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> what was all that effort being spent on Not being left behind if you're wrong. I'm in a tech-adjacent industry and see it all the time. Competitor A comes o

> what was all that effort being spent on Not being left behind if you're wrong. I'm in a tech-adjacent industry and see it all the time. Competitor A comes out with "shiny new technology" and markets the hell out of it. My company panics because we're suddenly lagging behind and rushes a competing project into development. Competitor B sees all of this and hops in too. All of a sudden it's the new direction of the industry and dominating trade shows, despite the origin being a mediocre product with some clever marketing. 5 years later it's never spoken of again. I'm not familiar enough to say for sure this is what happened with "blockchain", but from a distance it has a lot of familiar markers.

johnchristopher 9y ago
An example from the top of your head ?
- scrooched_moose 9y ago
  GPU acceleration in scientific computing. My god in 2011 it was the only thing anyone talked about. Every COTS solver package cobbled together support in less than a year and were promising order of magnitude speedups. In 2018 it's still hanging around but realizing a 20% speedup on certain classes of problems. Maybe.
  - bushin 9y ago
    Amdahl's law strikes again.
  - saganus 9y ago
    Didn't that tech shifted to AI/ML? Isn't that considered scientific computing by some measure? I'm definitely not an expert so I'm maybe missing something here.
    - scrooched_moose 9y ago
      "Scientific Computing" was probably too general of a term to use. I focus more on FEA/CFD type problems where it's effectively been a bust. Most of our benchmarks show 8 cpu cores + 1 GPU is roughly equivalent to 10 cpu cores, and a second GPU has little additional benefit. I'm sure there are other disciplines that have seen a larger benefit.
  - sndean 9y ago
    > GPU acceleration in scientific computing > it's still hanging around but realizing a 20% speedup on certain classes of problems It really varies though. In grad school I felt like god when some molecular dynamics simulations running on my pair of GTX 760s finished faster than the same thing running on my advisor's 96-core CPU cluster. Point taken, though, that it was over-hyped. There were lots of conference presentations with GPU-acceleration in the title (kind of like deep learning is now).
    - thanatropism 9y ago
      Wasn't your advisor just using a smaller, more conservative value for h?
  - wsxcde 9y ago
    Relevant war story: I was one of the engineers who initially started looking at GPGPU computing at one of my former employers. This was circa 2007 and people were getting really excited thanks largely to NVIDIA's hype machine. 2007 BTW, was when the first Teslas were making their way into the wild. I was part of a group that developed signal processing algorithms and my boss's boss pulled me aside and asked me what we ought to do about this stuff. I told him that there are a few applications where this works very well, but it's pretty niche overall and we shouldn't do more than what we'd already done. He was a bit surprised because he thought I'd be one of the kool-aid drinkers given how much I knew about and liked playing with the tech. But he deferred to my judgement. It turned out to be one of the most significant conversations I've had. I was still a junior engineer fresh out of college, but my bosses realized that I could be trusted put aside naive enthusiasm about the tech and make cool-headed decisions about what was strategically important. And I learned to trust my intuition about what was useful and what was just hype.
  - neuromantik8086 9y ago
    At the same time, I really wish that GPUs would take off in neuroimaging, where 90% of the steps performed in an analysis pipeline are not modeling-related, but rather basic image manipulations / pre-processing (i.e., scaling, smoothing; stuff that GPUs are actually good at).
- tangue 9y ago
  Semantic web related technologies. Oh man, this was the future rdf triplets, ontologies ...
- namdnay 9y ago
  "Digital Transformation"
  - fs111 9y ago
    that one is still hot, according to our marketing...
  - thanatropism 9y ago
    Well, "digital transformation" is not a technology -- it's this strategic paradigm of how technology is diffused across an organization. The opposite of "digital transformation" is "IT infrastructure" -- the idea that technology works as an infrastructural layer supporting business operations, rather than dispersed across operations themselves. "IT" has for long been this back-office area where specialists get to dictate business policies because they know computers. (A classic on this genre is the Bastard Operator from Hell [0]) -- but now lusers bring their own computers and phones to work, and hell if they don't have technological ideas of their own. IT has been commoditized, cloudified, outsourced. If "digital transformation" sounds bogus is because management consultants are bogus. But in practice it can be a real thing that's not as much about new sexy tech (in the sense of blockchains, RISC chips and so on) as about putting what's already available into operation using business knowledge. [0] https://en.wikipedia.org/wiki/Bastard_Operator_From_Hell https://en.wikipedia.org/wiki/Bastard_Operator_From_Hell
- deleted 9y ago
  [deleted]
- mooneater 9y ago
  X. M. L.

johnchristopher 9y ago

An example from the top of your head ?

scrooched_moose 9y ago
GPU acceleration in scientific computing. My god in 2011 it was the only thing anyone talked about. Every COTS solver package cobbled together support in less than a year and were promising order of magnitude speedups. In 2018 it's still hanging around but realizing a 20% speedup on certain classes of problems. Maybe.
- bushin 9y ago
  Amdahl's law strikes again.
- saganus 9y ago
  Didn't that tech shifted to AI/ML? Isn't that considered scientific computing by some measure? I'm definitely not an expert so I'm maybe missing something here.
  - scrooched_moose 9y ago
    "Scientific Computing" was probably too general of a term to use. I focus more on FEA/CFD type problems where it's effectively been a bust. Most of our benchmarks show 8 cpu cores + 1 GPU is roughly equivalent to 10 cpu cores, and a second GPU has little additional benefit. I'm sure there are other disciplines that have seen a larger benefit.
- sndean 9y ago
  > GPU acceleration in scientific computing > it's still hanging around but realizing a 20% speedup on certain classes of problems It really varies though. In grad school I felt like god when some molecular dynamics simulations running on my pair of GTX 760s finished faster than the same thing running on my advisor's 96-core CPU cluster. Point taken, though, that it was over-hyped. There were lots of conference presentations with GPU-acceleration in the title (kind of like deep learning is now).
  - thanatropism 9y ago
    Wasn't your advisor just using a smaller, more conservative value for h?
- wsxcde 9y ago
  Relevant war story: I was one of the engineers who initially started looking at GPGPU computing at one of my former employers. This was circa 2007 and people were getting really excited thanks largely to NVIDIA's hype machine. 2007 BTW, was when the first Teslas were making their way into the wild. I was part of a group that developed signal processing algorithms and my boss's boss pulled me aside and asked me what we ought to do about this stuff. I told him that there are a few applications where this works very well, but it's pretty niche overall and we shouldn't do more than what we'd already done. He was a bit surprised because he thought I'd be one of the kool-aid drinkers given how much I knew about and liked playing with the tech. But he deferred to my judgement. It turned out to be one of the most significant conversations I've had. I was still a junior engineer fresh out of college, but my bosses realized that I could be trusted put aside naive enthusiasm about the tech and make cool-headed decisions about what was strategically important. And I learned to trust my intuition about what was useful and what was just hype.
- neuromantik8086 9y ago
  At the same time, I really wish that GPUs would take off in neuroimaging, where 90% of the steps performed in an analysis pipeline are not modeling-related, but rather basic image manipulations / pre-processing (i.e., scaling, smoothing; stuff that GPUs are actually good at).
tangue 9y ago
Semantic web related technologies. Oh man, this was the future rdf triplets, ontologies ...
namdnay 9y ago
"Digital Transformation"
- fs111 9y ago
  that one is still hot, according to our marketing...
- thanatropism 9y ago
  Well, "digital transformation" is not a technology -- it's this strategic paradigm of how technology is diffused across an organization. The opposite of "digital transformation" is "IT infrastructure" -- the idea that technology works as an infrastructural layer supporting business operations, rather than dispersed across operations themselves. "IT" has for long been this back-office area where specialists get to dictate business policies because they know computers. (A classic on this genre is the Bastard Operator from Hell [0]) -- but now lusers bring their own computers and phones to work, and hell if they don't have technological ideas of their own. IT has been commoditized, cloudified, outsourced. If "digital transformation" sounds bogus is because management consultants are bogus. But in practice it can be a real thing that's not as much about new sexy tech (in the sense of blockchains, RISC chips and so on) as about putting what's already available into operation using business knowledge. [0] https://en.wikipedia.org/wiki/Bastard_Operator_From_Hell https://en.wikipedia.org/wiki/Bastard_Operator_From_Hell
deleted 9y ago
[deleted]
mooneater 9y ago
X. M. L.