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This is a rather narrow perspective focused on (and giving examples from) one subfield (deep learning) at one point of time (year 2018). Have factors like (i) commoditization of software + hardware, (ii) the limited mathematics required, (iii) many open problems, and (iv) a lot of industry funding made a PhD unnecessary for doing research in deep learning in year 2018?: Yes. But does this mean that a PhD (with several advanced courses and a few years of struggle solving hard research problems) won't be useful for doing Computer Science research for the next 30 years? The answer is probably "No". If you want a long-term, intellectually satisfying research career, whether in academia or industry, a PhD is extremely useful.

Also, this field is quite easy to get into without any external support. You can become an expert in deep learning with a laptop and an internet connection. Most research fields will require a well equipped lab. You can usually find good labs in industry, but you won't have the same freedom to play with all those toys as you will have when pursuing a PhD.

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