29 ms·
I feel the pain of people that want to stay in science and do not want to move to software engineering. At the same time, at the end of the graduate school many
by ternaus 6y ago
I feel the pain of people that want to stay in science and do not want to move to software engineering. At the same time, at the end of the graduate school many people loose their passion for science. I would recommend these people to learn how to write code and move to industry. The demand for programmers is pretty high.
P.S. I got PhD in theoretical Physics at UC Davis, but moved to Bay Area for a Machine Learning job.
I love Physics, and can get back to it after retirement, but right now now I am paid well, and more flexible. I like that I can choose company and geography. Postdocs and faculty members do not have this luxury.
- petermcneeley 6y agoWhere would you put the recent work of Steven Wolfram? Crank? PS. Undergrad Physics so that means I only have a vague understanding of anything post 1940s.
- hart_russell 6y agoDid the math-y parts of Physics translate well to AI?
- ternaus 6y agoGood question. Let me quote myself from https://www.toolbox.com/tech/big-data/articles/lyft-on-why-ridesharing-is-the-future-of-mobility/ https://www.toolbox.com/tech/big-data/articles/lyft-on-why-r... > I believe Physics and Machine Learning are really well aligned. > First, the level of Math that you learn in Physics is a few decades away from what you use in modern Machine Learning. This makes the theory behind machine learning easy to understand. > Second, and the most important is the mindset. In Physics, people are maneuvering between rigorous theory and actual data, trying to connect them sensibly. Machine Learning is very similar. > I may be biased about the alignment of Physics and machine learning. Still, I know at least 20 Kaggle Grandmasters that have Physics majors.