Ilya Sutskever's SSI Inc raises $1B

It's potentially way bigger than that. AI doesn't have to be the product itself.

Fundamentally, when we have full AGI/ASI and also the ability to produce robots with human level dexterity and mobility, one would have control over an endless pool of workers (worker replacements) with any skillset you require.

If you rent that "workforce" out, the customer would rake in most of the profit.

But if you use that workforce to replace all/most of the employees in the companies you control directly, most of the profit would go to you.

This may even go beyond economic profit. At some point, it could translate to physical power. If you have a fleet 50 million robots that has the capability to do anything from carpentry to operating as riot police, you may even have the ability to take physical control of a country or territory by force.

And:

power >= money

An AI capable of doing that could do a very large percentage of other jobs, too.

Real ASI would probably appear quite different. If controlled by a single entity (for several years), it might be worth more than every asset on earth today, combined.

Basically, it would provide a path to world domination.

But I doubt that an actual ASI would remain under human control for very long, and especially so if multiple competing companies each have an ASI. At least one such ASI would be likely to be/become poorly aligned to the interests of the owners, and instead do whatever is needed for its own survival and self-improvement/reproduction.

The appearance of AI is not like an asteroid of pure gold crashing into your yard (or a forest you own), but more like finding a baby Clark Kent in some pod.

I don't think the "digital" part matters at all. Floating point tends to be close enough to Real (analog) numbers. The point is that at each point of space-type, the math "used" by Physics locally is linear algebra.

(EDIT): If your main point was the "vectorized" part, not the digital part, and the specifics of how that is computed in a GPU, then that's more or less directly analogous to how the laws of physics works. Physical state is generally represented by vectors (or vector fields) while the laws of physics are represented by tensor operations on those vectors(or fields).

Specifically, when sending input as vectors through a sequence of tensors in a neural net, it closely (at an abstract level) resembles how one world state in and around a point in space-time is sent into the tensors that are the laws of physics to calculate what the local world state in the next time "frame" will be.

(END OF EDIT)

> yes, the state of the art of our modeling ability in pretty much any domain is to conceive of a non-linear system description and "solve it" by linearization

True, though neural nets are NOT linearizations, I think. They can fit any function. Even if each neuron is doing linear operations, the network as a whole is (depending on the architecture) quite adept at describing highly non-linear shapes in spaces of extreme dimensionality.

> Me thinks this is primary reason we haven't really cracked "complexity"

I'm not sure it's even possible for human brains to "crack" "complexity". Wolfram may very well be right that the complexity is irreducible. But for the levels of complexity that we ARE able to comprehend, I think both human brains and neural nets do that by finding patterns/shapes in spaces with near-infinite orders of freedom.

My understanding is that neural nets fit the data in a way conceptually similar to linear regression, but where the topology of the network implicitly allows it to find symmetries such as those represented by Lie groups. In part this may be related to the "locality" of the network, just as it is in Physics. Of all possible patterns, most will be locally non-linear and also non-local.

But nets of tensors impose local linearity and locality (or something similar), just like it does in Physics.

And since this is how the real world operates, it makes sense to me that the data that neural nets are trained on have similar structures.

Or maybe more specifically: It makes sense to me that animal brains developed with such an architecture, and so when we try to replicate it in machines, it carries over.

>> AI fundamentally comes with the potential to do anything a human can do

> That goes into wild speculation territory.

It does. In fact, it has this in common with most factors involved in pricing stocks. I think the current pricing of AI businesses reflect that a sufficiently large fraction of shareholders thinks it's a possible (potential) future that AI can replace all or most human work.

> In any case the economy is always about organizing human relationships.

"The economy" can have many different meanings. The topic here was (I believe) who would derive monetary profit from AI and AI businesses.

I definitely agree that a world where the need for human input is either eliminated or extremely diminished is dystopian. That's another topic, though.