Any number expressible in ternary, or a base 3 number system, is expressible in binary with a very simple formula to convert between the two. Binary just requires more digits. Fundamentally, a ternary computer is the same as a binary computer in terms of the problems that are decideable.
Ternary computers have been around for a very long time. They are not new, and I fail to see how they are in any way relevant to AGI (which, to be clear, is something that exists purely in the realm of science fiction and not something we’re actually going to be accomplishing any time soon). Ternary computing is certainly interesting and can offer potential performance improvements over binary computers in terms of speed/power efficiency for certain specialized applications, but it’s not some magical new computing paradigm or something. Oh, and by the way, there’s multiple ways of making ternary systems: -1, 0, and 1 is just one system (called balanced ternary).
Also, fuzzy logic (or logic that accounts for uncertainty) has been around for a very long time, and in fact, is exactly what neural networks are using right now. It’s encoded using floating point numbers between 0 and 1, which, in binary, are encoded using 32 or 64 bits (or more rarely, 16 bits). Again, not anything new.
And I have no idea what you’re talking about with analog.
Any number expressible in ternary, or a base 3 number system, is expressible in binary with a very simple formula to convert between the two. Binary just requires more digits. Fundamentally, a ternary computer is the same as a binary computer in terms of the problems that are decideable.
Ternary computers have been around for a very long time. They are not new, and I fail to see how they are in any way relevant to AGI (which, to be clear, is something that exists purely in the realm of science fiction and not something we’re actually going to be accomplishing any time soon). Ternary computing is certainly interesting and can offer potential performance improvements over binary computers in terms of speed/power efficiency for certain specialized applications, but it’s not some magical new computing paradigm or something. Oh, and by the way, there’s multiple ways of making ternary systems: -1, 0, and 1 is just one system (called balanced ternary).
Also, fuzzy logic (or logic that accounts for uncertainty) has been around for a very long time, and in fact, is exactly what neural networks are using right now. It’s encoded using floating point numbers between 0 and 1, which, in binary, are encoded using 32 or 64 bits (or more rarely, 16 bits). Again, not anything new.
And I have no idea what you’re talking about with analog.
I mean, analog computing is a thing. The rest of it as you pointed out is mostly incoherent nonsense.
Sure, I just meant that I have no idea how it’s at all relevant.
lol true… but it seems just as relevant as ternary numbers!