology in development. I think for the OP these are all tech buzzwords that he invests in without understanding what they really are. That’s why he thinks all these unrelated things are the same.
I'd say AR & VR were hyped to be as big as AI is now, but just haven't fully delivered on the promise yet. 3D printing was similarly hyped for a time. Same with blockchain. Nuclear power in the 50s was hyped to be the future of energy.
The point is to take the hype with a grain of salt and knowledge that not all hyped technologies transformed the world as promised. Maybe AI is like the internet or electricity. But maybe the claims about AGI/ASI and full automation are just hype.
I always figured AI would be a big deal from childhood onwards and wrote about it for my college entrance exam in 1980 or so. That doesn't apply to any of
>3D TV, AMP, Augmented Reality, Beanie Babies, Blockchain, Cartoon Avatars, Curved TVs, Frogans, Hoverboards, iBeacons, Jetpacks, Metaverse, NFTs, Physical Web, Quantum Computing, Quibi, Small and Safe Nuclear Reactors, Smart Glasses, Stadia, WiMAX
It's quite a different thing, more on the level of the evolution of life on earth and quite unlike all that junk.
When non-programmers make sweeping statements about LLMs.
Deep disconnect from reality.
For me, this captures it:
"All of the above technologies are still chugging along in some form or other (well, OK, not Quibi). Some are vaguely useful and others are propped up by weirdo cultists. I don't doubt that AI will be a part of the future - but it is obviously just going to be one of many technology which are in use.
> No enemies had ever taken Ankh-Morpork. Well technically they had, quite often; the city welcomed free-spending barbarian invaders, but somehow the puzzled raiders found, after a few days, that they didn't own their horses any more, and within a couple of months they were just another minority group with its own graffiti and food shops.
- Terry Pratchet's Faust Eric"
I get that everyone has a strong opinion on whats-going-to-happen-with-AI, but I really think nobody knows.
We're in that part of turbulence where we don't know if the floating leaf is going to go left or right.
The people who will have the hardest time with this transition are those who go all in on a specific prediction and then discover they were wrong.
If you want to avoid that, you can try very very hard to just not be wrong, but as I said, I don't think that's possible.
Instead, we need to be flexible and surf the wave as it comes. Maybe AI fades away like VR. Or maybe it reshapes the world like the internet/smartphones. The hardest thing to do right now, when everyone is yelling, is to just wait and see what happens. But maybe that's the right thing to do.
[p.s.: None of this means don't try to influence events. If you've got a frontier model you've been working on, please try to steer us safely.]
I got my first tech job in 2001. I've been doing this a while and ridden all the waves.
There are two kinds of waves. The ones that don't require collective belief in them to succeed, and those that do.
The latter are kinds like crypto and social media. The former is mobile...and AI.
If no one else in the world had access to AI except me, I would appear superhuman to everyone in the world. People would see my level of output and be utterly shocked at how I can do so much so quickly. It doesn't matter if others don't use AI for me to appreciate AI. In fact, the more other people don't use AI, the better it works out for me.
I'm sympathetic to people who feel like they are against it on principle because scummy influencers are talking about it, but I don't think they're doing themselves any favors.
> If no one else in the world had access to AI except me, I would appear superhuman to everyone in the world.
You really wouldn't. AI simply isn't that useful because it is so unreliable.
I have found that to be utterly untrue
to me, ai seems likely to become a new user interface, just like gui did from cli.
abstract away a lot of the mechanics of working with data/information.
helpful, when literacy seems to be trending in a downward direction.
Everything is the same until it's not, good luck predicting when "until it's not" is on the horizon though. Isn't technology innovation a power law thing? Everything hums along fairly regular and then, out of the blue, there's a massive impact. Personally, I think AI has made a pretty large impact in software dev and overall tech industry but I don't see AGI any time soon (and that hype has died down) and therefore I don't see the economics working out. The coding tools, API integrations, chatbots, those are great but I don't see them producing the returns required to keep companies like OpenAI running unless OpenAI takes all the customers and all the ad clicks from everyone else ( Athropic, Alhphabet, X, Amazon, Meta, even Microsoft ). I just don't see that happening.
Perhaps this is the failure to understand the distinction between a technology and a meta-technology. Upgrading the factory that builds the robots is much different than upgrading the robots.
A technology is a set of methods and tools for achieving the desired results (generally in a reliable and reproducible way). Or, in a broader sense of the word, it's the idea of applying scientific knowledge to solving practical problems, and the process of such application.
What is meta-technology?
Or (taking the other side) failure to notice the distinction between a technology and a pump-and-dump. The technology (attention/diffusion) is awesome. The hype is unbelievable. Literally.
Said elsewhere on this post... "AI is a bubble!" "AI will change everything!"
Is just propaganda...
Iran is 2 weeks from a nuclear weapon We obliterated Iran's nuclear dreams
Russia is fighting with shovels Russia is on the verge of swarming Europe
What would Joost Meerloo say about it, I wonder.
Use the reader view button.
A very cynical article.
Actually IT IS different. Actually if they manage to create a viable small nuclear reactors or Quantum computers the world will change like it changed with the Watt thermal engine.
Why he is not talking about the Internet, trains, electricity, nuclear bombs, rockets,aviation or engines? Because they worked, like AI works today.
All of them were bubbles at the time and they changed the world forever. AI is changing the world AND it is a bubble.
AI is here to stay. It will improve and it will have consequences. The fact that a robot could do things with its hands is actually significant, whenever you like it or not.
> Why he is not talking about the Internet, trains, electricity, nuclear bombs, rockets,aviation or engines? Because they worked, like AI works today.
Except for the minor bit that AI doesn't work today, and it is not yet clear if it ever will.
This Andrew Klavan interview on AI is worth your time, if not an independent submission:
https://www.youtube.com/watch?v=SZFhFGpDWGw
"Today, I'm speaking with Stephen C. Meyer, Director of The Discovery Institute's Center for Science and Culture, and and George D. Montañez, Director of the AMISTAD Lab at Harvey Mudd College–both of whom are extremely knowledgable on the topic of artificial intelligence. During the course of our conversation, they discuss the asymmetry between human intelligence & AI, the inability of AI to ascribe meaning to raw data, and the limitations of large language models. The real question though is: are we screwed? Let's find out."
Honestly, the remixes this generation suck compared to priors.
"This time will be different," they said about the Metaverse, ignoring the vast tranches of MUCKs, MUDs, MMOs, LSGs, and repeated digital real estate gold rushes of the past half-century. Billions burned on something anyone who played Second Life, Entropia, FFXIV, EQ2, VRChat, or fucking Furcadia could've told you wasn't going to succeed, because it wasn't different, it just had more money behind it this time.
"NFTs are different", as collectors of trading cards, art prints, coins, postage stamps, and an infinite glut of collectibles looked at each other with that knowing, "oh lord, here we go" glance.
"Crypto is different", as those who paid attention to history remembered corporate scrip, gift cards, hedge funds, the S&L crisis, Enron, the MBS crisis, and the multitude of prior currency-related crises and grifts bristled at the impending glut of fraud and abuse by those too risky to engage in traditional commerce.
And thus, here we are again. "This time is different", as those of us who remembered the code generators of yore pollute our floppy drives and salesgrifts convinced our bosses that their program could replace those expensive programmers roll our eyes at the obvious bullshit on naked display, then vomited from stress as over a trillion dollars was diverted from anything of value into their modern equivalent - with all the same problems as before.
I truly hate how stupidly people with money actually behave.
Is this “nothing ever happens”
Short of insider trading, betting on things not happening is apparently the best way to make money on those shady betting sites.
This lazy kind of post annoys me because it sort of groups any of us saying that this technology is profoundly different in with all the town criers who have said this kind of thing before — even if we have never said it before and were even skeptical of past declarations
Effectively, it’s a statement saying nothing can ever be profoundly different, because people have said it before and been wrong.
Lazy.
LLMs are really a marvel, GPT 2 actually inspired me to go back to college (not directly, rather I needed to understand how it worked).
I have unlimited derision for morally spineless worms who disingenuously make it out to be more than it is-- looking at Dario, Sam, and the silly CEO of Control AI. Also, I hate to say it but Andrej Karpathy on twitter-- he's a worthless follow now. I can't blame, but am daily exasperated by media figures who can't help but go with what they hear prominent individuals in the field say.
If I were a junior now, and less confident, I would be abandoning my career in this climate.
LLMs are not going away. They will get a little better than they are now, and new model paradigms will come around at some point. But this tale of massive redundancy and skyrocketing unemployment is not going to come from LLMs.
This is the only reason why I cannot wait for a pop, and pray to God that it comes sooner than later. I just want to feel good about technology again. I want to tinker, to feel positivity, to know how sustainable the tools I'm using actually are.
I don't want to be reminded daily of the disgusting reality of unbridled capitalism.
I enjoyed Dave Cridland's comment more than the article. The article is dismissive of AI and other technologies in an unsubstantiated way.
New things are happening and it's exciting. "AI bad" statements without examples feel very head-in-sand.
OP here. Unless you're still watching Quibi on your curved TV, delivered via WiMax then, yeah, I'd say it was pretty bloody substantiated.
I like technology. I made a decent living from it. But if I had chased every hyped fad that was promised as the next big thing, I doubt I'd be as happy as I am now.
You claim to cite 'technologies' but include a few brands and companies for some reason.
The one you keep citing, here and in the article, Quibi, lives on in technology-form (the spirit of your article we must presume) as an 8 billion dollar business in China and is rapidly upending every Hollywood film studio.
So, arguments about substantiation or even 'this time' fall flat in the face of not even understanding your own message.
Just chiming in to say thanks for the Pratchett quote! I dare say he's about to beat out Douglass Adams for my top author. Feets of Clay and Hogfather should be must reads for people dealing with AI right now imo.
You're not really saying anything, though. For every tech hype that has failed, there is another that's changed the world. This IS changing the world and our industry, regardless of whether it reaches the heights of the hypers.
I mean you're just stating that sometimes tech doesn't meet it's hype. What's insightful about that? It's a given; cherry-picking examples doesn't prove your case.
> For every tech hype that has failed, there is another that's changed the world.
Well, no, the ratio is most definitely not 1-to-1.
The thing is, the successful tech rarely get the excessive hype.
MRNA vaccines. Where are the countless breathless articles about these literal life saving tech? A few, maybe, but very few dudes pumping out asinine "white papers" and trying to ride the hype train.
Solar and battery. Again, lots of real world impact but remarkably few unhinged blowhards writing endless newsletters about how this changes everything.
I'm struggling to think of a tech from the last 20 years which has lived up to its hype.
Not everything is written to be insightful. Some things are just written to get them out of my head.
I personally see plenty of hype but I've also been following the trends and using the tools "on the ground". At least in terms of software these tools are a substantial shift. Will they replace developers? No idea, but their impacts are likely to be felt for a very long time. Their rate of improvement in programming is growing rapidly.
Do feel AI is overall just hype? When did you last try AI tools and what about their use made you conclude they will likely be forgotten or ignored by the mainstream?
I spent an hour with Gemini this morning trying to get instructions to compile a common open source tool for an uncommon platform.
It was an hour of pasting in error messages and getting back "Aha! Here's the final change you need to make!"
Underwhelming doesn't even begin to describe it.
But, even if I'm wrong, we were told that COBOL would make programming redundant. Then UML was going to accelerate development. Visual programming would mean no more mistakes.
All of them are in the coding mix somewhere, and I suspect LLMs will be.
> write an article dismissing ai
> usage is copy pasting code back and forth with gemini
the jokes write themselves
That's the most recent time. But I've bounced around all the LLMs - they're all superficially amazing. But if you understand their output they often wrong in both subtle and catastrophic ways.
As I said, maybe I'm wrong. I hope you have fun using them.
Have you tried a coding agent such as claude code or codex?
Yes. And, again, they look amazing and make you feel like you're 10x.
But then I look at the code quality, hideous mistakes, blatant footguns, and misunderstood requirements and realise it is all a sham.
I know, I know. I'm holding it wrong. I need to use another model. I have to write a different Soul.md. I need to have true faith. Just one more pull on the slot machine, that'll fix it.
Unrelated to the conversation but:
> Not everything is written to be insightful. Some things are just written to get them out of my head.
I like that, going to use it as the motivation to get some things out of my own head.
Yes! More blogging :-)
Why do you think that solar+battery technology or MRNA vaccines haven't been written about in excited, hype-filled ways? If a technology is successful, then looking at past accounts of that technology and why it will change the world don't come across to you reading it now as hype, they come across as a description of something normal about the world.
The web? GLP-1s? 5G? The newton was mega-hyped, failed but Apple came back with the iPhone. All the dot com failures that eventually became viable businesses (so viable in-fact that sfgate has to reach back 26 years to write their stinkpiece [1])
Hype is often early, in 10-20 years we'll start seeing the value as the rest of the world catches up
https://www.sfgate.com/food/article/rise-fall-bay-area-start...
It's not unsubstantiated though. The claim is "People frequently assert that 'this time is different' and they are almost always wrong" and it proceeded to provide a reasonable list of analogous manias.
This only doesn't feel like substantiation if you reject the notion that these cases are analogous.
"You shouldn't eat that."
"Why not?"
"Everyone else who's eaten it has either died or gotten really sick."
"But I'm different! Why should I listen to your unsubstantiated claims?"
"(lists names of prior victims)"
"That doesn't mean anything. I'm different. You're just making vague and dismissive unsubstantiated claims."
The claim isn't "AI bad" the claim is more along the lines of "there's a lot of money changing hands and this has all the earmarks of a classic hype cycle; while attention/diffusion models may amount to something the claims of their societal impacts are almost certainly being exaggerated by people with a financial stake in keeping the bubble inflated as long as possible, to pull in as many suckers as possible."
If you want another example (which you won't find analogous if you've already drunk the koolaid):
https://theblundervault.substack.com/p/the-segway-delusion-w...
What is the point being made here? Some past technologies were overhyped, therefore AI is overhyped? Well, some past consumer technologies did change the world (smartphones, texting, video streaming, dating apps, online shopping, etc), so where's the argument that AI doesn't belong to this second group?
Also, every single close friend of mine makes some use of LLMs, while none of them used any the overhyped technologies listed. So you need a specially strong argument to group them together.
For all of those, there is a gartner hype cycle. The thing that matters is when it comes out the back end, is 1m, 1b, 6b people using it?
for all the things you listed, less than 1000 people are using it, with AI we're clearly not finished with the gartner hype cycle, but the back end is going to be over a billion users.
Blatant strawman.
If you can't distinguish the actual utility and progress of AI from it's annoying hype-men then it's hard to take your dismissal of AI seriously.
Failure to appreciate changes in AI will have left you calling every shot wrong over the past 5 years. While AI models continue to improve at an exponential rate, you'll cling to your facile maxims like "dude it's just predicting the next token it isn't real intelligence".
Nuclear weapons - this time is different
Internet - this time is different
iPhone - this time is different
I invested in Tesla extremely early (2011) because electric cars, if built correctly, would obviously make great cars, and Elon was one of the few people I actually thought had a shot at doing it.
I was right that blockchain was BS and all the "not sure about Bitcoin, but blockchain will be big" people were idiots.
I've been right for the last couple of years on AI and that people were vastly underestimating it when it came to it's coding potential. And I put my money where my mouth was here. In 2021 when GPT-3 came out I decided almost immediately I needed to invest a significant amount of my net worth in Google simply as hedge against AI destroying knowledge work jobs. Which at the time I thought was probably going to happen around 2030 not realising how far LLMs could go with reasoning.
I'm not particularly intelligent ("only" top 1-2% IQ), but my ability to predict the future is very good. If you have a skill you're unusually good you might relate to how it's strange other people find it so hard to do that thing you find kinda easy. For me that's predicting things and computers.
Since I was a young teen I have been worrying about AI. Most of my IRL best friends I have made from talking about AI risk in 2010s when I was studying AI.
Admittedly I got some of the details wrong back then. In 2010 I thought a lot of manual labour jobs would be easier to automate first – warehouse work, mail, taxis, buses, trains, etc. I worried primarily about the economic and political ramifications, and much less about ASI scenario (at least in this half of the century). But I think still I got the general timeframes and direction right. This was the decade I was concerned about.
I'm so scared right now... My whole life I've had nightmares about AI. I know there are some people who talk about how AI is an existential risk, but it feels like they don't internalise it like I do. They're not prepping like me for one, not that you really can prep for what's coming. If they're concerned why don't they have the nightmares of the omnipresent AI which you can't out think or punch to protect those you love? AI is so powerful in the scariest ways. Super viruses, mass surveillance and control, mind reading, unimaginable sci-fi weapons. It's like a horror story, but suddenly real.
I am an OG AI doomer, but until the last few months I've at least always had some doubt in my mind about whether I'm right, perhaps not about the risk of AI broadly, but about whether we'd actually be able to develop highly capable AIs while I still have a lot of my life ahead of me.
In my opinion this time is different, and what I've been worrying about for the last couple of decades is now here.
We are collectively the indigenous peoples of America and the Europeans have just arrived in the new world. The risk vectors are now endless and how this all plays out is hard to know exactly. What we do know is that the majority of ways this will play out are bad, and some are incomprehensibly bad. Some may achieve status and wealth in the near-term, but longer-term we're all dead, or worse.
I always worry these comments make me sound like a lunatic, I think I am, but I hope I am. I hope you will all forgive me, but I just need to shout about this tonight while I still can. We need to stop this insanity. Data centers need to be nuked. You may doubt me now, but in time you will understand. Hopefully I won't be around to say I told you so. Please make the best of the time we have left.
> I needed to invest a significant amount of my net worth in Google simply as hedge against AI destroying knowledge work jobs
I felt similarly, and did similarly, with both GOOGL and MSFT. I'm not an AI "doomer" in the Yudkowski/LolzWrong sense, but I do think it's quite sad that generative AI is first branch of the AI "tech tree" we raced up. AI art, especially, is tragic.
this just looks like someone hearing about tons of hyped things from people across the internet (which almost by definition, is full of false signals and grifters), imagining they are coming from the same person, then arguing with how wrong that person always is. how is that interesting?
I hoped the article would be be a meta-discussion of "time" and perhaps relativity or some other phenomenon. Sigh, it's an investment thesis saying "This Time is Different" is a risky bet.
That sounds like an interesting article. You should write it.
Or have an LLM write it and then we can judge whether the OP is wrong about whether "this time is different".
I feel like someone is in a bubble of Crypto-bros. That does not instill confidence.
I would suggest editing the title to "This Time is Different". I think that captures the essence much better.
Love the Sir Terry reference.
I wonder if that was an automated HN edit?
Similarly to how titles that start with "how" usually have that word automatically removed.
Usually HN only auto-edits on first submission. If you go in and undo it manually as the submitter, you can force it to read how you intend.
Maybe I'm only noticing the times when it messes things up, but it kinda seems like these auto-edits cause a lot of confusion that could be avoided if they were shown up-front to submitters, who would then have the option to undo them.
Or maybe judicious use of an LLM here could be helpful. Replace the auto-edits with a prompt? Ask an LLM to judge whether the auto-edited title still retains its original meaning? Run the old and new titles through an embedding model and make sure they still point in roughly the same direction?
oh interesting, TIL I can go edit my submission titles! That's useful, I've definitely submitted stuff and gotten a less-good title due to the automated fixes, so I'll have to pay attention to this next time
And the HTTP headers
Agreed--I clicked to read an article about the physics of time or something. Was sorely disappointed.
Title got mangled somehow, the original title is "This time is different".