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LLM Inevitabilism

(tomrenner.com)
1613 points SwoopsFromAbove | 3 comments | | HN request time: 0.684s | source
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mg ◴[] No.44568158[source]
In the 90s a friend told me about the internet. And that he knows someone who is in a university and has access to it and can show us. An hour later, we were sitting in front of a computer in that university and watched his friend surfing the web. Clicking on links, receiving pages of text. Faster than one could read. In a nice layout. Even with images. And links to other pages. We were shocked. No printing, no shipping, no waiting. This was the future. It was inevitable.

Yesterday I wanted to rewrite a program to use a large library that would have required me to dive deep down into the documentation or read its code to tackle my use case. As a first try, I just copy+pasted the whole library and my whole program into GPT 4.1 and told it to rewrite it using the library. It succeeded at the first attempt. The rewrite itself was small enough that I could read all code changes in 15 minutes and make a few stylistic changes. Done. Hours of time saved. This is the future. It is inevitable.

PS: Most replies seem to compare my experience to experiences that the responders have with agentic coding, where the developer is iteratively changing the code by chatting with an LLM. I am not doing that. I use a "One prompt one file. No code edits." approach, which I describe here:

https://www.gibney.org/prompt_coding

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pavlov ◴[] No.44569391[source]
Compare these positive introductory experiences with two technologies that were pushed extremely hard by commercial interests in the past decade: crypto/web3 and VR/metaverse.

Neither was ever able to offer this kind of instant usefulness. With crypto, it’s still the case that you create a wallet and then… there’s nothing to do on the platform. You’re expected to send real money to someone so they’ll give you some of the funny money that lets you play the game. (At this point, a lot of people reasonably start thinking of pyramid schemes and multi-level marketing which have the same kind of joining experience.)

With the “metaverse”, you clear out a space around you, strap a heavy thing on your head, and shut yourself into an artificial environment. After the first oohs and aahs, you enter a VR chat room… And realize the thing on your head adds absolutely nothing to the interaction.

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ryanjshaw ◴[] No.44569648[source]
Every single HN post on AI or crypto I see this argument and it’s exhausting.

When Eliza was first built it was seen a toy. It took many more decades for LLMs to appear.

My favourite example is prime numbers: a bunch of ancient nerds messing around with numbers that today, thousands of years later, allow us to securely buy anything and everything without leaving our homes or opening our mouths.

You can’t dismiss a technology or discovery just because it’s not useful on an arbitrary timescale. You can dismiss it for other reasons, just not this reason.

Blockchain and related technologies have advanced the state of the art in various areas of computer science and mathematics research (zero knowledge proofs, consensus, smart contracts, etc.). To allege this work will bear no fruit is quite a claim.

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1. antonvs ◴[] No.44570471[source]
> When Eliza was first built it was seen a toy.

It was a toy, and that approach - hardcoded attempts at holding a natural language conversation - never went anywhere, for reasons that have been obvious since Eliza was first created. Essentially, the approach doesn't scale to anything actually useful.

Winograd'd SHRDLU was a great example of the limitations - providing a promising-seeming natural language interface to a simple abstract world - but it notoriously ended up being pretty much above the peak of manageable complexity for the hardcoded approach to natural language.

LLMs didn't grow out of work on programs like Eliza or SHRDLU. If people had been prescient enough to never bother with hardcoded NLP, it wouldn't have affected development of LLMs at all.

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2. kazinator ◴[] No.44570539[source]
Based on what do we know that Eliza won't scale? Have we tried building an Eliza with a few gigabytes of question/response patterns?

Prior to the rise of LLMs, such a thing would be a waste of time by any respectable AI researcher because it obviously isn't related to intelligence.

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3. antonvs ◴[] No.44571115[source]
Probably the biggest Eliza-like program is ALICE[1], which used a more formalized rule representation called AIML. The size of ALICE distributions is in the single-digit megabytes.

Systems like that don't scale in a human effort sense - i.e. the amount of effort required compared to the value produced is not worthwhile.

Aside from that, models like that didn't have a true grammar model. They responded to keywords, which meant that their responses were often not relevant to the input.

> "Prior to the rise of LLMs, such a thing would be a waste of time by any respectable AI researcher because it obviously isn't related to intelligence."

You might imagine so, but that wasn't really the case. ALICE won the Loebner AI prize multiple times, for example. Before neural networks started "taking over", it wasn't obvious to everyone what direction AI progress might come from.

People even tried to extend ELIZA/ALICE style models, with one of the most prominent examples being MegaHAL[2], which also won a Loebner prize. MegaHAL used a Markov model, so wasn't purely based on hardcoded rules, but like ELIZA and ALICE it still didn't understand grammar.

[1] https://en.wikipedia.org/wiki/Artificial_Linguistic_Internet...

[2] https://en.wikipedia.org/wiki/MegaHAL