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Back a decade or so ago, the only way to really reliably get access to current research was to work at a University or a large company with journal subscription

Back a decade or so ago, the only way to really reliably get access to current research was to work at a University or a large company with journal subscriptions. These days it's really easy to get all the information you need to teach yourself whatever you need to. If you have problems, ask the Internet for help. And these days, if you want to work on the actual leading edge, it's likely at Google, not at a University.

YeGoblynQueenne 9y ago
>> These days it's really easy to get all the information you need to teach yourself whatever you need to. If you have problems, ask the Internet for help. The information may be online but it's not organised in any way and if you're learning on your own, first you have to figure out what information is relevant to what you want to learn. University offers focus, support and guidance that you don't have when you're on your own. I think a lot of developers treat machine learning as just another technology they can get good at if they apply themselves to it, like blockchain, non-relational databases, VR etc. In truth, AI is nothing like that. You really need to grok some background knowledge before you can do anything useful with it. You can sure learn to use the free-access tools available today, like TensorFlow or Keras etc, but, for instance, you're not going to just figure out how to roll your own deep learning framework just by reading a few books you found online- like you could do for, say, a web framework. Nor does it mean that, just because you learned how to use a machine learnign framework, you can discover new knowledge and invent new machine learning algorithms, or optimise existing ones. Which means- someone else always has to be there to do the hard work for you. I'd say, that's the reason why it's AI PhD students who are being poached, and not just random devs who declare themselves "passionate about machine learning" on their facebook pages. Because the AI PhDs already have the background the big AI companies are looking for.

YeGoblynQueenne 9y ago

>> These days it's really easy to get all the information you need to teach yourself whatever you need to. If you have problems, ask the Internet for help. The information may be online but it's not organised in any way and if you're learning on your own, first you have to figure out what information is relevant to what you want to learn. University offers focus, support and guidance that you don't have when you're on your own. I think a lot of developers treat machine learning as just another technology they can get good at if they apply themselves to it, like blockchain, non-relational databases, VR etc. In truth, AI is nothing like that. You really need to grok some background knowledge before you can do anything useful with it. You can sure learn to use the free-access tools available today, like TensorFlow or Keras etc, but, for instance, you're not going to just figure out how to roll your own deep learning framework just by reading a few books you found online- like you could do for, say, a web framework. Nor does it mean that, just because you learned how to use a machine learnign framework, you can discover new knowledge and invent new machine learning algorithms, or optimise existing ones. Which means- someone else always has to be there to do the hard work for you. I'd say, that's the reason why it's AI PhD students who are being poached, and not just random devs who declare themselves "passionate about machine learning" on their facebook pages. Because the AI PhDs already have the background the big AI companies are looking for.