121–130 of 225 posts
not a single line of code was written by me by hand.
but damn many prompts.
Earlier quoted context omitted.
I see this as an example of the reverse: AI is still stupid enough that it takes humans a degree of skill to craft a request which generates the desired output.
From what I've seen, the problem is not with the GPT models, but the people themselves. Almost everyday I get multiple unstructured, unclear and often without required context requests from people that I need to iterate back and forth with additional questions to get a clear view what they're trying to achieve. The only thing GPT is "stupid enough" is that it's not prompted to ask questions back to clarify the reques…
This is not really the same, but may be interesting to some: I subscribe to ChatGPT plus for a month to check out GPT-4. The rate limits were cumbersome though and it can be easy to waste a prompt, so I started to bootstrap: I would explain my problem to 3.5 and ask it to suggest comprehensive prompts to use with 4 to maximize my limited quota. It worked very well. In the long years to come the most advance AIs may b…
- When you first start, tell ChatGPT about the limitation. Example - “I’m only allowed to send you 25 prompts every 3 hours. As a result, I need you to keep track of the messages I send you. At the end of each response you give me, please tell me how many prompts I have left, ex: this ‘X/25’”
- Combine multiple questions into one prompt, and tell ChatGPT how to handle it. Example “I need help doing X, Y and Z. Please provide all of the details I need for each task, separating your answer for each with ‘—————‘“. Your prompts can be quite long, so don’t hesitate to jam a lot into a single prompt. Just be sure to tell ChatGPT how to handle it, or you’ll end up with shallow answers for each.
- Provide an excruciating amount of detail in your prompts to avoid having to waste other prompts clarifying. For example, let’s say I’m encountering an issue in an app I’m building. I will tell ChaGPT what the issue is, share the relevant parts of my code (striping out any details I don’t want to share), and tell it the expected behavior. This could be dozens of lines of code, multiple files, etc. It can all be one prompt.
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The cool tool makes another cool tool, which in turn makes another cool tool, faster and faster, until we really don't understand at all what the latest cool tool is doing. But it just keeps getting smarter/faster/more effective/whatever it's optimizing for. That's the basic definition of "the singularity".
What never was so clear to me in that vision is, how the version n actually makes sure the version n+1 is actually faster and better. Initially there might be the easy option of using more tokens/memory/ . But when that becomes impractical, how will the "dumber AI" select between x generated "smarter AIs"? How will it ensure that the newly generated versions are better at all (if there are no easily measurable parame…
I directed chatGPT to code https://chrome.google.com/webstore/detail/franz-ai-text-rewr... a chrome extension which rewrites any content in place on any website. not a single line of code was written by me by hand. but damn many prompts.
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GPT-4 32k can fit a few thousand lines of code into a single prompt and output diff's, patches, and/or the fully modified code. For best results, pasting any relevant documentation into the prompt can help.
Is there word of ane outside big co's getting access to 32k ? I got 8k access pretty quickly but no word whatsoever about 32k (and my current prompts + context already reach 8-9k tokens)
Earlier quoted context omitted.
What never was so clear to me in that vision is, how the version n actually makes sure the version n+1 is actually faster and better. Initially there might be the easy option of using more tokens/memory/ . But when that becomes impractical, how will the "dumber AI" select between x generated "smarter AIs"? How will it ensure that the newly generated versions are better at all (if there are no easily measurable parame…
You have it optimize towards reasoning tests, not tokens or memory. It’s like if you were optimizing a race car. You make the explicit goal time around the track, not horsepower or weight.
Every post that claimed using ChatGPT to achieve non-trivial tasks turned out to have non-trivial human intervention. > (from the original article) In fact, I found it better to let ChatGPT generate a toy-ish version of the code first, then let it add things to it step-by-step. This resulted in much better output than, say, asking ChatGPT to generate production-quality code with all features in the first go. This als…
I had chat gpt 3.5 build a small web app for me too. I have since been building some tooling for this sort of GPT-assisted programming. https://github.com/paul-gauthier/easy-chat
I've had GPT3.5 teach me how to make a watchOS application to control a BLE device, and after a couple evenings I have one working on my watch right now.
On the bright side, it gave some concrete hands-on guidance that I just wasn't been able to get from Apple documentation. It quickly gave me enough pointers to make things click in my head. While I've never wrote a single line for any Apple ecosystem before, I have a fair amount of experiences in various other niches, so I just needed a crash-course introduction showing me the ropes until I start to see the similarities with things I already know about - and it gave me exactly what I wanted. Unlike beginner "write your first app" blog articles, this crash course was tailored specifically to my requirements, which is incredibly helpful.
However, on the downside, the code it wrote was awful, lacking any design. It gave me enough to get familiar with Swift syntax and how to setup CoreBluetooth, but the overall architecture was non-existent - just some spaghetti that kind-of worked (save for some bugs that were easier to fix on my own than explain to GPT) in my described happy scenario. It was like a junior developer would've grabbed some pieces from StackOverflow. In my attempts to bring things to order, I've hit a knowledge cutoff barrier (it has no clue about latest Swift with new its async syntax or Xcode 14 specifics - as a few things were moved around) and heavy hallucinations (ChatGPT actively trying to refer to various classes and methods that never existed).
Still, I'm impressed. Not a replacement for a developer, but definitely a huge boon. Wonder what others' experiences and opinions are.