The Landauer's limit suggests that a brain consuming 20W at 36C can carry out no more than ~1e22 irreversible operations per second (20W / (309.2K * Boltzmann constant * ln(2))).
That bounds brains at ~1e21 FLOP/s (~10 bits erased per FLOP). The best supercomputer right now does ~4e17 FLOP/s.
That's log2(1e21 / 4e17) ~11 doublings of computing power until supercomputers will be faster than thermodynamic maximum of FLOPS power of brains.
Assuming we keep up the doubling time below 3 years, we will have supercomputers faster than a human brain in up to 3 * 11 ~ 33 years.
And at that rate we will need another log2(1000^3) ~ 30 doublings to reach humanity brains computational power, so up to another 90 years.
Overall, I don't see a reason why not to use biological platform for general type computations. If we are able to grow muscle tissue in a lab on an industrial scale, then we should be able to learn how to grow neurons in a lab on an industrial scale. Apparently neurons are a lot more difficult to grow, but it's still perfectly doable [2]. The issue is that we don't know how to grow them so that they do useful computation. But I can easily imagine that AWS and competition will be selling access to teachable biological neurons in the mid term future e.g. in 30 years.
[0] https://news.ycombinator.com/item?id=26623730
Replicating "intelligence" that is alive is probably a trillion times more difficult.
Correct me if I'm wrong but I think you just made an argument for "Why Computers (as we know them) Won't Make Themselves Smarter".