I would say PHD is sufficient to advance the field. That's no small thing, but only really overlaps at the start when just about anything advances the field and you need a broad focus.
Machine leaning for sorting peas at high speed is a very well trodden area at this point with a lot of industry specific domain knowledge. I expect self driving cars for example to reach a similar state in ~10-25 years.
The risk with a PHD is you miss the specific wave. But, if you want to stay on the bleeding edge it's probably well worth it.
> I would say PHD is sufficient to advance the field.
Yep! We’ve now made our way back to my initial point in response to OP. :)
Re:Machine Learning Crash Course
by recursivelambda on Friday March 02, 2018 @03:59AM
(#16500072)
You can spend many months working through papers and books without a company paying you for that. That's something that I continually do and have always done, in my own time (and many different fields). Sufficient and not necessary indeed.
Re:Machine Learning Crash Course
by infinite8s on Friday March 02, 2018 @12:30PM
(#16503677)
It's definitely easier to do when it's your primary job.
The PhD is sufficient but not necessary here, right? A PhD researcher's job description is basically "learn necessary math, become a domain expert, and publish papers advancing that domain." It's difficult (but possible) to gain the same experience in industry if you don't have a graduate degree. Which company would pay you to work through Bishop or Goodfellow for a few months? Even a principal DS doesn't get that deal, much less a junior/associate.
Also remember: my comment addressed non-vanilla cases. In your example, this is the difference between a researcher advancing 3D programming and someone using Unity or Unreal.
(Also, sorry for all the edits. Done now!)