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Travis Oliphant

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2021-09-23
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2021-09-23
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  1. “And it's a really important concept. And not having it means you have to develop it several times. And those times may not share an approach. One of the common things in programming, one of the things programming enables is abstractions. But when you have shared abstractions, it's even better. It sort of gets to the level of language of actually we all think of this the same way, which is both powerful and dangerous Because powerful in that we now can quickly make bigger and higher level things on top of those abstractions dangerous because it also limits us as to the things we left behind in producing that abstraction, which is at the heart of programming today and actually building around the programming world. So I think it's a fascinating philosophical topic. Yeah, that will continue.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “Some will lose. That's exactly right. But it had no math to it. So numeric had math and a basic way to think and erase. So I was looking for that and it had complex numbers. A lot of programming languages, and you can see it because if you're just a computer scientist, you think, ah, complex number is just too float. So people can build that on. But in practice, a complex number is one of the significant algebras that helps connect a lot of physical and mathematical ideas, particularly to FFT for an electrical engineer.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “There was a one dimensional byte concept, but there was no n dimensional, two, three, four-dimensional tensor, they call it now. I'm still in the category that a tensor is another thing. And it's just an MD array. We should call it. Of lost that battle as many battles in this.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “Jim Huganen, and I went back and read the mailing list to see the history of how it grew. There was a very interesting, fascinating to do that, actually, to see how this emergent cooperation, unstructured cooperation happens in the open source world that led to a lot of this collective programming, which is something maybe we might get into a little later about what that looks like.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “Taking information from satellites, I was an electrical engineering student, used to taking information and trying to get something out of it, doing some data processing, getting information out of it. And I'd done that in MATLAB. I'd done that in Perl. I'd done that in scripting on a VMS. There's actually a Vax VMS system, and they had their own little scripting tools around Fortran. Done a lot of that. As a graduate student, I was looking for something and encounter Python. And because Python had an array, had two things that made me not filter it away because I was filtering a bunch of stuff as Yorick. I looked at Yorick. I looked at a few other languages that are out there at the time in 1997, but it had arrays. There's a library called Numeric that had just been written in 95, like not very. Not too much earlier by an MIT alum”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “Good question. It was a process, it took about a year. I first encountered Python in 1997. I was a graduate student studying biomedical engineering at the Mayo Clinic. And I had previously been involved.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “I completely agree. I'm very much in that vein of there's a lot of genius out there that we miss. And it's sort of fortunate when it bubbles up into something that we can understand or process. There's a lot we miss. I tend to lean towards really loving democratization or things that empower people or I'm very resistant to sort of authoritarian structures fundamentally for that reason several reasons but it just hurts us yeah We're worse off”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “It was too rudimentary early on. It was a lot of work to actually take a thought you'd have and actually get it implemented. And that's still work, but it's getting easier. And so, yeah, I would say that's definitely what's attracting me to Python is that that was more real, right? I could think in Python. Speaking of foreign language, I only speak another language fluently besides English, which is Spanish. And I remember the day when I would dream in Spanish. And you start to think in that language. And then you actually, I do definitely believe that language limits or expands your thinking. There are some languages that actually lead you to certain thought processes.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “I've always loved math. A lot of people think they don't like math because I think when they're exposed to it early, it's about memory. When you're exposed to math early, you have a good short term memory member's timetables. And I do have a reasonably, I mean, not perfect, but a reasonably long short-term memory buffer. And so I did great at times tables. I said, oh, I'm good at math. But I started to really like math, just the problem solving aspect. And so computing was problem solving applied. And so that's always kind of been the draw, coupled with the mathematics.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  10. “It was basic And then they had a visit calc. And so a little bit of spreadsheet programming in VisiCalc, but mostly just some basics.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  11. “Processors would not. Yeah, the Timex Sinclair was one of the very first. It was a cheap, cheap, I think it was, well, it was still expensive, but it was $2K of memory. We got the 16K add-on pack. But yeah, it had memory and you could program it. You had the, in order to store your programs, you had to attach a tape drive. Remember that old, the sound that would play when you converted the modem that would convert digital bits to audios file, sent on a tape drive. Still remember that sound. But that was the storage.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  12. “Oh man, good question. I think actually when I was 10, you know, my dad got us a Timex Sinclair. And he was excited about the spreadsheet capability, but I made him get the basic add-ons we could actually program in basic. And just being able to write instructions and have the computer do something. Then we got a TI 994A when I was about 12. And I would just, it had sprites and graphics and music you could actually program us to do music. That's when I really sort of fell in love with programming.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  13. “No, I didn't take C until the next year in college. I had a course in C, but I haven't done much in Pascal. Just that AP Computer Science course.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  14. “I didn't see that until high school when I took an AP computer science course. I did a lot of other kinds of just programming and TI. Finally, when I took an AP computer science course in Pascal. Yeah, it was Pascal. That's when I, oh, there are these principles.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  15. “It's a good question. I think it was in fourth grade. Just a simple loop in basic. I think, or maybe it was an Atari 800. It was a part of a class, and we just were just basic loops to print things out.”

    2021-09-23 · Lex Fridman Podcast · #224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming · IDENTIFIED FROM THE TRANSCRIPT · source