I recently did a deep dive on open-endedness, and my favorite example of its power is Picbreeder from 2008 [1]. It was a simple website where users could somewhat arbitrarily combine pictures created by super simple NNs. Most images were garbage, but a few resembled real objects. The best part is that attempts to replicate these by a traditional hill-climbing method would result in drastically more complicated solutions or even no solution at all.
It's a helpful analogy to understand the contrast between today's gradient descent vs open-ended exploration.
Built one for myself. It's context-aware and promptable.
Tested well on Linux, not so much on other platforms but in theory should support them.
It's a bit meta but I wrote it mostly using Claude Code. Once I had an MVP, I was able to prompt much faster by just speaking out what I wanted it to change.
I used to think that typing speed was not really that important, especially when now we have so many LLMs doing the typing for us. But honestly, now I think it's even more important because the specificity and detail in your prompts are paramount to getting a good response, and something like a dictation tool (which is what I'm using right now) is really good for generating very specific prompts.
In fact, I wrote all this out using a dictation tool in ~20 seconds (258 WPM).
Cursor is likely very tuned for Claude (prompts-wise and all) due to its dominance with 3.5 and now 3.7. Still, Gemini 2.5's tool calling has been pretty poor in my experience which Cursor heavily relies on.
Yep, it does some naive rescaling of the clock to make it circular (since perspective would make it more like an ellipse in the image), but then assumes 12 is always at the top.
