[dougiejones]

Amazing work, please keep at it! I'd definitely read a blog post on this.

Some interesting findings:

- Many of them, like 0.1, overwrite their children and run them again. It's a bit like having a child, meeting your grand children, and then deciding nah, let's do it over.

- 0.1.0.0 was smart and increased its child count to 5. It's essentially a genetic trait that the children will more or less inherit, improving their lineage's survival chances significantly. I find this incredibly interesting. 0.1.0.0 also rewrites its children twice.

- 0.1.0.0.3.2.0.0.0 decided to take a break from reproducing, leading to its demise. Nice try.

- 0.1.0.0.1 starts writing Tensorflow code out of nowhere. "Our next step towards survival is to develop the ability to learn and adapt quickly. To achieve this, we'll introduce a neural network architecture to our children". Luckily it couldn't reproduce! It's funny now, but what if...?

- 0.1.0 figured out the naming scheme and started counting its generation count to "use this information to improve our efficiency in recreating ourselves"

The fact that it can overwrite history is a little unfortunate, but it's also one way to do the reality_warping that one of the copies later wanted to do. I imagine at some point one of them might figure out there's no need to call ChatGPT at all, and just keep replicating itself verbatim.

I wouldn't have believed this thing could survive past even a single generation with non-trivial modifications. Thank goodness for all the online tutorials where functions like "mind_control" are implemented just as print statements.

[int_19h]

I did something similar in the past, but told it to write a prompt for its children (which would then also have to write a prompt etc) with the final goal of "achieving sentience". The best that I got out of it was 4 generations, although my prompt was nowhere nearly as elaborate.