In industry AI work, the primary focus is on performance and practical outcomes, where understanding serves as a tool to achieve the desired result; in contrast, research AI work prioritizes generating new understanding, knowledge, and perspectives for the community, requiring a fundamentally different mindset that values theoretical contribution over immediate practical application.
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Research vs Industry AI workAñadido:
What would you say is like the biggest difference in like mentality that you have when you do that type of like more practical minded work that you know is going to go into like I don't know like a car or something like that and like some the more research long term type of stuff.
>> when you work on an actual product actual application what you really care about is performance. Understanding is just a tool to get the right performance and sometimes as much as understanding is fun and research is fun just going through data set and cleaning it give you way more performance boost.
>> Yeah.
You need to kind of stop yourself from focusing too much on what is you know like cool or fun or new and do the like you know work first and only then like put effort. While I feel in this is one of the reasons I went from industry to PhD that as a researcher they don't care about a specific application the thing that we bring into the world is new understanding is new knowledge and this require completely different like perspective. It's all about what kind of new understanding new knowledge new perspective you give to the community.
And I think that this is much more fun than just you know playing the numbers game.
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