You raise a good and apt point. I would say firstly, we don't have to know how to achieve it exactly, since once we have the hardware we can just experiment.

You raise a good and apt point. I would say firstly, we don't have to know how to achieve it exactly, since once we have the hardware we can just experiment. The human source code is about seven hundred megabytes (fairly precisely, DNA is almost precisely 2 bits per base pair) so somewhere in that is the encoding for human intelligence, since humans inherit it. So we know that there is some < 700 MB program. Now 700 MB is a ton of source code, but it's not an unimaginable amount. We know some of the compiled results, as we can see how human brains are built actually. So there's lots of indications that we will be able to get similar results once we have the hardware for it - which we do. Secondly I would point to many of the specific advances reached using machine learning as excellent indications that we are quite near the kind of algorithmic breakthroughs that are necessary. Since the topology of these algorithms is in many cases closely inspired by human neural topology, and many algorithms achieve many similar results, it seems quite likely that we would be able to reproduce some of these effects experimentally. More than "likely", in many domains the computers have done just that.