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Comment by ogogmad | Hacker News Reader

I think using these tools might become a science or an art form in its own right. You'll have to give these tools the input they need to produce the most useful answers to you. In the short term at least, this is not going to take away your need to think. But it might change how you think, and it might make you more productive when your problem aligns well with these tools.

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I think that you are correct, we will see AI used as a copilot for artists and content creators. I have had access to the OpenAI APIs for GPT-3 since last summer, and in addition to using this for NLP tasks, I have also experimented with using GPT-3 to help me work on a sci-fi short book that I have been occasionally writing for years. It has been useful for expanding sections that I have been stuck on. I feel that I should copyright my story as being authored by The Internet since every content creator whose text, programming listings, etc. that goes into training these language models has in some sense been a contributor to my short story.

This gives me an idea.

You know how you can break writing down into 2 phases: creative and edit?

What if you did the creative part, braindumping all your ideas and vision into a word document. Then had an AI edit your incoherent story into engaging prose.

I find the creative part easy, but the editing part tedious.

Like, a doctor I know asked me to write a review for him. I did the braindump part, but have been procrastinating on the edit part.

Unfortunately, GPT-3, CoPilot, AlphaCode, etc., also excel more at the creative part (helped out by their enormous training database, which saves you from doing the Google search to match your high-level description to examples), but they're still dogshit at editing, because that is the part that actually requires a detailed understanding of the text. So the princess is still in the next castle.

Hmm it intuitively seems like the editing part should be the easy part, because the output is basically a template, and you just need to fill it in, and tweak it a little bit…

I get with code it’s a bit less so, but still, there are plenty of design patterns which basically cover a lot of the output space…

The context window of GPT-3 is vanishingly small compared to any novel-like work. GPT-3 will happily invent descriptions of characters and objects that contradict what it suggested three pages ago.

Not saying it can't help you with getting an idea what to describe, but this is the kind of "editing" that it won't be good at.

I think these tools push in the other direction.

You get the tool to brain dump for you, then you edit after

I haven’t used copilot, but don’t you specify what you want first, in comment form, then copilot spits it out?

I get that you have to do subsequent editing, because it’s not perfect.

Potentially, but that doesn't address the problem of replacing writing code with the (harder) process of reading, verifying and fixing it. However well I engineer my inputs I'll still have to review, verify and fix the outputs.

This problem has been (albeit imperfectly) addressed in speech recognition. When error corrections are made through the the UI the engine can learn from those corrections. Presumably over time the corrections needed in alphacode will become more semantic than syntactical. But you're right, correcting subtly flawed code or text is way harder than writing from scratch.

One of the most difficult problems in software development in general is coming up with the right test cases that cover the real-world domain's needs. If you have an AI like this at your disposal, that you can throw test cases at and it will give you the stupidest piece of code that makes them pass, then at the least you have something that helps you iterate on your test cases a lot more effectively, which would be a great boon.

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