A simple virus has abilities that no "computer" has ever demonstrated.
For example, the ability to reproduce and optimize it's own programming for survival and expansion.
For example, the ability to reproduce and optimize it's own programming for survival and expansion.
But a biological virus can change and adapt to new situations and environments all on it's own --- with new logic of it's own design. You could easily argue that a simple biological virus is more "intelligent".
Computing power that biological platforms provide are quite huge.
Each infected person carries 1e9 - 1e11 virions during peak infection [0]. If there are 1 million (1e6) infected people right now then we have around 1e15 - 1e17 virons. With a viron size of 32kb and 8h replication time [1] we get speed of ~10 bits/s or very roughly 1 FLOPS per viron.
That gives us computing power used for virus replication between 1 petaFLOPS to 100 petaFLOPS. The number is probably an underestimate because 1 viron probably needs to produce 1000 or more copies to maintain replication rate of 1. The upper bound then would be 100 exaFLOPS.
That's in the range of TOP500 supercomputers (1.3 petaFLOPS - 442 petaFLOPS) [2].
The sum of all TOP500 supercomputers is 2.4 exaFLOPS, so some 40 times less than the upper bound on the virus of 100 exaFLOPS.
[0] https://www.medrxiv.org/content/10.1101/2020.11.16.20232009v...
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".
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
As for optimization, it is a pure random walk.
We have yet to build a computer program that can adapt and "learn" and grow as effectively or as efficiently as a simple biological virus. In other words, a virus; which is technically not even alive, is closer to being "intelligent" than anything AI has yet produced. Never mind intelligence that is alive.
I would not describe this process as efficient. It has no memory: mutations could be randomly done and undone. A huge majority of mutations lead to non viable viruses, still keep occurring again and again. Of course it successfully adapts to changing conditions, but without that that would not even be an optimization algorithm. Given huge resources we would have no difficulty simulating such a process. At a smaller scale it has inspired genetic algorithms and a large family of stochastic algorithms, which had to be carefully refined to become useful. We do not have the same resources and the same patience as Mother Nature.
Exactly!
Overall, Mother Nature is actually pretty resource efficient.