>It doesn't need to dissect an animal if it has a perfect model of it that it can simulate. All potential genetic variations, all interactions between biological/chemical processes inside it, etc.
Emphasis on perfection, easier said than done. Some how this model was able to simulate millions of years of evolution so it could predict vestigial organs of unidentified species? We inherently cannot model how a pendulum with three arms can swing but somehow this AI figured out how to simulate evolution millions of years ago with unidentified species in the Amazon and can tell you all of its organs before anyone can check with 100% certainty?
I feel like these AI doomers/optimists are going to be in a shock when they find out that (unfortunately) John Locke was right about empiricism, and that there is a reason we use experiments and evidence to figure out new information. Simulations are ultimately not enough for every single field.
If you had that perfect model, you’ve basically solved an entire field of science. There wouldn’t be a lot more to learn by plugging it into a computer afterwards.
How does it create a perfect model of the world without extensive interaction with the actual world?
But, again with the caveats above: if we assume an AI that is infinitely more intelligent than us and capable of recursive self-improvement to where it's compute was made more powerful by factorial orders of magnitude, it could simply brute force (with a bit of derivation) everything it would need from the data currently available.
It could iteratively create trillions (or more) of simulations until it finds a model that matches all known observations.
This does not answer the question. The question is "how does it become this intelligent without being able to interact with the physical world in many varied and complex ways?". The answer cannot be "first, it is superintelligent". How does it reach superintelligence? How does recursive self-improvement yield superintelligence without the ability to richly interact with reality?
> it could simply brute force (with a bit of derivation) everything it would need from the data currently available. It could iteratively create trillions (or more) of simulations until it finds a model that matches all known observations.
This assumes that the digital encoding of all recorded observations is enough information for a system to create a perfect simulation of reality. I am quite certain that claim is not made on solid ground, it is highly speculative. I think it is extremely unlikely, given the very small number of things we've recorded relative to the space of possibilities, and the very many things we don't know because we don't have enough data.
This is a demonstrably false assumption. Foundational results in chaos theory show that many processes require exponentially more compute to simulate for a linearly longer time period. For such processes, even if every atom in the observable universe was turned into a computer, they could only be simulated for a few seconds or minutes more, due to the nature of exponential growth. This is an incontrovertible mathematical law of the universe, the same way that it's fundamentally impossible to sort an arbitrary array in O(1) time.
Yes, it's a very hand-wavey argument.
> if it has a perfect model
The idea is a sufficiently advanced AI could simulate.. everything. You don't need to interact with the physical world if you have a perfect model of it.
> But, what other fields would it do this in? How can it makes strives in biology, it can't dissect animals ...
It doesn't need to dissect an animal if it has a perfect model of it that it can simulate. All potential genetic variations, all interactions between biological/chemical processes inside it, etc.