1,194 karma · joined October 9, 2009
But ingeniously, the simulator smoothly scales its speed as you zoom, totally erasing the fact of time. I wish there was an indicator somewhere of how much game time was going by per real-life second.
EDIT: ...but in order to do that you'd have to declare one of the levels to be the "bottom" level, the one that runs in real time, and that would ruin the fractalness of it all...
This pattern isn't unique – you could certainly come up with infinitely many more machines in Game of Life that do the same thing. But yes, most Game of Life patterns aren't fractal like this.
A country set up for global trade is not ready to lose access to that trade. They depend on things not produced locally, and depend on the proceeds of exporting things they produce in surplus. It would take decades to adapt by returning to a self-sufficient economy. And some goods (phones, for instance) could barely exist without global trade, so an embargoed country will lose access to those things inevitably.
Why not put a grayscale LCD panel behind the MicroLED screen to allow the display to be locally opaque? Control it with an alpha channel for the whole display. Then you could have windows or objects appearing to float in space, with full dynamic range available.
Am I being detained, Mr. Policeman?
“That's okay, I brought an Erector Set.”
“Throw a towel over it!”
“Do some pushups, Pablo, Maybe it’ll go away.”
Agreed; that’s why I was very careful to say “one approach.” I suspect that technique exploits a feature of the LLM’s sampler that penalizes repetition. This simple rule is effective at stopping the model from going into linguistic loops, but appears to go wrong in the edge case where the only “correct” output is a loop.
There are certainly other approaches that work on an LLM that wouldn’t work on a human. Similar to how you might be able to get an autonomous car’s vision network to detect “stop sign” by showing it a field of what looks to us like random noise. This can be exploited for productive reasons too; I’ve seen LLM prompts that look like densely packed nonsense to me but have very helpful results.
To me, "acting like a human" is quite distinct from being a human or being afforded the same rights as humans. I'm not anthropomorphizing LLMs so much as I'm observing that they've been built to predict anthropic output. So, if you want to elicit specific behavior from them, one approach would be to ask yourself how you'd elicit that behavior from a human, and try that.
For the record, my current thinking is that I also don't think ML model output should be copyrightable, unless the operator holds unambiguous rights to all the data used for training. And I think it's a bummer that every second article I click on from here seems to be headed with an ML-generated image.