Comment by _5tsv | Hacker News Reader

Comment by _5tsv | Hacker News Reader

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I remember when bitcoin was taking off, and everyone instantly started saying "bitcoin may not win but one thing is for sure, the **blockchain** is here to stay." Then 15 years went by and the crypto market is basically bitcoin, which won as a store of value, and then a long tail of shitcoins that were "unlocked by the blockchain as a platform."

AI feels to me like it's in a similar state. ChatGPT was a genuinely exciting breakthrough, and because of the previous example of web, everyone instantly wants to see "LLMs as a platform" take off. This has not happened whatsoever. I literally only use ChatGPT. I don't even use Copilot because it's janky and doesn't solve any real problems for me. I guess I sometimes use the RAG-based applications (like docs pages now support a ChatGPT interface), but these are basically ChatGPT with some extra context injected in-- so, ChatGPT. You talk to any of these AI companies and they all admit they're just using the AI label to fundraise and behind the scenes it's either a CRUD app or the thinnest GPT integration in front. I literally don't use any other AI applications. They're all annoying and flooding the web and it is pure clutter everywhere that adds no benefit ever, all because everyone wants to see "LLMs as a platform."

I grew up being a huge fan of YC, and I would respect them so much more if they would take the contrarian (but in my humble opinion correct) view and say actually, judging by the structural evidence and actual results, it's not clear what exactly AI has to offer right now, and we're going to return to PG's founding philosophy and continue funding unsexy and unpopular but ultimately actually important things.

> AI feels to me like it's in a similar state.

Apple has heavily integrated AI into it's systems and apps. Every other major tech company is actively adding it to their apps and systems in many different ways. They aren't talking about future potential. We are years past that already. It's here. That's it. We aren't trying to convince people that AI is here to stay. Rather, we are already talking about a post-AI/LLM world. Crypto never really got to that state.

What was crypto's big thing? Ape pictures.

> I literally don't use any other AI applications.

Linux users will get there too. Especially if you start using ANY tech used by any of the major players. You are already using it, and you don't even realize it.

I suppose we'll see. I use a Mac and iPhone and the internet like everyone else and personally I find almost all the AI stuff they're pushing to be annoying, unnecessary and not solving any actual problems I have. Like believe me, I'm the laziest person alive and if AI is going to make my life easier, it's like, where do I sign up? ChatGPT does make my life better and accordingly I happily pay them the twenty bucks every month. But every time I try one of these AI thingies it ends up being a disappointment. Time will tell if the emperor's clothes come off at some point, or if I'm just a grumpy luddite.

> I suppose we'll see. I use a Mac and iPhone and the internet like everyone else

So, you are already using more than just ChatGPT. And we both know you aren't going to switch off Mac and iPhone.

> Time will tell

23 hours... so yeah, not long at all.

"You're already using it, and you don't even realize it."

With all the hype it would be quite difficult to not "realize" where it is allegedly being used. There is a comical effort to claim that "AI" is being used in everything.

The trick is to extend the definition of AI to any statistical method, or recently, conditional logic.

Well, we, as developers, need to adapt to changing market conditions just like everyone else.

Apple is being smart and prompting the user to accept going to ChatGPT for LLM searches so that the user knows it's not apple when it hallucinates..

Cryptos big thing is buying drugs online.

Don’t forget VPNs.

> I literally only use ChatGPT.

I also use Claude Opus for activities that need large context window. But the second a better alternative appears, most people will switch to it. Because - why not?

The market already stabilized somewhat - you can use lower quality models locally for simpler stuff and paid models (better quality in case of ChatGPT-4, larger context window for Claude Opus[0]) when you need something more advanced.

[0] I'm not sure what is the current status of Gemini Pro with 1M context window, but from what I heard it's too expensive for any practical use.

Dismissing the potential of the current wave of AI as overhyped because "I literally only use ChatGPT" is like someone in 1985 dismissing computers as overhyped because "I literally only use WordPerfect". You're missing out on what all the other computers are being used for.

The current wave of model development, sharing, and fine-tuning is creating a technical ecosystem that supports making computer programs that are able to interact with unstructured data in ways that historically have been impossible.

That most people have only seen that used to make a chatbot that can answer unstructured questions with unstructured and occasionally hallucinated answers says nothing about the profound ways those capabilities will shift what kinds of problems we point computers at in the future.

Let's take a classic cataloging problem like managing a small library inventory. Say you're a software company and you have a few bookshelves of programming books people can borrow. And you want to make it possible for people to search the list of books you have in stock to see if there's something they want to borrow before they walk down. This is classic Web 1.0 stuff - a mySQL database with a books table and an authors table, indulge your third normal form fetish. And maybe you integrate with an ISBN catalog by sending it nicely structured XML queries so you can use a scanner to scan the barcodes, pull down and transform structured data about each book, and use it to populate your database. Make an old school HTML form to search it by title, author, publisher, date, etc...

Nowadays, you can take a picture of the spines on the shelves; ask a multimodal AI to figure out what books that means you've got; feed that, plus plain text search access to an online catalog, to another model to get it to build a nice big document describing all the books; feed that as context into a chatbot librarian and let it help users find books. Set up a webcam pointing at the shelf and periodically take new pictures to keep track of who took what books.

Think about the massive amounts of efforts businesses go to to create information technology systems to structure the state of their business, interactions among their employees, data about their customers and suppliers, integration with external systems, and to schematize and constrain the processes of their business. And now start to think about how that all changes when I can skip the structure part.

We are not yet used to thinking about how to solve problems with computers that don't need their inputs to be rigorously structured. When we start realizing what that means, we're in a different game entirely.

I get what the optimism is about in theory. Parsing unstructured data is something we can now do that we couldn't before. It adds a whole new vector to the span of software, a big piece of capability that software now has whose emergent, unforeseen consequences we can't predict.

I'm just not quite sure I buy this. It feels to me like there's a light motte-and-bailey going on, where supposedly AI is going to be a paradigm shift that changes the very notion of what's possible, but the actual proposals are mostly about LLMs being a finite-multiplier enhancement for the existing ability of software to model and optimize processes.

In particular, a big fraction of the concrete proposals seem to be about making business processes more efficient. Are businesses generally constrained by this to begin with? Like businesses don't seem to be sprinting at the edge of software technology to get as much efficiency as they can, buying diminishing returns from existing tech and waiting eagerly for the next wave of improvements. Judging by revealed preferences, it just doesn't seem like a very high priority for them.

Taking your automated library example, that sounds very cool from a hacker/tinkerer perspective and I'm sure it would result in some efficiency improvements, but it just doesn't seem like, no offense to anyone, a problem that needs urgent attention. How does this significantly improve the situation for anyone involved?

Of course it's true that we don't know what we don't know, and I don't disagree that often technology changes the world in unpredictable ways or even that current AI could possibly lead to this. At risk of being the dropbox-is-just-rsync guy, I'm just skeptical about the following pattern:

(1) some new tech gets invented that's supposedly the next internet;

(2) no one can quite explain or plausibly hypothesize how; but

(3) in the meantime, a wave of companies start building "platforms" and selling shovels to people who will supposedly later build the actual useful thing.

I like using local LLMs via SillyTavern for roleplaying, which is fun, but is not going to be a source of revenue for anyone.

One of the things I dislike about the multitude of get-rich-quick crypto scene so much is that many projects disproportionately punished people for trying out new technology and being early adopters. The scar tissue of that is going to be hard to unlearn. I think that “ai” as in generative models right now is under-hyped by a lot of people who dismiss it as another solution in search of a problem similar to blockchains, but it’s difficult to argue it’s under-hyped by the market overall with these insane valuations assuming realistic % chances of ASI right around the corner.

I think a better analogy might be self driving cars: probably going to be as impactful as early hype people guessed eventually, but on much longer timescales than people originally thought.

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