6 ms·

The other day I met with someone who was visiting my city to attend a big ML conference. In the course of our discussion, it transpired this person did not kno

by xamuel 9y ago

The other day I met with someone who was visiting my city to attend a big ML conference. In the course of our discussion, it transpired this person did not know the Halting Problem. He'd "heard of" Turing machines, but nothing more than "hearing" of them. Gatekeepers shouldn't keep gates just for gatekeeping sake. But if so-called ML experts don't even know undergraduate computer science, that should really give you pause before you open up your wallet for them.

eanzenberg 9y ago
Why? Most of that cruft is abstracted away, computation only gets cheaper over time (a world class AI rig cost ~30k, a decent one for 2k) and most applications of ML run on commodity hardware.
- xamuel 9y ago
  For one thing, it suggests that they are actually technicians, not the scientists they're selling themselves as. That's fine if you want a technician (and if they're charging technician's rates).
  - eanzenberg 9y ago
    And then that technician rate is X times what a technician rate would be for pure software dev.. what is your point?
  - opencl 9y ago
    I think when it comes to ML the CS experts with limited statistics knowledge are the technicians and the statistics experts with limited CS knowledge are the scientists, not the other way around.
grad_ml 9y ago
"turing machines" are cs 101?
- xamuel 9y ago
  Amended that to "undergraduate computer science"
joshuamorton 9y ago
Why does an ML-expert need to know the halting problem? Considering that ML is really a CS-oriented form of statistics, why would you expect a statistician to know CS theory?
- xamuel 9y ago
  Thinking more, it's the misleading names ("machine learning", "AI") that rustle my jimmies so much. Sure, you don't need to know the halting problem to approximately solve MNIST by fitting a million-parameter curve to a dataset. But you're misleading people if you're claiming to have any kind of insight into how computers can be made intelligent, or how computers can "learn", when you don't even know the halting problem.
  - joshuamorton 9y ago
    Does this just come down to a semantic idea that if something isn't in pursuit of AGI, its not really AI? That feels unfair to most of these researchers who absolutely disagree with that. And to consider these algorithms to not "learn" is similarly unfair. They do. They learn to solve specific problems (at least right now), but they do learn.
  - xapata 9y ago
    I guess "dynamic programming" must really bother you. That field was named completely arbitrarily, to secure funding. The more you look around, the more you find science concepts are named for marketing purposes. Heck, "data scientist" is a bit of nonsense.
  - dannypgh 9y ago
    I disagree. Frankly, for a lot of people and a lot of contexts, I don't think the halting problem is particularly important. You're using understanding of it as a shibboleth for exposure to common curricula about theoretical computation. But you can even know a lot about practical computation and not know anything about the halting problem. Curious: has your knowledge of the halting problem ever actually saved you time or effort in your work? If so, how? Turing's work on the limitations of his machine are interesting, and I'm sure people with a deep understanding of them can advance the study of computation. I think you're just being dismissive of skillsets which aren't your own. I think you're just bothered by the fact that AI and ML are being advanced more by people with more knowledge of linear algebra and statistics than computer science. And realize that it's the arrogant among them that will dismiss you as "just a technician." Anyone who is looking down on either "scientists" or "technicians" should get over themselves.
sannee 9y ago
> But if so-called ML experts don't even know undergraduate computer science To be fair, Machine learning seems more closely related to applied mathematics - statistics/optimization than to computer science.
HumanDrivenDev 9y ago
Maybe I'm an iconoclast, but I'd respect that person more for not trying to bullshit his way out of it.
- xamuel 9y ago
  That's a great point. It shines a positive light on the gentleman I spoke with, and a negative light on the industry as a whole (if bs is so rampant that merely admitting not knowing something makes someone shine)
istorical 9y ago
How does knowing that it's impossible to predict whether an infinite loop exists in a piece of code yield an actionable piece of wisdom that this ML expert should have? I'd suppose that most developers, formal education or not, would have encountered an infinite loop at some point in their initial work with iteration or recursion. How does knowing that Turing proved you can't predict this bug in a piece of code change anything? I might genuinely be missing something important here - not trying to be snarky in my questioning. It seems like obviously infinite loops are a disastrous bug for critical code - but what does knowing the formal name of the problem and background of its discovery give you? I could understand if you were arguing in favor of test code or static analysis.
- deleted 9y ago
  [deleted]
eanzenberg 9y ago
I could have the same reverse worldview: "I attended a big software dev conference. Someone I met did not know about data bias. They heard of gradient boosting but nothing more than hearing them. If so-called dev experts don't even know undergraduate statistics, that should really give you pause before you open up your wallet for them."

by xamuel 9y ago

eanzenberg 9y ago

Why? Most of that cruft is abstracted away, computation only gets cheaper over time (a world class AI rig cost ~30k, a decent one for 2k) and most applications of ML run on commodity hardware.

xamuel 9y ago
For one thing, it suggests that they are actually technicians, not the scientists they're selling themselves as. That's fine if you want a technician (and if they're charging technician's rates).
- eanzenberg 9y ago
  And then that technician rate is X times what a technician rate would be for pure software dev.. what is your point?
- opencl 9y ago
  I think when it comes to ML the CS experts with limited statistics knowledge are the technicians and the statistics experts with limited CS knowledge are the scientists, not the other way around.

grad_ml 9y ago

"turing machines" are cs 101?

xamuel 9y ago
Amended that to "undergraduate computer science"

joshuamorton 9y ago

Why does an ML-expert need to know the halting problem? Considering that ML is really a CS-oriented form of statistics, why would you expect a statistician to know CS theory?

xamuel 9y ago
Thinking more, it's the misleading names ("machine learning", "AI") that rustle my jimmies so much. Sure, you don't need to know the halting problem to approximately solve MNIST by fitting a million-parameter curve to a dataset. But you're misleading people if you're claiming to have any kind of insight into how computers can be made intelligent, or how computers can "learn", when you don't even know the halting problem.
- joshuamorton 9y ago
  Does this just come down to a semantic idea that if something isn't in pursuit of AGI, its not really AI? That feels unfair to most of these researchers who absolutely disagree with that. And to consider these algorithms to not "learn" is similarly unfair. They do. They learn to solve specific problems (at least right now), but they do learn.
- xapata 9y ago
  I guess "dynamic programming" must really bother you. That field was named completely arbitrarily, to secure funding. The more you look around, the more you find science concepts are named for marketing purposes. Heck, "data scientist" is a bit of nonsense.
- dannypgh 9y ago
  I disagree. Frankly, for a lot of people and a lot of contexts, I don't think the halting problem is particularly important. You're using understanding of it as a shibboleth for exposure to common curricula about theoretical computation. But you can even know a lot about practical computation and not know anything about the halting problem. Curious: has your knowledge of the halting problem ever actually saved you time or effort in your work? If so, how? Turing's work on the limitations of his machine are interesting, and I'm sure people with a deep understanding of them can advance the study of computation. I think you're just being dismissive of skillsets which aren't your own. I think you're just bothered by the fact that AI and ML are being advanced more by people with more knowledge of linear algebra and statistics than computer science. And realize that it's the arrogant among them that will dismiss you as "just a technician." Anyone who is looking down on either "scientists" or "technicians" should get over themselves.

sannee 9y ago

> But if so-called ML experts don't even know undergraduate computer science To be fair, Machine learning seems more closely related to applied mathematics - statistics/optimization than to computer science.

HumanDrivenDev 9y ago

Maybe I'm an iconoclast, but I'd respect that person more for not trying to bullshit his way out of it.

xamuel 9y ago
That's a great point. It shines a positive light on the gentleman I spoke with, and a negative light on the industry as a whole (if bs is so rampant that merely admitting not knowing something makes someone shine)

istorical 9y ago

How does knowing that it's impossible to predict whether an infinite loop exists in a piece of code yield an actionable piece of wisdom that this ML expert should have? I'd suppose that most developers, formal education or not, would have encountered an infinite loop at some point in their initial work with iteration or recursion. How does knowing that Turing proved you can't predict this bug in a piece of code change anything? I might genuinely be missing something important here - not trying to be snarky in my questioning. It seems like obviously infinite loops are a disastrous bug for critical code - but what does knowing the formal name of the problem and background of its discovery give you? I could understand if you were arguing in favor of test code or static analysis.

deleted 9y ago
[deleted]

eanzenberg 9y ago

I could have the same reverse worldview: "I attended a big software dev conference. Someone I met did not know about data bias. They heard of gradient boosting but nothing more than hearing them. If so-called dev experts don't even know undergraduate statistics, that should really give you pause before you open up your wallet for them."