unknown-horizons VS OpenWorm

Open Horizons (Anno-like?)

In case you didn't know about it you might be interested in contributing to https://unknown-horizons.org/

Unknown Horizons is inspired by the Anno series. Not exactly the same, but also a city builder with resource management.

Not mentioned yet:

Unknown Horizons https://unknown-horizons.org/

I suggest you google for "open source [genre]" or something like that. There are games like FreeCiv (Civilization 2 clone), FreeCol (Colonization clone), 0AD (medieval but maybe too much strategy oriented), Unknown Horizons (Anno clone) or Wildelands (Settler 1/2 clone).

OpenRCT2 UnReal World Unknown Horizons Freeciv Haven & Hearth

Unknown Horizons

0 A.D. , Unknown Horizons , NetHack , FreeOrion , Minetest

So I have three thoughts about this.

The first is cell specialization, particularly neurons. It seems like nature really came up with a universal neuron. There aren't neurons for eyesight vs thinking, etc. They've experimented with this on frogs where they've reweired the optic nerve to a different part ofd the brain and the frog seems to see just fine. They've even added an eye and the frog seems to cope and use it just fine.

The second is the OpenWorm project [1]. This is an attempt to simulate a relatively simple organism with IIRC ~280 neurons. Despite lots of effort, the simulated version just doesn't match up to the real thing. In artificial neural networks we have a stupidly simplified model of neurons that tends to get reduced to a binary signal and an activation function. Thius can do a lot but it's clearly wholly inadequate for any realistic modelling. The protein interactions in a cell are mind-bogglingly complex.

The third is the three-body problem. To summarize, we have a general solution for the grvity interactions of two bodies. Add one more and we don't. We have classes of solutions but no general solution. This is why JPL needs to use supercomputers to calculate flight plans with a relatively low number of bodies. We see a relatively simple set of interactions lead to massive complexity with protein folding. I imagine that it just won't be computationally viable to simulate even a single realistic cell given all th einteractions that go on. We're simply left to make estimations.

[1]: https://openworm.org/

> And this will not just be in government, it will be everywhere. The scariest part is that as people start to spend less time developing a skill set, and instead deferring to AI answers, you will cross a point where this problem can't be fixed (because nobody has the skills to fix it and the AI is trained on the outputs of previous generations of humans).

I think that would require AI development to approximately halt at close to the current level for over a lifetime.

Conditional on development halting, I'd agree with you. By analogy, there's this single, very useful, very powerful, set of "hidden methods that can be used to win all games, get rich, find love, determine the limits of thought itself!" — mathematics[0]. Do people like learning it? They do not. Calculator much easier. What a calculator does is none of that, calculators are merely arithmetic, but most people can't tell the difference between mathematics and arithmetic.

I think LLMs have the same effect on anything that can be expressed in words, and all the various image generator models have this effect on graphical arts. One must be extremely motivated to get past the "but the computer is better than me" hump.

However, I don't expect AI development to even approximately halt at anything close to the current level. There's a lot of room for self-play in domains like maths and computing where the proofs can be verified, and probably a lot of room for anything that can be RLHF'd, too. And that's also assuming we don't get any brain uploads; regardless of the question of "is such an upload of a human capable of consciousness", which absolutely matters, it may still be relevant to the economic issues of AI depending on the cost of running one depending on all the details of such an upload that I can't even begin to guess at at this point (last I heard, https://openworm.org was not actually measuring synaptic weights directly, but rather neural activity? I may be out of date, not my field).

Whatever happens, however good it does or doesn't get, I do expect something to go very weird before I reach the current state pension age — close enough that, if that something is "the machines break" or "society breaks", then there will still be plenty who remember the before times.

[0] https://www.smbc-comics.com/comic/secrets-2

Consider the case of a computer simulation of a worm [0]

If your simulation predicts the worm behavior up to some tolerance, you then laugh at it's supposed free will

There's some outside conditions that can't be controlled (the simulator is also a subset of the same universe) and may deterministically affect the worm behavior

To fully account for these factors and their corresponding deterministic chain, the simulation must grow more and more complex

Maybe free will could be thought instead of as a determinism ratio taking into account compute limits

I suspect a logical contradiction could arise presuming a subset of the universe being able to simulate the whole universe

If the simulation has to be limited, some "wiggle room" of free will must be granted

Considering the known vastness of the universe, I might as well wiggle

[0] https://openworm.org/

this is important

There is a complete, precise connectome for C. elegans, a roundworm with a central nervous system of 302 neurons and about 7k synapses. You can simulate the worm on your computer right now. More invertebrate connectomes have been mapped since then. It's been difficult to tell, from these animals, whether the connectome is the be-all-end-all of CNS function (SciAm 2012 -- I'd like to find an updated source on the discussion).