https://evanthebouncy.github.io/program-synthesis-minimal/
Here's my take on it, you can view it as a modern extension to Armando's work (he's my PhD advisor)
Readit Newsevanthebouncy commented on Introduction to Program Synthesis people.csail.mit.edu/asol... · Posted by u/squircle
evanthebouncy commented on A Minimalist Guide To Program Synthesis evanthebouncy.github.io/p... · Posted by u/optimalsolver
Kind of unrelated, but I love this blogs typography.
it is very related, and I spent an ungodly amount of time to make sure it is visually compact and to the point, so I can deliver knowledge directly into your eye holes with minimal friction. It's super heartwarming to see someone appreciating this aspect.
evanthebouncy commented on A Minimalist Guide To Program Synthesis evanthebouncy.github.io/p... · Posted by u/optimalsolver
This is a GREAT resource, thanks for posting.
I feel the advent of GPT-3 / Codex and the power that comes with it has been surprisingly underestimated - maybe because the folks who would benefit most from it (people who don't write code, like myself) haven't really caught up with it, while the ones using it (mostly people who do write code) maybe don't see the immediate benefits as much (and maybe are a little bit concerned about what this will mean to their economic position in all this...?)
I've played around a ton with simple GPT-3 code over the last few weeks and am in total awe of the possibilities this opens up to folks like me (who don't write code)
E.g. I had GPT-3 write me app script integrations of itself (!) and stablediffusino into a Google Sheet, allowing me to build a massive sandbox playground for various prototyping experiments.
Here's a thread on that process if you're curious: https://twitter.com/fabianstelzer/status/1577416649514295297
yes. reading some of your twitter posts I'd say I share your sentiment on how codex will upend the programming world. but I think better integrations and statement of intents need to be more fleshed out, given openAI & friends are tech companies and not user companies, the UX part will take time.
evanthebouncy commented on A Minimalist Guide To Program Synthesis evanthebouncy.github.io/p... · Posted by u/optimalsolver
> large language models
Can you clarify what this means? In this context seems like it could mean either machine learning language model or programming language grammar/semantics.
I meant gpt3 and its cousins.
evanthebouncy commented on A Minimalist Guide To Program Synthesis evanthebouncy.github.io/p... · Posted by u/optimalsolver
Thank you for posting this. Code generation is an interest of mine and a core foundation of the technology that I build.
It will take me some time to read through this blog, but I have a question:
Is there any research being done where people are using large language models to generate or transform syntax trees for programs as opposed to operating with programs as simply streams of tokens?
Here's an obtuse answer.
The operations that transform syntax trees are just programs as well which... Can be represented as a steams of tokens.
But this is likely helpful if it makes it easier to learn by the NN. I'm certain there are works that do this, but not off the top of my head rn
evanthebouncy commented on A Minimalist Guide To Program Synthesis evanthebouncy.github.io/p... · Posted by u/optimalsolver
Hiyo I'm the author xD
Feel free to ask me questions uhhh... How does hacker news work lmao do i get notifications even hmm.
I'll uhh... refresh this page once in awhile and see if I can help!
if that don't work prolly just ping me on twitter.
For example, if we can cache/re-use the compiler run on previous codegen candidates, to speed up compilation of the next candidate sniplet
I wouldn't worry about speeds. We should expect compute and inference to be faster in the future, where we can sample easily 10k programs in a second, check all of them against test cases.
I'd worry about communicating precisely to computers when test cases are awkward to write.