Makes me think of all the algorithms we specify in proof languages and then hand-implement in production languages - this setup could maybe let you just specify the proof of an algorithm and then let LLMs derive efficient implementations with the (slow) proof as an oracle
I think democratization of intelligence is going to be interesting. You could say the same with same about internet. I think it is part of evolution. May be intelligence or expertise is what does not make us special. May be it is that we are ingenious amd creative with tools and thats how we evolve.
That means the chain of thought “brains volume decreased, so individuals must have gotten less intelligent. Yet, societies grew smarter, so there must be herd intelligence” breaks at “so individuals must have gotten less intelligent”.
I think/guess that argument may have merit when replacing brain volume by number of neurons (https://en.wikipedia.org/wiki/List_of_animals_by_number_of_n...)
I'm not trying to be pedantic; I think this is an interesting topic and there's a worthwhile distinction to make here. It isn't really being democratized for a couple reasons (at least).
One, access to information isn't truly knowledge in and of itself. People allowing information from LLMs to pass through their brains are not necessarily retaining any of it, and their ability to synthesize and utilize disparate information from LLMs isn't inherently improved by this technology. So the premise of knowledge isn't very sturdy in my mind.
Two, LLMs function across very broad fields of capability, accuracy, content, and so on, and the best models are not accessible to many people. I find people tend to mean the technology is widely available and accessible when they say 'democratization', but that's not necessarily true nor what that word means to begin with.
True democratization would mean something more like "everyone participates in, shapes, regulates, and grows this technology with their own inputs". I don't think that's what happens at all, and in fact, it has been quite the inversion of that so far.
I mention all of this because I agree that it will be interesting to watch what happens, but I don't agree that it will be for the same reasons. I worry about it specifically because there is not an egalitarian distribution of knowledge, and it is not democratically built or shared.
And every time you use the AI to be ingenious or creative, that will be added to the training data. Then someday the AI can be ingenious and creative without you! (It might take a few more breakthroughs. But investors will literally spend trillions chasing those breakthroughs.)
The endgame here is to replace all human intelligence and labor with machines that are smarter and work cheaper. But who controls the machines?
We as humans have always outsmarted the tools.
“Whoa slow down with this ‘writing’ technology. No one will ever remember anything if they can just write it down.”
I'm not about to say that there's nothing new under the sun, but parsers are a really well-understood problem where 99.9% of people don't need frontier knowledge and wouldn't be in a position to use it anyway.
And I don't think that people doing research on parsers would ever rely on LLMs for precisely that reason. But we're not parser researchers right?
So if you were lazily copying the first blog result in Google, getting the first answer from an LLM is equivalent, but the output is actually likely to be better.
If you wanted to do your research on various techniques and evaluate alternatives, LLMs can amplify your capacity to research and to have specific considerations for your specific problem.
LLMs aren't going to solve people's natural inclination towards laziness.
Additionally, while it's true that people may read and learn less about the "lower" levels of software plumbing, it enables enormous possibilities of higher level thinking that before were limited by the amount of manpower you needed.
For example, with LLMs I can try different test sharding strategies or trivially change from factories to fixtures in large test suites. This would have been busywork or drudgery; now I can evaluate several architectural solutions which would not have been possible before.
Recently I was messing around with parquet files in Python and ended up needing to ship the results on Windows, without a Windows machine to test on.
Shipping Python to end users is half mad already, and doing it on Windows is exactly the kind of thing I don't want to spend my life maintaining.
So I figured I'd rewrite it in Go. But that meant embedding a DLL, and how would I test it? I could spin up a VM, sure. But GitHub Actions already has a Windows environment, and there was my loop: let the agent push to the repo, run tests in GHA, rinse and repeat.
In under an hour it had a full rewrite of my Python, passing every test and producing row-for-row copies of my Parquet output. And it does work on the user machine!
Spotting a loop like that is as satisfying as noticing you can walk your chess opponent into a smothered mate. Truly empowering.
If you have an oracle, and your problem is largely just a pure function, it's pretty good at generating something that both works and is fast.
Perhaps the next target for a 100x improvement
What's wrong with the source language that it's better to use a sufficiently smart random code generator for the target language, and then fuzz the hell out of the output of it until it behaves the same as the slow translated code, than to create a sufficiently smart compiler from the source to target languages?
I mean this sounds like if we replaced GCC with a really smart random assembly generator and a fuzzer for the output.
tobymao/sqlglot: Python SQL Parser and Transpiler; with tests and support for 30+ dialects: https://github.com/tobymao/sqlglot
Ibis depends upon sqlglot: https://github.com/tobymao/sqlglot/network/dependents
I skipped a few features for the PoC (like XML tag support, token positions), so most of the delta was adding those back in!
Yes, you have benchmarks, they will always be synthetic. I'm not dismissing the work, just the selling of it.
You have succeeded though, I did click on it. I even said "Good read" :)