The amount of computation, and program expressibility involved in folding a protein is far far far more than you would expect from just counting the DNA that made that protein.
Yes, "fold proteins" is a member of a distinguished class of algorithms that DNA is exceptionally well suited to handle.
Similarly, "simulate shallow wave dynamics" is in the class of algorithms that a water tank is pretty near optimal for, and the "find local minima" problem is handled with remarkable ease by gravity and a rolling ball; we'd be hard pressed to write computer programs that solve any of these problems using fewer bits than we can get by with by using the real world to solve them instead.
But most algorithms are not made that easy by any of these computational substrates; in fact, vanishingly few of them are, and an algorithm is only likely to be "easy" relative to vanishingly few systems.
What would let us assume that "Do intelligence" is a member of the subset of problems that are made easy by the detailed workings of biology? Because the a priori probability that it falls into that class is just about zero...
From "counting the DNA", you would expect that the family of hundred-amino-acid-long peptides, which are encoded in strings of 300 bases, would have 4³⁰⁰ = 2⁶⁰⁰ possible three-dimensional conformations, or rather probability distributions over conformations, since many peptides have multiple stable conformations.
However, those 2⁶⁰⁰ sequences of bases are immediately reduced to 20¹⁰⁰ ≈ 2⁴³² possible sequences of amino acids (ignoring the start and stop codons, which are presumed to lie just before and just after the 300-base sequence in question).
Are you suggesting that these 2⁴³² different peptides somehow express many more than the 2⁶⁰⁰ different three-dimensional structures, or rather, probability distributions over them? Because that seems like a highly implausible claim, on the face of it.
Or are you going to answer, "Fucking arithmetic. How does it work?"
Similarly, "simulate shallow wave dynamics" is in the class of algorithms that a water tank is pretty near optimal for, and the "find local minima" problem is handled with remarkable ease by gravity and a rolling ball; we'd be hard pressed to write computer programs that solve any of these problems using fewer bits than we can get by with by using the real world to solve them instead.
But most algorithms are not made that easy by any of these computational substrates; in fact, vanishingly few of them are, and an algorithm is only likely to be "easy" relative to vanishingly few systems.
What would let us assume that "Do intelligence" is a member of the subset of problems that are made easy by the detailed workings of biology? Because the a priori probability that it falls into that class is just about zero...