"The seed of my passion for AI was planted in the early 2000s when I studied electrical and computer engineering at college. I was exposed to a type of machine learning called pattern recognition. In 2009, I completed a Ph.D. in computer vision at Carnegie Mellon - well before the current excitement around LLMs and generative AI. But we had the same goal: make machines more intelligent."
"Next, I moved into research and teaching roles, and in 2016, I spent a year as a research scientist at Facebook AI Research, or FAIR. Following that, I'd spend my springs and summers at FAIR in Menlo Park, California, and my falls teaching computer vision at Georgia Tech. Over time, I enjoyed Meta more than my professorship, and I transitioned to a full-time role in 2021, eventually becoming a senior director of GenAI."
"Professor and research scientist roles in AImight list a Ph.D. as a requirement, but there are other cutting-edge jobs in this space. There are good reasons to do a Ph.D, like if you want to work in academia or explore certain ideas. But if your end goal is doing interesting AI work and learning how the sausage is made, you could spend those five to six years at startups or big labs instead."
Devi Parikh earned a Ph.D. in computer vision from Carnegie Mellon in 2009 and began a career combining research and teaching. She worked as a research scientist at Facebook AI Research (FAIR) in 2016 while also teaching at Georgia Tech, later joining Meta full time and rising to senior director of generative AI before leaving in 2024 to cofound Yutori. Practical industry roles, startups, open-source projects, and side work can provide cutting-edge AI experience as alternatives to a Ph.D. Persisting through projects and seeing ideas to completion has been instrumental to career success in AI.
Read at Business Insider
Unable to calculate read time
Collection
[
|
...
]