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I made this whole series of videos on how to build this 8-bit computer, but in this video
I want to get a bit philosophical and ask the question: Is this thing really a computer? And if not, why not? What's it missing?
And obviously, even if this thing is a computer, it's a very limited computer. I mean our clock is incredibly slow;
we can speed it up a bit, but even then, the maximum clock speed—at least with the components I'm using—
looks to be about 300Hz here which if I compare that to the computer I'm using to edit this video,
that's got 2.8GHz so it's almost 10 million times faster.
But that's not the point; sure, this is limited and in fact the memory—instead of 16 gigabytes—
we only have 16 bytes because we have 4-bit address.
But I'm not asking is this a limited computer; I'm asking something a little bit more philosophical, which is
Is this thing a computer at all?
So, to answer that I think we've got to look at two things: one is what is this thing currently capable of?
And then, second, what should a computer be able to do? And are we missing anything?
So these are the instructions we've got so far and there's a bunch of stuff in here. Load A, store A, add, subtract
But one thing, just as an example, what about multiplying? We don't have an instruction to do that.
And that certainly seems like something that a computer ought to be able to do is multiply two numbers, right?
Okay, maybe we need to add a multiply instruction next.
You know we could we could do that by by adding some additional hardware like we did for subtract and add
So we've got an adder and subtractor here, maybe we can build some hardware to multiply two numbers, and you can do that
You know it's just combinational logic to look at what's in this register, and what's in this register
multiply those together put the result into the result register here, and then we need to add and some sort of
Control signal here part add another bit to our control word for multiplication
and
Then you know put the appropriate thing in the microcode and add another instruction. So we could do that and then the computer would be
Able to multiply but multiplication isn't the only thing that's missing here. I mean what about division what about?
exponentiation what about
Logarithms trigonometric functions, I mean we could go on and on about with all the functions that were missing
But if we just keep adding new
Instructions for each new function that we think up you know we're going to be adding instructions all day
We're gonna be building you know custom hardware for each instruction
Is that is that really what we want yeah?
I would think that a
Computer what we'd want is we want enough instructions to be able to program the computer to do any of those functions
So so we ought to be able to write a program that can multiply you know. We've got an add instruction
And multiplication is just a bunch of addition
So it seems like we ought to be able to write a program that just takes two numbers
You know perhaps. They're in in memory somewhere
but before the program starts and
And then run through that program and it would multiply those two numbers and output the result to the display here
But it turns out that with the instructions that we've got here
it's impossible to write a program that does that and I
Would encourage you to you know give it a try look at these instructions see if you can write a program
But I don't think it's possible
Which brings up this really interesting question?
Which is what instructions do we need and I don't just mean well if we had a multiply instruction would be able to multiply
You know I mean what instruction
What would be the minimum set of instructions we would need to let us write programs that would let us do any of these operations
and
Not just any of these operations, but but any operation
Although even that like is that really what we want do we do
We just want to be able to do any operation or do we really want enough instructions to be able to do any
calculation which might involve lots of different operations
I don't know it seems like maybe real computers are able to do more than just calculate things
So maybe what we really want is enough instructions to be able to do anything computable
But what does that even mean you know?
What exactly is computable and what isn't I mean?
We don't really expect a computer to be able to compute the meaning of life right so
So it's maybe what we're after is is things that can be computed with an algorithm of some sort
But even that just raises questions about what kinds of operations the algorithm can do and we're right back where we started
though intuitively
we all kind of know what sorts of things a computer can and can't do so you know maybe you know a computable problem when
You see it
But but without a rigorous definition of the set of computable problems
You know how are we ever going to know if we've got all the instructions we need in order to compute anything
So this question of what you need in order to compute anything?
And you know what does that even mean, this came up pretty early in the development of computer science.
Alan Turing is widely regarded as the the father of modern computer science, and you know one of the reasons is that in
1936 he wrote a paper that talked about this very question
And this is this is a copy of that paper and in here he makes this
Astonishing claim which is that: "It is possible to invent a single machine, which can be used to compute any computable sequence" now
It's not clear what he means by any computable sequence
But he does talk about the machine in quite a bit of detail
He described this hypothetical machine that actually seems relatively simple, so it reads its input from a paper tape that is
Infinitely long, which is one of the reasons why it's a only hypothetical machine
But this tape is is infinitely long in both directions
and it has a bunch of squares on it and each of the squares contains a symbol in the
simplest case that it works is you could have two symbols so either a space is blank or maybe it has the symbol 1 and
Every every point on this tape has one of these symbols either blank or or 1 and
then there is a
Head that can move back and forth along the tape and it can look at just one symbol at a time and then
after looking at that symbol it consults a
You know a table of instructions that might look something like this and that table of instructions tells it what to do based on
The the state it's in and what symbol it scans and so
The machine, also has a notion of a state, so it might be in state A for example
and so if we're in state A and the head is pointed to a 1
then you know this is the line that we would look at in the table and so then what it does is it writes a symbol 1 to the tape so in the same position it writes a 1 in this case there's already a 1 there
But if it were blank, then it might write a 1 there, and then it moves to the left
So it moves to the left
And it could be the head that moves it could be the tape that moves it really doesn't matter
As long as you're consistent, and then it changes state to state C. And so now it's in state C
Which means now when it looks at the table? It's looking just at these things that are in state C
and in this case it's a 1 so it would erase the symbol there move to the left and then switch to state B and
It just keeps doing this until it finds its way to a transition to where it halts
And you know it may or may not actually ever get there
But but if it gets there halts, and then once its halted then whatever answer whatever
It's trying to compute would
Be on the tape somewhere that you could then look at and so it turns out that with an appropriate table of instructions like this
And some input you know encoded on the tape before the machine starts
Then this machine a machine like this can carry out pretty much any mathematical tasks
You just have to set up the right table of instructions
And in fact, it actually gets better than that
This universal computing machine that Turing talks about is just another machine like this that has a table of instructions
That that lets it basically start with a tape that has a different machine's table of instructions encoded on it
so that says the machine is supplied with a tape on on the beginning of which has written the this is a standard definition which
He defines up here sort of reducing this table of instructions down to sort of a number that you can put on the tape
of some other computing machine
And then the universal machine can actually compute the same result that that other machine would compute so
In other words this Universal machine can actually simulate
itself or simulate any other machine like this
And so that's what leads Turing to this bold claim that it's possible to invent a single machine
Which can be used to compute any computable sequence.
But this still leads us back to the same question of what do we mean by anything computable? What is this
"any computable sequence". Well, even Turing admits that there really isn't a good answer to this so later on in the paper here
He says all arguments which can be given are bound to be fundamentally appeals to intuition and for this reason rather unsatisfactory
Mathematically, so he's pretty honest that there really isn't any good definition of exactly everything that a general purpose computer ought to be able
To do but he does do his best anyway to kind of argue that his Universal machine that he's come up with
can do everything it needs to but he says here the arguments are kind of a direct appeal to intuition or
You know proving that it's equivalent to some other definition in case
You know, you like the other one better
And failing that he gives a bunch of examples of different things that that he can compute with this
But ultimately it's not a super satisfying answer to what does it mean that you can compute anything that's computable
Now at about the same time in in 1936 there was this other guy
Alonzo Church who was trying to figure figure that same thing out and so he wrote this paper, which which says
You know the purpose of this paper is to propose a definition of effective calculability which is to correspond satisfactorily to the somewhat vague
intuitive notion in terms of which problems this clause often stated
So so he's trying to nail down an actual definition of what is this you know idea of everything that can be calculated
But the interesting thing is he comes at it from a completely different direction so in this paper
He comes up with this whole new system of mathematics called lambda calculus, which starts with just a few rules
And these are this is really it you've got variables
And then you've got the ability to define a function so you can say a function that takes a variable X and
Returns some other expression and again that other expression has got to come from this list or be built from this
And then you have the ability to apply a function so you can you can give a function and give it some parameter.
From this he's able to argue that you can build on this to calculate anything calculable again
whatever whatever that means and
You know when I say you can build anything on just these rules you know I mean it so see how there there aren't any
Numbers here? So when you're defining a function here all you have is these abstract variables you don't have numbers. You don't have
Boolean values you don't have anything to work with you have to define all of that and so
Here on page 3 of his paper. He's actually defining. You know here's some abbreviations for the numbers 1 2 3
And so on so so this is a very fundamental
very abstract way of
Describing computing which is pretty wild stuff and it would be the topic of a whole other series of videos
but
But the reason that I bring Church up is that the invention of lambda calculus
was actually just a tool in this paper to get to his real conclusion which was
Which was also to show that that not every problem of this class is solvable so some of these computable problems
Not everything that's computable can actually be solved
And again, I won't go into the details of what exactly with that that means
But the point is that at the time this was an open question that no one actually knew the answer to
Which which is why this paper was was so important?
But what's really remarkable is that this question which which was also known as the decision problem?
Or or more commonly at the time in German. It was known as the Entscheidungsproblem (which I'm probably horribly butchering)
and this problem was simultaneously answered by Turing's paper and both of these were published in 1936
And so Turing and Church independently solve this unsolved problem at the same time
Not knowing about each other's work, and they did it in completely different ways
Which is pretty remarkable because I think any time you can solve the same underlying problem using two completely different methods that that at first
Don't seem related
you know it suggests that there there might be some you know deeper more fundamental connection between these things and
Indeed as soon as Turing heard about Church's work, he added this appendix to his paper
In August 1936 he added this appendix where he basically proves that everything that lambda calculus can do so effective calculability
Is is basically the same as computability so everything that lambda calculus can calculate
It is something that his machine can compute and the converse everything his machine can compute is something that that
Can be calculated with lambda calculus and Church also came to the same conclusion and actually introduced the term to Turing machine
Which is now what we call
What Turing was originally calling the automatic machine
So in other words a Turing machine can completely
simulate lambda calculus and lambda calculus can completely simulate a Turing machine they're
computationally equivalent
And so all of this comes back to this question of what do we mean by computability?
Well, you know what is anything computable. What is anything calculable. Well. It's still this this kind of squishy intuitive
You know it when you see it kind of thing but with Turing machines and lambda calculus being these these very different things
That that turn out to be identical in terms of precisely what they can compute
Perhaps there is a single definition of computability and so the result is that there's this widely accepted thesis that the church-turing thesis
That says that when we say that something is computable that means it's computable by a Turing machine
So so an algorithm is is defined as anything that can be computed on a Turing machine, and that's it no more, no less
So if we want to make sure our computer is truly flexible enough to be programmed to do pretty much anything
You know as long as we make sure it can do anything a Turing machine can do then
Well know that we can program it to compute anything computable
So even though you know we can't write a program now to multiply two numbers
if we if we just ignore that
For a moment moment and just focus on you know making sure the computer can do everything a Turing machine can do you know when?
We're done with that
Then we'll know that we'll be able to write a program to do multiplication since you know surely
Multiplication is something that can be computed and not just multiplication. You know all of the amazing things that modern computers
Do are are based on on just this ability to compute any computable function you know that the brightness of this red pixel here is
Is really just the computation of a complex function with a bunch of different inputs that are constantly changing and being recomputed?
So if we go back to the instruction set for a computer you know when we started we're trying to figure out
Why we can't just use this add instruction somehow to write a program to multiply two numbers
And you know the problem is that our instruction set doesn't let us do everything a Turing machine can do, so let's figure out
What's missing if we think about what a Turing machine can do a Turing machine has a tape that can move?
You know left or right one position at a time and read or write the data at that position, so well. We've got RAM
We've got a load A, we've got a store A command
and
You know RAM is random access so we can read or write any position whenever we want so that's certainly at least as powerful as
A Turing machine in terms of being able to to read and write data from the well in our case the RAM
But the Turing machines case the tape
But the other thing the Turing machine can do is that after reading a cell it can take a different action?
so if the cell is blank it can move right if the cell is a 1 it can move left so it can take a
Different action based on what it reads
And we can't actually do that none of the instructions that we have actually does anything different based on the result of of any data
read from anywhere
So one thing that would give us that is a conditional jump instruction so something just like the jump instruction that we've already got that
skips to another instruction
But that only jumps sometimes based on some data value so for example
We have this program here if we load some data from address 14, and we subtract some some other data. That's in address 15
We might have this conditional jump instruction that
Conditionally jumps if the result of this subtraction is negative so in other words if the second value that we load is
Bigger than the first value in that case it jumps down to line six here and it does some stuff down here
Otherwise if the result of this subtraction is is not negative so this the second value here is not bigger than the first value
Then this this conditional jump instruction. Just doesn't do anything at all and
Execution just continues and we do this other stuff here, and then once we're done doing that other stuff
We might have a jump instruction that then that jumps us past
That at first block and continues execution down here
So this is basically kind of the same thing as if then else kind of thing so you might almost imagine it
Looking looking like this in a different language. So you could say like if you know some value in memory address 14
- memory address value and 15
Is less than 0, so we're loading 14, 15 subtracting that if that's less than 0 then we do some stuff
So that's this stuff here, otherwise we we do some other stuff which is this stuff here
And maybe it seems weird to have this instruction that says jump if the result of the previous subtraction is less than 0
That's kind of a weird thing
But it actually really doesn't matter what the conditional jump is actually looking at as long as we're able to take some kind of different
Action based on something discernable in memory that's enough to do what a Turing machine is doing
So just by adding one new instruction our computer will be turing-complete
Which means it can do anything a Turing machine can do which means it can compute anything computable?
Which is an awful lot so in the next video
I'll build the hardware for conditional jump
So we can actually turn this thing into a real computer and also actually write that program to multiply two numbers
Just to show that it's possible once It's turing-complete
You may want to try
Writing that program yourself
Well while you're waiting and maybe also think about you know what what sort of conditional jump
Instruction you would add because there's lots of different potential types of conditional jumps
We could add you know it doesn't really matter, which one we add
But you know you may want to think about that and and think about how you'd write a program to multiply now
There's one other thing that you might be wondering you may remember me mentioning that a Turing machine
uses this
Infinitely long tape and you might be wondering how we're going to
Be able to do everything the Turing machine can do with only 16 bytes of memory
Well you got me on that one that that's definitely a limitation so so in practice this will never truly be
Equivalent to a Turing machine because it will never have infinite memory
But hey you know neither is any computer and since 16 bytes of memory is
Not much further from infinity than 16 gigabytes of memory. I say will be close enough
You