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It's really depressing that a lot of machine learning tasks can now be performed without much programming knowledge and even less knowledge about machine learni

It's really depressing that a lot of machine learning tasks can now be performed without much programming knowledge and even less knowledge about machine learning...

cookingrobot 8y ago
Why?
TheSpiceIsLife 8y ago
Why is that depressing? I use heaps of tools I probably couldn't create myself, or at least don't have the gumption to try.
- deleted 8y ago
  [deleted]
sgt101 8y ago
It's interesting though, you can do most (all?) statistics using R with very little (or almost no) programming, or knowledge of statistics.
- conjectures 8y ago
  I can use power tools, but you sure as hell don't want me building your extension.
  - sgt101 8y ago
    Yup, this is what I think, trouble ahead I think!
kayoone 8y ago
abstracting the complexities away and making the technology more accessible is a good and inevitable thing. Do you think academic gatekeeping and elitism have more value? Doesn't mean that there is no room for experts with deep understanding though.
heinrichf 8y ago
Replace "depressing" by "dangerous in the case of certain applications" and we can agree: https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction
- deleted 8y ago
  [deleted]
hnuser123456 8y ago
Did you mean "exciting"? A few steps of matrix multiplication shouldn't require extensive programming knowledge. Backpropagation is intuitive to someone who already understands algebra and calculus. It doesn't take much knowledge. Creating useful models still requires real practical skills, especially for high confidence levels in complex datasets.
- bayesian_horse 8y ago
  It's exciting unless you have invested considerable time in learning data-science and machine learning from the ground up and want to make money from it. Yes, it still needs that expertise to run models well. But those without the expertise sound more confident and then ruin the market with the expectations they elicit.
j7ake 8y ago
If the problem is standard to the point where you won't encounter any weird edge cases (e.g., runs analogously as it does in a tutorial on the internet) , then you don't need programming or machine learning to perform the tasks. But once you want to extend a problem into an unfamiliar domain or debug why an algorithm is not working, then I don't see how you can accomplish this without domain-specific and machine learning knowledge. Or have I been missing out on some amazing auto-debugging AI that I am unaware of?
no1youknowz 8y ago
Depressing why? Oh I know. Because you are an elitist who believes that what can come from AI should only belong to those who can code it? Or because your own lively hood is dependent on machine learning? Whatever the case may be and my response is that I don't care. I firmly believe that this is a GOOD thing. As developers we should be striving for a) open sourcing machine learning so that everyone can contribute to the good it can do and b) that we democratise the result of those efforts so that everyone can benefit from it for their own projects. When time goes forward these efforts will translate into an NPM of machine learning. What would have taken a small team and a year to do, now just takes installing a plugin and having an API at the developers disposal. This is definitely a future that I cannot wait to see and it's within reach. Out of the 3, AN (Narrow) I, AG (General) I and AS (Super) I. Artificial Narrow Intelligence is going to grow in prevalence in the next 10 years and the effects will be very good. I don't think it will kill jobs, merely make people much more productive.
- RestlessMind 8y ago
  > As developers we should be striving for a) open sourcing machine learning so that everyone can contribute to the good it can do and b) that we democratise the result of those efforts so that everyone can benefit from it for their own projects. Why? Oh I know. You are a wild-eyed optimist who would have cheered unfettered globalization in late 90's because "the whole can benefit from it". You know what - as developers, we should care about maintaining scarcity of developers around the world so that we can continue being in demand and continue having great salaries. I would rather be a part of AMA (cartel which limits supply of Doctors in the USA and erects legal/regulatory barriers for competitors, thereby ensuring high standard of life for Doctors) than being a manufacturing engineer whose job was lost (or threatened) first by globalization and now by automation. You know who benefits from "democratization of results of our efforts" or when "everyone can contribute to the good machine learning" (or other software engineering in general)? VCs and mega-rich folks, whose capital now doesn't have to share productivity gains with labor because labor is abundantly available.

It's really depressing that a lot of machine learning tasks can now be performed without much programming knowledge and even less knowledge about machine learning...

cookingrobot 8y ago

Why?

TheSpiceIsLife 8y ago

Why is that depressing? I use heaps of tools I probably couldn't create myself, or at least don't have the gumption to try.

deleted 8y ago
[deleted]

sgt101 8y ago

It's interesting though, you can do most (all?) statistics using R with very little (or almost no) programming, or knowledge of statistics.

conjectures 8y ago
I can use power tools, but you sure as hell don't want me building your extension.
- sgt101 8y ago
  Yup, this is what I think, trouble ahead I think!

kayoone 8y ago

abstracting the complexities away and making the technology more accessible is a good and inevitable thing. Do you think academic gatekeeping and elitism have more value? Doesn't mean that there is no room for experts with deep understanding though.

heinrichf 8y ago

Replace "depressing" by "dangerous in the case of certain applications" and we can agree: https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction

deleted 8y ago
[deleted]

hnuser123456 8y ago

Did you mean "exciting"? A few steps of matrix multiplication shouldn't require extensive programming knowledge. Backpropagation is intuitive to someone who already understands algebra and calculus. It doesn't take much knowledge. Creating useful models still requires real practical skills, especially for high confidence levels in complex datasets.

bayesian_horse 8y ago
It's exciting unless you have invested considerable time in learning data-science and machine learning from the ground up and want to make money from it. Yes, it still needs that expertise to run models well. But those without the expertise sound more confident and then ruin the market with the expectations they elicit.

j7ake 8y ago

If the problem is standard to the point where you won't encounter any weird edge cases (e.g., runs analogously as it does in a tutorial on the internet) , then you don't need programming or machine learning to perform the tasks. But once you want to extend a problem into an unfamiliar domain or debug why an algorithm is not working, then I don't see how you can accomplish this without domain-specific and machine learning knowledge. Or have I been missing out on some amazing auto-debugging AI that I am unaware of?

no1youknowz 8y ago

Depressing why? Oh I know. Because you are an elitist who believes that what can come from AI should only belong to those who can code it? Or because your own lively hood is dependent on machine learning? Whatever the case may be and my response is that I don't care. I firmly believe that this is a GOOD thing. As developers we should be striving for a) open sourcing machine learning so that everyone can contribute to the good it can do and b) that we democratise the result of those efforts so that everyone can benefit from it for their own projects. When time goes forward these efforts will translate into an NPM of machine learning. What would have taken a small team and a year to do, now just takes installing a plugin and having an API at the developers disposal. This is definitely a future that I cannot wait to see and it's within reach. Out of the 3, AN (Narrow) I, AG (General) I and AS (Super) I. Artificial Narrow Intelligence is going to grow in prevalence in the next 10 years and the effects will be very good. I don't think it will kill jobs, merely make people much more productive.

RestlessMind 8y ago
> As developers we should be striving for a) open sourcing machine learning so that everyone can contribute to the good it can do and b) that we democratise the result of those efforts so that everyone can benefit from it for their own projects. Why? Oh I know. You are a wild-eyed optimist who would have cheered unfettered globalization in late 90's because "the whole can benefit from it". You know what - as developers, we should care about maintaining scarcity of developers around the world so that we can continue being in demand and continue having great salaries. I would rather be a part of AMA (cartel which limits supply of Doctors in the USA and erects legal/regulatory barriers for competitors, thereby ensuring high standard of life for Doctors) than being a manufacturing engineer whose job was lost (or threatened) first by globalization and now by automation. You know who benefits from "democratization of results of our efforts" or when "everyone can contribute to the good machine learning" (or other software engineering in general)? VCs and mega-rich folks, whose capital now doesn't have to share productivity gains with labor because labor is abundantly available.