> On 1 Nov 2019, at 12:02, Philip Thrift <[email protected]> wrote:
> 
> 
> 
> On Friday, November 1, 2019 at 5:51:26 AM UTC-5, Bruno Marchal wrote:
> 
>> On 31 Oct 2019, at 12:00, Philip Thrift <[email protected] <javascript:>> 
>> wrote:
>> 
>> 
>> 
>> On Thursday, October 31, 2019 at 5:47:14 AM UTC-5, John Clark wrote:
>> On Wed, Oct 30, 2019 at 6:54 PM Philip Thrift <[email protected] <>> wrote:
>> 
>> >> The computation is the same independently of the substrate of its 
>> >> implementation. For example, you could run the same program on a computer 
>> >> based on vacuum tubes or transistors, with the same output.
>> Stathis Papaioannou
>> 
>> > That's the case for the conventional-Platonistic definition of computing. 
>> > Not the case for computing with a material-intrinsic semantics.
>> 
>> So according to "material-intrinsic semantics" the 4 that a vacuum tube 
>> computer produces when it adds 2+2 is not the same 4 that a transistor 
>> computer produces when it adds 2+2; and the 4 a white man gets when he adds 
>> 2+2 does not mean the same thing as the 4 a black man gets when he adds 2+2, 
>> and there is a male 4 when a man makes the addition and a female 4 when a 
>> woman does. So how can a serious person consider anything as monumentally 
>> silly as a computational theory involving "material-intrinsic semantics"?
>> 
>> John K Clark
>> 
>> 
>> If there is a program in C vs. a program in Python (vs. Java, etc.) that 
>> produce the same I/O, which uses the least energy? 
> 
> It all depends on the algorithm, and not of the language (but still on the 
> way that language is implemented).
> 
> The only thing which requires energy is in the erasure of the information 
> (Landauer). Yet, it has been shown (by Hao Wang) that we can get Turing 
> universality with elementary operations which never erase anything. This is 
> of course reflected in quantum computations, which have to reversible, and 
> never dissipate energy.
> 
> Computations does not require energy, except for read and write, and 
> interaction with the users.
> 
> For example, instead of using the combinators K (which erase information, as 
> Kxy = x, implies that the information in y has vanished), we can use the base 
> I, B, C, W:
> 
> Ix = x                (identity)
> Bxyz = x(yz)  (composer, applicator)
> Cxyz = xzy    (permuter)
> Wxy = xyy,    (duplicator)
> 
> In that case we can avoid using energy.
> 
> So, your question is that it depends on the number of erasing done in your 
> algorithm, and in the universal machine implementing your algorithm.
> 
> The presence of the quantum axioms ([]p->p, + p-> [<>p, for p sigma_1) in the 
> self-referential “observable” modes suggests that this remains true in the 
> physics extracted from arithmetic (or from any universal machinery).
> 
> Bruno
> 
> 
> 
> 
> 
>> 
>> Or a man vs. a woman that adds. :)
>> 
>> 
>> Material-intrinsic semantics are a UCNC conferences topic. Check them out.
>>  
>> @philipthrift
>> 
> 
> 
> I am including with the program (C, Python, etc. the whole system (compiler, 
> interpreter) that takes the program (implementing a common "algorithm") and 
> ultimately produces machine code for different machines.
> 
> If there was a universal compiler that could take a program in any (of the 
> top 10 languages, say) and produce the lowest energy and fastest version 
> transformation of the program for the target machine, that would be quite a 
> compiler.

That cannot exist, but some approximation of this could make sense. By the Blum 
speed-up theorem (or a more general version due ti Blum & Al.) there is no 
fastest universal machine. We can diabolise to bring a more faster one, in 
theory. There are nice theories which explains why they cannot be used in 
practice, but still play a role if we are concerned with the truth about the 
machine, and the relation between machine and truth.

Bruno



> 
> @philipthrift 
> 
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