Having worked both in industry and as an academic , Muhlstein is now keen to bridge the gap between the two as he believes this would result in a better outcome when AI technologies and products are created . He explained : “ At the surface level of academia , you tend to have a lot more time to think about problems in terms of the fundamentals , in terms of really focusing on getting a good understanding of what is happening and how things work .”
“ In industry , when you have practical considerations , you need to build something that works and has some sort of impact on the company , on your users , on society . So depending on where you work , you ' re almost incentivised for different kinds of work , but really it ' s important that they happen together because the impact that industry has is pretty massive on our society . Yet , if it ' s not informed by a better understanding of the world , it ' s blind in a lot of ways . As a result of this , we end up just building things that ‘ kind of ’ work and then we have to replace them pretty quickly ,” added Muhlstein .
Having worked at Google for nearly a year now , the Artificial Intelligence Engineer looks at problems and challenges from both an academic and professional outlook , as he explains : “ When I do work in industry , I always try to look at problems in a more fundamental way . I really look to sketch out the task to consider exactly what we are caring about here ? What are our tools , what is the fundamental nature of the thing that we ' re trying to do ? As opposed to a more surface-level relationship , I think this approach creates things that work better .”
Lending to his passion for AI , computer science and physics , Muhlstein is now working on a book looking into computational learning theory . Within it , he plans to explore what is possible to learn , how we define knowledge , and how we truly answer questions he doesn ’ t believe have been answered definitively within his field . aimagazine . com 21