Yeah you'd think the rapid obsolescence of the hardware would dampen P/E ratios a little. It has to pay for itself quickly.

P/E is, after all, given in the implied unit of "years". (Same as other ratios like debt/GDP).

Can't speak for anyone else, but for me, AI/LLMs have been firmly in the "nice but forgettable" camp. Like, sometimes it's marginally more convenient to use an LLM than to do a proper web search or to figure out how to write some code—but that's a small time saving at best, it's less of a net impact than Stack Overflow was.

I'm already a pretty fast writer and programmer without LLMs. If I hadn't already learned how to write and program quickly, perhaps I would get more use out of LLMs. But the LLMs would be saving me the effort of learning which, ultimately, is an O(1) cost for O(n) benefit. Not super compelling. And what would I even do with a larger volume of text output? I already write more than most folks are willing to read...

So, sure, it's not strictly zero utility, but it's far less utility than a long series of other things.

On the other hand, trains are fucking amazing. I don't drive, and having real passenger rail is a big chunk of why I want to move to Europe one day. Being able to get places without needing to learn and then operate a big, dangerous machine—one that is statistically much more dangerous for folks with ADHD like me—makes a massive difference in my day-to-day life. Having a language model... doesn't.

And that's living in the Bay Area where the trains aren't great. Bart, Caltrain and Amtrak disappearing would have an orders of magnitude larger effect on my life than if LLMs stopped working.

And I'm totally ignoring the indirect but substantial value I get out of freight rail. Sure, ships and trucks could probably get us there, but the net increase in costs and pollution should not be underestimated.

> Can you explain how you don't find clear utility, at the personal level, from LLMs?

Sure. They don't meaningfully improve anything in my life personally.

They don't improve my search experience, they don't improve my work experience, they don't improve the quality of my online interactions, and I don't think they improve the quality of the society I live in either

There was a study recently that showed how not only did devs overestimate the time saved using AI, but that they were net negative compared to the control group.

Anyway, that about sums up my experience with AI. It may save some time here and there, but on net, you’re better off without it.

I actually do get clear utility, with major caveats, namely that I only ask things where the answer is both well known and verifiable.

I still do 10-20x regular Kagi searches for every LLM search, which seems about right in terms of the utility I'm personally getting out of this.

As a dev, I find that the personal utility of LLMs is still very limited.

Analyze it this way: Are LLMs enabling something that was impossible before? My answer would be No.

Whatever I'm asking of the LLM, I'd have figured it out from googling and RTFMing anyway, and probably have done a better job at it. And guess what, after letting the LLM do it, I probably still need to google and RTFM anyway.

You might say "it's enabling the impossible because you can now do things in less time", to which I would say, I don't really think you can do it in less time. It's more like cruise control where it takes the same time to get to your destination but you just need to expend less mental effort.

Other elephants in the room:

- where is the missing explosion of (non-AI) software startups that should've been enabled by LLM dev efficiency improvements?

- why is adoption among big tech SWEs near zero despite intense push from management? You'd think, of all people, you wouldn't have to ask them twice.

The emperor has no clothes.

Much work is not "text in, text out", and much work is not digital at all. But even in the digital world, inserting an LLM into a workflow is just not always that useful.

In fact much automation, code or otherwise, benefits from or even requires explicit, concise rules.

It is far quicker for me to already know, and write, an SQL statement, than it is to explain what I need to an LLM.

It is also quite difficult to get LLMs into a lot of processes, and I think big enterprises are going to really struggle with this. I would absolutely love AI to manage some Windows servers that are in my care, but they are three VMs deep in a remote desktop stack that gets me into a DMZ/intranet. There's no interface, and how would an LLM help anyway. What I need is concise, discreet automations. Not a chat bot interface to try and instruct every day.

To be clear I do try to use AI most days, I have Claude and I am a software developer so ideally it could be very helpful, but I have far less use for it than say people in the strategy or marketing departments for example. I do a lot of things, but not really all that much writing.

Gemini wasted my time today assuring me that if I want a git bundle that only has the top N commits, yet is cleanly clone-able, I can just make a --depth N clone of the original repo, and and do a git bundle create ... --all.

Nope; cloning a bundle created from a depth-limited clone results in error messages about missing commit objects.

So I tell the parrot that, and it comes back with: of course, it is well-known that it doesn't work, blah blah. (Then why wasn't it well known one prompt ago, when it was suggested as the definitive answer?)

Obviously, I wasn't in the "the right mindset" today.

This mindset is one of two things:

- the mindset of a complete n00b asking a n00b question that it will nail every time, predicting it out of its training data richly replete with n00b material.

- the mindset of a patient data miner, willing to expend all they keystrokes. needed to build up enough context to in effect create a query which zeroes in on the right nugget of information that made an appearance in the training data.

It was interesting to go down this #2 rabbit hole when this stuff was new, which it isn't any more. Basically do most of the work, while it looks as if it solved the problem.

I had the right mindset for AI, but most of it has worn off. If I don't get something useful in one query with at most one follow up, I quit.

The only shills who continue to hype AI are either completely dishonest assholes, or genuine bros bearing weapons-grade confirmation bias.

Let's try something else:

Q: "What modes of C major are their own reflection?"

A: "The Lydian and Phrygian modes are reflections of each other, as are the Ionian and Aeolian modes, and the Dorian and Mixolydian modes. The Locrian mode is its own reflection."

Very nice sounding and grammatical, but gapingly wrong in every point. The only mode that is its own reflection is Dorian. Furthermore, Lydian and Phrygian are not mutual reflections. Phrygian reflected around is root is Ionian. The reflection of Lydian is Locrian; and of Aeolian, Mixolydian.

I once loaded a NotebookLM with materials about George Russel's concept of the Lydian Chromatic, and Tonal Gravity. It made an incomprehensible mess of explaining the stuff, worse than the original sources.

AI performs well on whatever is the focus of its purveyors. When they want to shake down entry-level coding, they beef it up on entry-level coding and let it loose, leaving it unable to tell Mixolydian from mixing console.

Like other commenters here, when I try to use them to help with my work, they don't. It's that simple. I have tried AI coding assistants, and they just guess incorrectly. If I know the answer, they generally give me the same answer. If I don't know the answer, they give me gibberish that ends up wasting time. I would love to look over the shoulder of an AI booster who had a really good interaction, because it's hard for me to believe they didn't just already know what they were looking for.

I think that there's a strong argument to be made that the negatives of having to wade through AI slop outweights the benefits that AI may provide. I also suspect that AI could contribute to enshittification of society; e.g. AI therapy being substituted for real therapy, AI products displacing industrial design, etc.

Last night, I asked a LLM to produce an /etc/fstab entry for connecting to a network share with specific options. I was too lazy to look up the options from the manual. It gave me the options separated by semicolons, which is invalid because the config file requires commas as separators.

I honestly don't see technology that stumbles over trivial problems like these as something that will replace my job, or any job that is not already automatable within ten thousand lines of Python, anytime soon. The gap between hype and actual capabilities is insane. The more I've tried to apply LLMs to real problems, the more disillusioned I've become. There is nothing, absolutely nothing, no matter how small the task, that I can trust LLMs to do correctly.

IMO I think it is a combination of being a really great programmer already and then either not all that intellectually curious or so well read and so intellectually curious that LLMs are a step down from being a voracious reader of books and papers.

For me, LLMs are also the most useful thing ever but I was a C student in all my classes. My programming is a joke. I have always been intellectually curious but I am quite lazy. I have always had tons of ideas to explore though and LLMS let me explore these ideas that I either wouldn't be able to otherwise or would be too lazy to bother.

The concerning thing is that AI contrarianism is being left wing coded. Imagine you’re fighting a war and one side decides “guns are overhyped, let’s stick with swords”. While there is a lot of hype about AI, even the pessimistic take has to admit it’s a game changing tech. If it isn’t doing anything useful for you, that’s because you need to get off your butt and start building tools on top of it.

Especially people on the left need to realize how important their vision is to the future if AI. Right now you can see the current US admin having zero concern for AI safety or carbon use. If you keep your head in the dirt saying “bubble!” that’s no problem. But if this is here to stay then you need to get involved.

The worst thing in the information space is bullshit. It's worse than lies because it's slicker. LLMs generate extremely dangerous bullshit that can be difficult to correct. Advice given may apply to old versions, outdated legal precedent, or radical opinions. Fully understanding nuance or mistakes can take a lot of effort and still be off.

Railroads move people and cargo quickly and cheaply from point A to point B. Mechanized textile production made clothing, a huge sink of time and resources before the industrial age, affordable to everybody.

What does AI get the consumer? Worse spam, more realistic scams, hallucinated search results, easy cheating on homework? AI-assisted coding doesn't benefit them, and the jury is still out on that too (see recent study showing it's a net negative for efficiency).

The luddites were often the ones that built the mechanized looms. They had nothing against mechanized looms, they had everything against the business owners using their workers talents and knowledge to build an entire operation only to later undercut their wages and/or replace them with lesser paid unskilled workers and reduce the quality of life of their entire community.

Getting people to associate the luddites as anti-technology zealots rather than pro-labor organization is one of the most successful pieces of propaganda in history.

Luddites weren’t anti technology at all[0] in fact they were quite adept at using technology. It was a labor movement that fought for worker rights in the face of new technologies.

[0]: https://www.newyorker.com/books/page-turner/rethinking-the-l...

Apples to oranges.

Luddites weren't at a point where every industry sees individual capital formation/demand for labor trend towards zero over time.

Prices are ratios in the currency between factors and producers.

What do you suppose happens when the factors can't buy anything because there is nothing they can trade. Slavery has quite a lot of historic parallels with the trend towards this. Producers stop producing when they can make no profit.

You have a deflationary (chaotic) spiral towards socio-economic collapse, under the burden of debt/money-printing (as production risk). There are limits to systems, and when such limits are exceeded; great destruction occurs.

Malthus/Catton pose a very real existential threat when such disorder occurs, and its almost inevitable that it does without action to prevent it. One cannot assume action will happen until it actually does.

With this generation of AI, it's too early to tell whether it's the next railroad, the next textile machine, or the next way to lock your exclusive ownership of an ugly JPG of a multicolored ape into a globally-referenceable, immutable datastore backed by a blockchain.

The mechanical loom produced a tangible good. That kind of automation was supposed to free people from menial work. Now they are trying to replace interesting work with human supervised slop, which is a stolen derivative work in the first place.

The loom wasn't centralized in four companies. Customers of textiles did not need an expensive subscription.

Obviously average people would benefit more if all that investment went into housing or in fact high speed railways. "AI" does not improve their lives one bit.

They laughed at Einstein, but they also laughed at Bozo the Clown.

This sort of “other people were wrong once, so you might be too” comment is really pointless.

I mean, for them it probably was.

a data centre is a big warehouse

the vast expense is on the GPU silicon, which is essentially useless for compute other than parallel floating point operations

when the bubble pops, the "investment" will be a very expensive total waste of perfectly good sand

> Reusing so many GPU's might be harder

It could have some unexciting applications like, oh, modeling climate change and other scientific simulations.

'It's debatable whether or not they'll achieve that, but if you actually look at what the goal is, the investment makes sense.'

The first clause of that sentence negates the second.

The investment only makes sense if the the expectation of success * the investment < the payoff of that goal.

If I don't think the major AI labs will succeed, then it's not justified.

AGI is not even a well-defined goal, let alone one that can be reasonably expected from the current tranche of investment. By your logic, any investment makes sense - this is not investment at all, it is a gambling addiction.

what? crashing the economy for a psychotic sci-fi delusion "makes sense"? how?