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I have done my PhD in theoretical computer science two years ago. I am currently working in a teaching university in India. I have done PhD on problems related to algebra and also during postdoc. I have started learning applied machine learning and published couple of research papers. I have seen a very new trend in research that now we don't need to have a solid background of topics, just surface level idea with implementation is fine.

It seems to me that the research in the future will be like a tent. If we have move from one research area to another we have to just fold our tent and move to the next and place the tent at that place. I think 10 years ago it was different it like making a house with solid foundation using stones. That foundation used to take time but now we can't afford that level of foundation. This thought came to my mind after listening to views of Yuval Noah Harari.

I have a simple question that do we need strong foundation in research? The goal of mine is to publish good papers and get a grant from government or private organizations in the future.

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    Surface level foundation will contribute only to surface level knowledge. And you risk building on something that will eventually collapse. If your aims are getting a grant, that might work. If your aim is to advance human knowledge, that won't necessarily work.
    – quantacad
    Jul 18, 2023 at 8:18
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    It sounds like you are confusing a rapidly evolving field for a field that only requires surface level understanding. Whenever there is something new(ish) like machine learning, there is inevitably low hanging fruit. That does not mean that A) you don't need a solid foundation and B) that the field will not develop to a point where those sorts of "easy" projects dry up. There is also a difference between changing research interests and hoping from one "hot" topic to another just to secure funding.
    – sErISaNo
    Jul 19, 2023 at 6:52

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Depends. In my discipline, there are many researchers who remain in a field for many years. There are some who go from field to field depending on funding opportunities.

I often see top researchers who have very strong foundation in X, e.g., convex optimization, and then branch off to Y and apply X.

In general, having a strong foundation is important. Otherwise, once an area becomes dated, your skills are dated too.

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