I suspect it would still involve billions of $ of funding, partnerships like the one with Microsoft, and other for-profit pressures to be the sort of player it is today. So I don’t know that Musk’s plan was viable at all.
Note that all of this happened before the scaling hypothesis was really formulated, much less made obvious.
We now know, with the benefit of hindsight, that developing AI and it’s precursors is extremely compute intensive, which means capital intensive. There was some reason to guess this might be true at the time, but it wasn’t a forgone conclusion—it was still an open question if the key to AGI would be mostly some technical innovation that hadn’t been developed yet.
I’m tempted to say when this page was first published.
Of course the core idea is older than that, going back to at least Moravec’s calculations of when AGI would arrive based on number of neuron in the retina in Mind Children (1988). But until the late 2010s that point there was still a lot of uncertainty about the relative contribution of algorithms and compute to general AI. Hence the “brain in a box in a basement” model.
Perhaps it would be more correct to say “before the scaling hypothesis was really validated”.
Note that all of this happened before the scaling hypothesis was really formulated, much less made obvious.
We now know, with the benefit of hindsight, that developing AI and it’s precursors is extremely compute intensive, which means capital intensive. There was some reason to guess this might be true at the time, but it wasn’t a forgone conclusion—it was still an open question if the key to AGI would be mostly some technical innovation that hadn’t been developed yet.
Hm, but I note others at the time felt it clear that this would exacerbate the competition (1, 2).
“before the scaling hypothesis was really formulated” When do you think that was? Deep Blue obviously used a lot of scaling. So did AlexNet.
I’m tempted to say when this page was first published.
Of course the core idea is older than that, going back to at least Moravec’s calculations of when AGI would arrive based on number of neuron in the retina in Mind Children (1988). But until the late 2010s that point there was still a lot of uncertainty about the relative contribution of algorithms and compute to general AI. Hence the “brain in a box in a basement” model.
Perhaps it would be more correct to say “before the scaling hypothesis was really validated”.