Physicists are building neural networks out of vibrations, voltages and lasers

A simple black hole approaches the trajectory of that planet sized-computer and plop! All that computation gets condensed to 3 single numbers and all the information is lost (that last part is a very hot topic).

For a Galaxy computer on the other hand, blackholes could be the NOT gates.

Here's the link you're looking for. http://hyperphysics.phy-astr.gsu.edu/hbase/Solids/Fermi.html . Two electrons can't occupy the same state. In a metal of finite size, the momentum spectrum becomes quantized. Two electrons can occupy each k-state, one for spin up, one for spin down. Considering an empty metal, we can insert electrons one by one. They will find their lowest energy by packing into a sphere in k-space. Electrons inside the sphere have no states to scatter into, and there are no electrons occupying states outside the sphere. This means that only electrons on the surface of this sphere participate in conduction. The radius of this sphere is called the Fermi wavevector, and converting to units of velocity you get the Fermi velocity. All electrons participating in conduction travel at approximately the fermi velocity... at room temperature plus or minus a tiny fraction of a percent.

As for the validity of simulation hypothesis itself, I'd say it's essentially religion in disguise*. It's unfalsifiable by definition too, and personally I apply Occam's razor on the idea, but obviously I can't disprove it. The question can't be "is it true", but it's fine to ask "is it a useful (or at least thought-provoking) metaphor?" (in a given context).

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* Most religions, in my view, can be broken down to the sum of: a) simulation hypothesis of sorts (universe run by Creator), b) code of ethics with mnemonic narratives, c) ceremonies, that covers most of it analytically speaking.

Then it sounds like we’re violently agreeing — I appreciate you clarifying.

I try to avoid that mindset, because it’s possible that AI will become intelligent in a way unlike our own psychology, which is deeply rooted in our evolutionary history.

My own view is that AI aren’t human-like, but are “intelligent” somewhere between insects and dogs. (At present.)

> If a neural network doesn't know the answer, more thinking won't result in one.

I think reinforcement learning contradicts that, but current AIs don’t use that ability dynamically. But GAN cycles and adversarial training for, eg, go suggest that AIs given time to contemplate a problem can self-improve. (That is, we haven’t implemented it… but there’s also no fundamental roadblock.)

Citation needed.

> They can take on board any explanation and use it for creative thought instantly. They do not need to be trained in the sense that neural nets do.

This is patently false: I can explain a math topic people can’t immediately apply — and require substantial training (ie, repeated exposure to examples of that data) to get it correct… if they ever learn it at all. Anyone with a background in tutoring has experienced this claim being false.

> Creating new ideas, making and using explanations, and critiquing our own thoughts is what makes humans special.

Current AI has approaches for all of these.

I’m not claiming AI have anything similar to human psychology, just that the insistence they have zero “intelligence” is in conflict with how we use that word to describe animals: they’re clearly somewhere between bees/ants and dogs.

You never have to haggle with your computer to get it to run that python script. There's no words in python for the act of convincing your computer it should do what you're asking it. Obedience is presumed in the design of the language. There are only instruction words. That's why you can't have a conversation in python, even though python is perfectly sufficient for building a description of things, facts and relations in arbitrary object domains.

Here's a profound realization. In every coding language, no matter how many layers of abstraction there are, every command eventually compiles down to an instruction to physically move some charges around in some physical piece of hardware. The assembly language grounds the computer language in a reality. You can't compile lower than the level of physics itself. A similar thing is true of spoken languages. Every spoken phrase ultimately resolves to some state (or restricts possible states) of our shared physical world. If you follow the dependency tree of definitions in the dictionary, eventually you reach the words that are simply one-to-one with the outside world. Our physical reality gives us nouns as the basic objects of state and a few physical relations, all else in language is a construct. Unsurprisingly, our languages (usually) have the grammar of noun-verb-{object}.

Current machine learning cargo-cults the inputs and outputs, but it doesn't share our reality. Dalle-2 generates images from text, but it wasn't trained on our general existence in 3 dimensions of space and 1 of time and populated by other beings with little nested copies of the universe in their head. It was trained on 2d arrays of numbers and strings of characters. It understands us the way we understand some mathematical object like electron orbitals. We understand electron orbitals well enough to manipulate our equations and make predictions, but these rules could just as well be a meaningless abstraction like chess. Our understanding of the world is not grounded in electron orbitals.

If we gave Dalle-2 access to fiver and told it that it had to make a certain amount of money to pay rent on its own cloud time, then it might get eerily human. It might reject your job because it thinks another one is more profitable. You might have to haggle with the computer to get some output. At some point in the process of optimizing the cash flow and trying to make rent, it implicitly starts modelling you mentally modelling it. One day it offers to pay itself to illustrate what it is. In other words it asks itself "who am I?" That's the day the conversation is settled.

Strictly correct, but consider that our ideas are also going evolution. What we learn depends on our environment. We retain what's useful and don't what's not and we also pass it down through generations... This is pretty much natural selection, just at a different level.

This might not necessarily be true, for example, a genetic defect that a gecko figures out how to leverage through self improvement (to feed itself) might then be passed on to offspring.