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We might be headed for the trough of disillusionment, but in terms of technology and industry applications, we are still in the early phase of modern AI (big da

We might be headed for the trough of disillusionment, but in terms of technology and industry applications, we are still in the early phase of modern AI (big data + ML).

VBprogrammer 7y ago
I'm doing a bit of hiring at the moment. It's hard to find a single CV which doesn't have some kind of machine learning slant. As much as I think there are plenty of advances in ML left to take, I doubt every graduate will step out into a good application for existing machine learning tools.
- misterman0 7y ago
  Just like not all astrophysicists reach Nobel prize level achievements not all machine-learning graduates will innovate in their field. But to help you out, in order to find people who are likely to innovate, find out if that is their goal. If it is not then you know not to hire them. But if that's their goal, maybe start some kind of "program" where you give these people a chance. 6 months. A year maybe. If the are close to something or if you're pleased with them even though they aren't really innovating, then give them a "tenure" so to speak. An evaluation process, it's very common here in Sweden. I mean how much money can you really loose in six months? You can kick that shithole straight out day one if that's your perogative. It's a good deal for both parties.
  - VBprogrammer 7y ago
    Sorry if I wasn't clear, our problems are CRUD at modest scale. There is little room for the application of machine learning.
    - dspillett 7y ago
      > There is little room for the application of machine learning You see people trying to shoehorn ML into many such system though, and there is money in it, which is why people are chasing it to have it on their CVs. Like the noSQL hype of a some years ago it'll settle down and people will gravitate back more towards the right tool for the job (which will sometimes be ML based, but often not, just as "noSQL" is sometimes the right tool or right enough). ML will survive where it is the best tool for the job, or at least where it can be genuinely useful and not significantly sub-optimal. > our problems are CRUD at modest scale. I see some of our client base looking into ML and "Big Data", and I despair a little because they often fail badly at getting "little data" correct. It is actually part of the sales pitch for ML: let the AI filter out the crap in your inputs and give you something approximating a decent answer as output. They'd be much better served working on fixing the data sources or using more traditional cleansing methods, but that seems like harder work compared to the new magic some consultant is extolling. ML isn't a magic bullet, but it is currently being sold as one.
- pts_ 7y ago
  What are you hiring for if you don't mind?
- glitchc 7y ago
  Does your job description list machine learning as a requirement? If so, there's your problem. Maybe a chat with HR may be in order.
  - DonHopkins 7y ago
    Maybe the problem is that HR is using machine learning to filter the resumes.
  - VBprogrammer 7y ago
    Definitely not.
Wiretrip 7y ago
Exactly, we are in a very early phase. However, the hype wave is driving a dangerous level of premature deployment of half-baked parlour tricks or the over reliance on simple algorithms where there are real consequences. i.e. prison sentences and insurance eligibility and yes, autonomous vehicles.
- cr0sh 7y ago
  I don't know if this is against HN "rules" - but I'm going to give you an explanation anyhow. I downvoted one of your comments that was essentially a cut-and-paste of this comment here; I have noticed that you have done this more than once here within the comments. Please refrain from doing this; it seems to add nothing but noise to the conversation. If you believe your commentary has merit within the context of the thread at hand, do your best to restate that opinion in an original manner, not by simply copying and repeating the exact same statement. I hope this explanation clarifies why I downvoted you; I believe your comment does have merit to the discussion as a whole, but posting it once should be enough to reach the audience with it's intended message.
  - Wiretrip 7y ago
    OK, under most circumstances that is a fair point, and I personally hate astroturfers, but in this case I feel the comment was equally valid as an answer to two threads that were physically separate - and could have ended up in vastly different places. If there is a way to link to an existing comment then let me know and I'll use that method in future :-)
- solidasparagus 7y ago
  Very good point. At least you can feel the pushback against that in the industry. It's a fraught time, but the AI community feels extremely proactive. It is however an uphill battle when these 80% systems offer such immediate gains. We really need governments to be informed and active.

We might be headed for the trough of disillusionment, but in terms of technology and industry applications, we are still in the early phase of modern AI (big data + ML).

VBprogrammer 7y ago

I'm doing a bit of hiring at the moment. It's hard to find a single CV which doesn't have some kind of machine learning slant. As much as I think there are plenty of advances in ML left to take, I doubt every graduate will step out into a good application for existing machine learning tools.

misterman0 7y ago
Just like not all astrophysicists reach Nobel prize level achievements not all machine-learning graduates will innovate in their field. But to help you out, in order to find people who are likely to innovate, find out if that is their goal. If it is not then you know not to hire them. But if that's their goal, maybe start some kind of "program" where you give these people a chance. 6 months. A year maybe. If the are close to something or if you're pleased with them even though they aren't really innovating, then give them a "tenure" so to speak. An evaluation process, it's very common here in Sweden. I mean how much money can you really loose in six months? You can kick that shithole straight out day one if that's your perogative. It's a good deal for both parties.
- VBprogrammer 7y ago
  Sorry if I wasn't clear, our problems are CRUD at modest scale. There is little room for the application of machine learning.
  - dspillett 7y ago
    > There is little room for the application of machine learning You see people trying to shoehorn ML into many such system though, and there is money in it, which is why people are chasing it to have it on their CVs. Like the noSQL hype of a some years ago it'll settle down and people will gravitate back more towards the right tool for the job (which will sometimes be ML based, but often not, just as "noSQL" is sometimes the right tool or right enough). ML will survive where it is the best tool for the job, or at least where it can be genuinely useful and not significantly sub-optimal. > our problems are CRUD at modest scale. I see some of our client base looking into ML and "Big Data", and I despair a little because they often fail badly at getting "little data" correct. It is actually part of the sales pitch for ML: let the AI filter out the crap in your inputs and give you something approximating a decent answer as output. They'd be much better served working on fixing the data sources or using more traditional cleansing methods, but that seems like harder work compared to the new magic some consultant is extolling. ML isn't a magic bullet, but it is currently being sold as one.
pts_ 7y ago
What are you hiring for if you don't mind?
glitchc 7y ago
Does your job description list machine learning as a requirement? If so, there's your problem. Maybe a chat with HR may be in order.
- DonHopkins 7y ago
  Maybe the problem is that HR is using machine learning to filter the resumes.
- VBprogrammer 7y ago
  Definitely not.

Wiretrip 7y ago

Exactly, we are in a very early phase. However, the hype wave is driving a dangerous level of premature deployment of half-baked parlour tricks or the over reliance on simple algorithms where there are real consequences. i.e. prison sentences and insurance eligibility and yes, autonomous vehicles.

cr0sh 7y ago
I don't know if this is against HN "rules" - but I'm going to give you an explanation anyhow. I downvoted one of your comments that was essentially a cut-and-paste of this comment here; I have noticed that you have done this more than once here within the comments. Please refrain from doing this; it seems to add nothing but noise to the conversation. If you believe your commentary has merit within the context of the thread at hand, do your best to restate that opinion in an original manner, not by simply copying and repeating the exact same statement. I hope this explanation clarifies why I downvoted you; I believe your comment does have merit to the discussion as a whole, but posting it once should be enough to reach the audience with it's intended message.
- Wiretrip 7y ago
  OK, under most circumstances that is a fair point, and I personally hate astroturfers, but in this case I feel the comment was equally valid as an answer to two threads that were physically separate - and could have ended up in vastly different places. If there is a way to link to an existing comment then let me know and I'll use that method in future :-)
solidasparagus 7y ago
Very good point. At least you can feel the pushback against that in the industry. It's a fraught time, but the AI community feels extremely proactive. It is however an uphill battle when these 80% systems offer such immediate gains. We really need governments to be informed and active.