Honestly judging from the volume of his output, a ton.
It’s rare to run into prodigious artists who simply produce a few perfect pieces - as a rule those few magnum opuses are built on a hill of cutting room floor scraps.
The director James Cameron stands out because he has only produced huge box office hits. Extremely hard to do like you said, and most artists and auteurs would be happy to have one great work they can be remembered for, even if it's amidst a dozen forgettable pieces.
I don’t know how to feel about HN thinking one of the greatest artist of all time produced slop. You guys really think Leonardo davinci was drawing ladies with 6 fingers before the Mona Lisa?
I assure the worst of Shakespeares work is far beyond anything most writers can produce, much less the incoherent slop LLMs generate
The problem is the infinite other literature produced along the way. It doesn't work to throw more monkeys at the problem of verification, and checking for matches against existing Shakespeare plays is cheating.
Right. The joke with shakespeares monkeys or borjes library is that you just do that and then filter out the books that match shakespeares works.
If you already know what you want in an infinite library, it is there. If you don't know exactly what you're looking for to the letter, you might not be able to find it.
Yes, because the folks waiting slack-jawed for the monkeys to finish will no longer have the skills or discernment to know what Shakespeare looks like.
And if in the end it does not produce masterworks, going faster and breaking things will be seen as a huge and credulous waste of time that poisoned the internet and some codebases beyond redemption.
But I’m glad someone else is running all these experiments so we can see who is right in their guess about the outcome.
2*128 is the UUID namespace, which is astronomical. That is like 21 letters. Making one sentence of Shakespeare by random search is strictly 0% chance. SHA256 is ~43 letters then. "LLM broke all of cryptography and creates random data to fit a hash" -- are we there yet?
Random search does not work at this scale. In all their cases, they played with pre-existing well-studied software, so they had an embedded fitness function. An extremely detailed one.
Monkeys have been reading Shakespeare all their lives (training). Effectively, this is LLM uncompression. Hence, "in Rust, from nothing but its documentation" -- not entirely true.
Yes it will be a terrible waste of time since dedicated humans can do it faster and produce better stuff. I would prefer literature created like that instead of just random monkeys writing what they don't understand. We also lose the ability for writers and creators to get better at their craft and produce unique works instead of just randoming spamming keys for millions of years
Isn't that the core fundamental of AI? Constrain the results to a latent space which has all the probable answers and then pick up whichever token makes sense based on your random sampling?
I feel like the whole concept of harness and LLMs IS to pick random tokens which make sense. Think about this as a solution space (a very complex one), then the harness and the LLM are moving towards the local minima at which the code is complete. This is akin to how we think about AI anyways.
Yes, agentic coding is machine learning. Not because of the underlying language models, but because it is gradient descent, where the test harness provides a gradient for the agent to traverse.