6 ms·

The other thing is that UNIX wasn't built a start-up, it was built at Bell Labs. Google could be argued t be a modern bell-labs. Most modern start-ups avoid, a

by strlen 17y ago

The other thing is that UNIX wasn't built a start-up, it was built at Bell Labs. Google could be argued t be a modern bell-labs. Most modern start-ups avoid, at all costs, any systems programming (or doing anything at all beyond using a scripting language to read text from a database and display it on a screen). Note, however, I said most. There are startups solving serious scientific and engineering challenges. It's just "start-up" does not equate "lasting technological/scientific contribution".

nostrademons 17y ago
"Google could be argued t be a modern bell-labs." Particularly given the ridiculous number of ex-Bell-Labs employees at Google. One of the SVPs of Engineering at Google was formerly the VP in charge of the organization that birthed C, C++, UNIX, etc.
gridspy 17y ago
I think the key here is to avoid doing any work at all that is not your value proposition. If scripting languages are good enough and will benefit you, use them. We use Python, Twisted, Django, Matplotlib, JQuery, Movable Type, Postgresql all for this reason. Even our firmware is built as much as possible on a 3rd party neworking library and high level hardware building blocks.
- strlen 17y ago
  That's great for you (if it's money you're after), but it does make the start-up fairly uninteresting to someone who's interested in systems level development (and not just glueing together a product based on work others have done). Generally, top scientists/engineers are not motivated by money, which means given an offer from a typical ("glue a product together") start-up and Google they'd choose Google, unless they're looking for the "start-up experience". If you want top technical talent (who will always be able to find fulfilling and challenging work at the whatever the current Google-like company is, e.g. SGI in early 90s, Netscape in mid 90s, etc), you have to give them top technical challenges (which is how these companies have themselves been able to compete for talent when they were start-ups).
  - gridspy 17y ago
    Yes, that is my frustration also. I would rather be doing low level optimisation work, but I haven't yet found someone who wants to pay me for it. In the next 6 to 18 months, I am going to have to start swapping out the big building blocks with parts meant to scale. At that point there should be plenty of room for the systems engineers to join me.
    - strlen 17y ago
      That's fine then. It's better to use high level components to build a product that's correct (i.e. does what customers want it to do well) and then make it fast then build a fast, but incorrect product. Be careful, however, with treating scale as equivalent of performance. You have to design for scalability, not optimize for it: given the same algorithm, sorting a list of items in python might take 50 times as long as doing it in C; yet using an n^2 vs. n log(n) algorithm a 1 000 000 item list would take 50000 times as long to sort.
      - gridspy 17y ago
        Please excuse the tone of this post. I have spent a lot of time thinking about potential performance issues, and rationalising my choices. I'm a ACM ICPC (programming contest) finalist, and have competed in the Google Codejam, so I know about big-oh. Anyway, who implements a sorting algorithm in pure Python? I use the builtin sort() function, which is implemented in C (making callbacks into python for comparisons for some types). It uses TimSort - an approach designed to minimise the number of comparisons. http://svn.python.org/projects/python/trunk/Objects/listsort.txt http://svn.python.org/projects/python/trunk/Objects/listsort... I thought you were going to point out that I should ensure that my system is modular (stateless, partitioned, etc) and I can spread the load across several machines - I can. You are right that I could make a screaming fast bubble sort and still end up with major issues. Fortunately I already have had that epiphany while solving ACM practice problems. I appreciate your advice, there are far too many who haven't yet understood it.
        strlen 17y ago

by strlen 17y ago

nostrademons 17y ago

"Google could be argued t be a modern bell-labs." Particularly given the ridiculous number of ex-Bell-Labs employees at Google. One of the SVPs of Engineering at Google was formerly the VP in charge of the organization that birthed C, C++, UNIX, etc.

gridspy 17y ago

I think the key here is to avoid doing any work at all that is not your value proposition. If scripting languages are good enough and will benefit you, use them. We use Python, Twisted, Django, Matplotlib, JQuery, Movable Type, Postgresql all for this reason. Even our firmware is built as much as possible on a 3rd party neworking library and high level hardware building blocks.

strlen 17y ago
That's great for you (if it's money you're after), but it does make the start-up fairly uninteresting to someone who's interested in systems level development (and not just glueing together a product based on work others have done). Generally, top scientists/engineers are not motivated by money, which means given an offer from a typical ("glue a product together") start-up and Google they'd choose Google, unless they're looking for the "start-up experience". If you want top technical talent (who will always be able to find fulfilling and challenging work at the whatever the current Google-like company is, e.g. SGI in early 90s, Netscape in mid 90s, etc), you have to give them top technical challenges (which is how these companies have themselves been able to compete for talent when they were start-ups).
- gridspy 17y ago
  Yes, that is my frustration also. I would rather be doing low level optimisation work, but I haven't yet found someone who wants to pay me for it. In the next 6 to 18 months, I am going to have to start swapping out the big building blocks with parts meant to scale. At that point there should be plenty of room for the systems engineers to join me.
  - strlen 17y ago
    That's fine then. It's better to use high level components to build a product that's correct (i.e. does what customers want it to do well) and then make it fast then build a fast, but incorrect product. Be careful, however, with treating scale as equivalent of performance. You have to design for scalability, not optimize for it: given the same algorithm, sorting a list of items in python might take 50 times as long as doing it in C; yet using an n^2 vs. n log(n) algorithm a 1 000 000 item list would take 50000 times as long to sort.
    - gridspy 17y ago
      Please excuse the tone of this post. I have spent a lot of time thinking about potential performance issues, and rationalising my choices. I'm a ACM ICPC (programming contest) finalist, and have competed in the Google Codejam, so I know about big-oh. Anyway, who implements a sorting algorithm in pure Python? I use the builtin sort() function, which is implemented in C (making callbacks into python for comparisons for some types). It uses TimSort - an approach designed to minimise the number of comparisons. http://svn.python.org/projects/python/trunk/Objects/listsort.txt http://svn.python.org/projects/python/trunk/Objects/listsort... I thought you were going to point out that I should ensure that my system is modular (stateless, partitioned, etc) and I can spread the load across several machines - I can. You are right that I could make a screaming fast bubble sort and still end up with major issues. Fortunately I already have had that epiphany while solving ACM practice problems. I appreciate your advice, there are far too many who haven't yet understood it.
      - strlen 17y ago