Database Reference
In-Depth Information
Another great thing about this approach is that you can have two different sets
of people working on the same problem space. With the current techniques,
if you want to move jointly along this space then you need people who know
everything. And that's really hard when hiring. It's hard to find the person who
knows optimized C++ numerical methods and really understands all these
kernel tricks or similar techniques; whereas with the generative approach I
can find people who are really good at modeling but only work with small
data, and I can find people who are as not as up on the modeling but know
how to do really efficient inference. Then I can put them together and get a
lot out.
Gutierrez: What is nontechnical advice you give your friends?
Jonas: The biggest thing I think people should be working on is problems they
find interesting, exciting, and meaningful. Today I saw a quote on Facebook
that said that a data scientist is a scientist who wants to feed his family. This is
not entirely incorrect. There are a lot of interesting problems out there that
I think a lot of people can get excited about—and life is too short to not be
having fun. So I hope that most people are operating in that space. For my
friends who are just graduating college, I tell them, “No, don't go do finance if
you're not really excited about it. There are so many other interesting things.”
In thirty years, you're not really going to care about that extra money. It won't
be a thing if you work on problems you find interesting and meaningful.
 
Search WWH ::




Custom Search