Kolmogorov's conjecture that $P$ has linear-size circuits In his book, Boolean Function Complexity, Stasys Jukna mentions (page 564) that Kolmogorov believed that every language in P has circuits of linear size. No reference is mentioned and I couldn't find anything online. Does anyone know more about this?
[Following a suggestion of Kaveh, I am putting my (somewhat extended) comment as an answer]

This "conjecture" of Kolmogorov is just a rumor. It was not published anywhere. In the former USSR, "publishing" mathematics meant something different than what it does today: give a talk at a seminar or tell your colleagues at lunch. Counting papers was not an issue. (Actually, I've also enjoined this way of doing math.) I cannot exclude the possibility that this "conjecture" was just told to Levin by Kolmogorov during their walk to a seminar at Moscow University.  So don't take this too seriously as a formal conjecture; it is just a rumor that (needless to say) hasn't been refuted over the years. But since a giant such as Kolmogorov seriously thought about this problem, and hasn't excluded the possibility of a "devil's power", the conjecture should be treated seriously enough, just as a warning about our possibly wrong intuition on what circuits actually do.

Here is a (very, very rough) speculation of my understanding of this conjecture. Our (apparently wrong) intuition about how circuits work relies on viewing the computation by a program as a sequential process which gradually collects information about the input string. This intuition is borrowed from our view of how a Turing machine works. But each input string $x$ determines a subcircuit (witnessing $f(x)=1$ or $f(x)=0$). And for a circuit to be correct, it is enough that the sets of subcircuits for $f^{-1}(1)$ and $f^{-1}(0)$ are disjoint. That is, a circuit is a compact "local encoding" of a given partition of the $n$-cube. The length of this code is the Kolmogorov complexity of the given binary string $f_n$ of length $2^n$. A polynomial time algorithm, however, does more: it gives one "global encoding" of the entire infinite string $f$ for all $n$. Now, an infinite string $f$ allowing an encoding of size $n^c$ must be "simple", and its prefixes "should" allow even more compact "local" encodings. Of course, it remains a mystery why Kolmogorov thought that "local" encodings even of size $cn$ for some $c$ may then be sufficient...

P.S. Sorry, forgot to add: An excellent confirmation of my "thesis" that circuits should be viewed as (static) codes rather than (dynamic) algorithms is the famous 
theorem of David Barrington that the entire class $NC^1$ can be simulated by polynomial-size branching programs of width 5. The "gathering information" view here is totally wrong: it is not even clear how to compute the majority function by keeping only 5 bits of information. A clever idea of David was just to encode the behavior of a given formula by particular sequences of 5-permutations, and to show that accepted and rejected strings will get different codes. The point is that a branching program also does not "compute" --- it rather encodes input strings by its sub-programs: when an input arrives, inconsistent edges disappear, and we have a code of this input.