Testing GPT 4's code-writing capabilities with some real world problems

I think outstanding software will still require well-paid, competent people orchestrating and developing a lot of complex systems for a while yet… But there’s a ton of bad software out there that will be able to be maintained for far less, and I suspect a lot of companies will be drawn to creating cookie cutter products generated by LLMs.

Just as people have turned to stores and blogs generated on templated systems, I think all of that and more will continue but with even more of it handled by LLM-based tooling.

I don’t think it’ll be next week, but I suspect it’ll be less than 10 years.

Some people expect that’ll lead to more software existing which will inevitably require more develops to oversee, but if that’s the case, I suspect they will be paid a lot less. I also expect that once AI tools are sophisticated enough to do this, they will largely make that level of oversight redundant.

Soon they could potentially patch the bugs in the software they generate by watching Sentry or something. Just automatically start trying solutions and running fuzz tests. It would be way cheaper than a human being and it would never need to stop working.

I suspect if you poked GPT-4 just right (starting with a detailed design/analysis phase?) it could find a rhetorical path through the problem that resulted in a correct algorithm on the other end. The challenge is that it can't find a path like that on its own.

Op: Can you get it to write your algorithm for this problem if you describe it in detail, as-is?

I suspect the difficulty here is just finding a socratic part to that description, which would tend to be rare in the training material. Most online material explains what and how, not why; more importantly, it doesn't tend to explain why first.

The morale is that it’s always better to have unique hard won skill sets that others don’t. Double down on those. Think of LLMs as freeing you to do more interesting high level tasks. Rather than having to build those menial tasks, what if you focused on your creativity getting the AI to build new types of product or gain new insights that peers aren’t considering. What if you leveraged the AI to build prototypes of ideas you wouldn’t have to otherwise?

Of course that’s easier said than done. For now, take comfort in the fact that no one is seriously trusting this as anything more than a glorified autocomplete (if that).

No surprise because GPT-4 is built upon the same model as GPT-3. Clever Engineering will bring us far, but breakthrough requires change of the fundamentals.

Nevertheless, it’s useful and can helps us solve problems when we guide it and split the work into many smaller subunits.

I believe the goal is to find a path with the fewest possible "fire" cells and the minimum cost as a tie breaker. The cost of a path is the sum of its cells' cost and it can't be greater than 5.

If I understood the assignment correctly, I don't think the problem statement is equivalent to what's included in the prompt. Specifically, the prompt doesn't clarify what happens if you have to cross through multiple "fire" cells.

> Fire tiles cost 1 point to move through, but they should avoid pathing through them even if it means taking a longer path to their destination (provided the path is still within their limited movement range)