I think AGI before human uploads is far more likely. If you have hardware capable of running an upload, the trial-and-error approach to AGI will be a lot easier (in the form of computationally expensive experiments). Also, it is going to be hard to emulate a human brain without knowing how it works (neurons are very complex structures and it is not obvious which component processes need to appear in the emulation), and as you approach that level of knowledge, trial-and-error again becomes easier, in the form of de novo AI inspired by knowledge of how the human brain works.
Maybe you could do a coarse-grained emulation of a living brain by high-resolution fMRI-style sampling, followed by emulation of the individual voxels on the basis of those measurements. You’d be trying to bypass the molecular and cellular complexities, by focusing on the computational behavior of brain microregions. There would still be potential for leakage of discoveries made in this way into the AGI R&D world before a complete human upload was carried out, but maybe this method closes the gap a little.
I can imagine upload of simple nonhuman nervous systems playing a role in the path to AGI, though I don’t think it’s at all necessary—again, if you have hardware capable of running a human upload, you can carry out computational experiments in de novo AI which are currently expensive or impossible. I can also see IA (intelligence augmentation) of human beings through neurohacks, computer-brain interfaces, and sophisticated versions of ordinary (noninvasive) interfaces. I’d rate a Singularity initiated by that sort of IA as considerably more likely than one arising from uploads, unless they’re nondestructive low-resolution MRI-produced uploads. Emulating a whole adult human brain is not just an advanced technological action, it’s a rather specialized one, and I expect the capacity to do so to coincide with the capacity to do IA and AI in a variety of other forms, and for superhuman intelligence to arise first on that front.
To sum up, I think the contenders in the race to produce superintelligence are trial-and-error AGI, theory-driven AGI, and cognitive neuroscience. IA becomes a contender only when cognitive neuroscience advances enough that you know what you’re doing with these neurohacks and would-be enhancements. And uploads are a bit of a parlor trick that’s just not in the running, unless it’s accomplished via modeling the brain as a network of finite-state-machine microregions to be inferred from high-resolution fMRI. :-)
The following is a particular take on the future, hopefully demonstrating a realistic path for uploads occurring before AGI.
Imagine a high fidelity emulation of a small mammal brain (on the order of 1 g) is demonstrated, running at about 1/1000th real time. The computational demand for such a code is roughly a million times less than for emulating a human brain in real time.
Such a demonstration would give immense credibility to whole brain emulations, even of humans. It’s not unlikely that the military would be willing to suddenly throw billions into WBE research. That is, the military isn’t without imagination, and once the potential for human brain emulation has been shown, it’s easy to see the incredible ramifications they would bring.
The big unknown would be how much optimization could be made to the small brain uploads. If we can’t optimize the emulations’ code, then the only path to human uploads would be through Moore’s law, which would take two decades: ample time for the neuroscience breakthroughs to impact AGI. If, on the other hand, the codes prove to allow large optimizations, then intense funding from the military could get us to human uploads in a matter of years, leaving very little time for AGI theory to catch up.
My own intuition is that the first whole brain emulations will allow for substantial room for optimization.
I think AGI before human uploads is far more likely. If you have hardware capable of running an upload, the trial-and-error approach to AGI will be a lot easier (in the form of computationally expensive experiments). Also, it is going to be hard to emulate a human brain without knowing how it works (neurons are very complex structures and it is not obvious which component processes need to appear in the emulation), and as you approach that level of knowledge, trial-and-error again becomes easier, in the form of de novo AI inspired by knowledge of how the human brain works.
Maybe you could do a coarse-grained emulation of a living brain by high-resolution fMRI-style sampling, followed by emulation of the individual voxels on the basis of those measurements. You’d be trying to bypass the molecular and cellular complexities, by focusing on the computational behavior of brain microregions. There would still be potential for leakage of discoveries made in this way into the AGI R&D world before a complete human upload was carried out, but maybe this method closes the gap a little.
I can imagine upload of simple nonhuman nervous systems playing a role in the path to AGI, though I don’t think it’s at all necessary—again, if you have hardware capable of running a human upload, you can carry out computational experiments in de novo AI which are currently expensive or impossible. I can also see IA (intelligence augmentation) of human beings through neurohacks, computer-brain interfaces, and sophisticated versions of ordinary (noninvasive) interfaces. I’d rate a Singularity initiated by that sort of IA as considerably more likely than one arising from uploads, unless they’re nondestructive low-resolution MRI-produced uploads. Emulating a whole adult human brain is not just an advanced technological action, it’s a rather specialized one, and I expect the capacity to do so to coincide with the capacity to do IA and AI in a variety of other forms, and for superhuman intelligence to arise first on that front.
To sum up, I think the contenders in the race to produce superintelligence are trial-and-error AGI, theory-driven AGI, and cognitive neuroscience. IA becomes a contender only when cognitive neuroscience advances enough that you know what you’re doing with these neurohacks and would-be enhancements. And uploads are a bit of a parlor trick that’s just not in the running, unless it’s accomplished via modeling the brain as a network of finite-state-machine microregions to be inferred from high-resolution fMRI. :-)
The following is a particular take on the future, hopefully demonstrating a realistic path for uploads occurring before AGI.
Imagine a high fidelity emulation of a small mammal brain (on the order of 1 g) is demonstrated, running at about 1/1000th real time. The computational demand for such a code is roughly a million times less than for emulating a human brain in real time.
Such a demonstration would give immense credibility to whole brain emulations, even of humans. It’s not unlikely that the military would be willing to suddenly throw billions into WBE research. That is, the military isn’t without imagination, and once the potential for human brain emulation has been shown, it’s easy to see the incredible ramifications they would bring.
The big unknown would be how much optimization could be made to the small brain uploads. If we can’t optimize the emulations’ code, then the only path to human uploads would be through Moore’s law, which would take two decades: ample time for the neuroscience breakthroughs to impact AGI. If, on the other hand, the codes prove to allow large optimizations, then intense funding from the military could get us to human uploads in a matter of years, leaving very little time for AGI theory to catch up.
My own intuition is that the first whole brain emulations will allow for substantial room for optimization.