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Simon Peyton Jones completely different sort of computer architecture. That phase lasted from about 1980 to 1990 radical architectures for functional programming. I now regard it as slightly misdirected but nevertheless it was terribly exciting. Lazy evaluation was another huge motivating factor. With the benefit of hindsight I now think lazy evaluation is just wonderful but at that time it was sort of pivotal. Lazy evaluation is this idea that functions don t evaluate their arguments. Again the motivating factor was something to do with it being beautiful or elegant and unusual and radical. That s kind of good for catching the imagination: it looks as if this might be a way of thinking about programming in a whole new way. Rather than just putting one more brick in the wall, we can build a whole new wall. That s very exciting. I was strongly motivated by that. Was it just that it was a neat trick In some ways I think neat tricks are very significant. Lazy evaluation was just so neat and you could do such remarkable different things that you wouldn t think were possible. Seibel: Like what Peyton Jones: I remember my friend John Hughes wrote a program for me. For a project I was doing two implementations of the lambda calculus and comparing their performance, so John gave me some test programs. One of them was a program that computed the decimal expansion of e to arbitrary precision. It was a lazy program it was rather beautiful because it produced all the digits of e. Seibel: Eventually. Peyton Jones: Eventually, that s right. But it was up to the consumer. You didn t have to say how many digits to produce in advance. You just got given this list and you kept hauling on elements of the list and it wouldn t give you another digit until it had spent enough cycles computing it. So that s not something that s very obvious to do if you re writing a C program. Actually you can do it with enough cleverness. But it s not a natural programming paradigm for C. You can almost only do it once you ve seen the lazy functional program. Whereas John s program was just about four or five lines. Amazing.
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Simon Peyton Jones Seibel: Other languages have since special-cased that kind of computation with, for example, generators in Python or something where you can yield values. Was there something that made you say, Aha; there are lots of things that could be fruitfully looked at as an infinite series of computations from which we just want to draw answers until we re tired of it As opposed to saying, Oh, that s an interesting technique for certain problems but not the basis for everything. Peyton Jones: I think at this stage I wasn t as reflective as that. I just thought it was so cool. And fun. I think it s important to do what you find motivating and interesting and follow it. I just found it very inspiring. I don t think I really thought there are deep principled reasons why this is the way to do programming. I just thought it was a rather wonderful way to do programming. I like skiing. Well, why do I like skiing Not because it s going to change the world just because it s a lot of fun. I now think the important thing about laziness is that it kept us pure. You ll have seen this in several of my talks probably. But I actually really like laziness. Given a choice I d choose a lazy language. I think it s really helpful for all kinds of programming things. I m sure you ve read John Hughes s paper, Why Functional Programming Matters. It s probably the earliest articulate exposition of why laziness might be important in more than a cute way. And his main story is that it helps you write modular programs. Lazy evaluation lets you write generators his example is generate all the possible moves in your chess game separately from your consumer, which walks over the tree and does alpha-beta minimaxing or something. Or if you re generating all the sequence of approximations of an answer, then you have a consumer who says when to stop. It turns out that by separating generators from consumers you can modularly decompose your program. Whereas, if you re having to generate it along with a consumer that s saying when to stop, that can make your program much less modular. Modular in the sense of separate thoughts in separate places that can be composed together. John s paper gives some nice examples of ways in which you can change the consumer or change the generator, independently from each other, and that lets you plug together new programs that would have been more difficult to get by modifying one tightly interwoven one.
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