The situation of scientists
The scientist's situation is beyond the reach of few people. The first is those scientists who are engaged in artificial intelligence research. They can create many algorithms and theories to solve some cutting-edge problems. For example, Hinton, the founder of deep learning, generated a confrontation network inventor.
Ian goodfellow, Xgboost inventor Chen Tianqi and so on.
The engineer's situation
The position of engineer is also difficult. It is required to have a strong theoretical background and engineering completion ability, be able to reproduce the latest paper independently, deeply understand the completion principle of the paper, and make some small innovations on it.
User situation
The user's situation is that of most artificial intelligence algorithm engineer. The first thing is to understand the principle of the algorithm and know how to complete it. The core is to know how to apply it to an actual trading scenario.
Understand its natural situation
The last one is to know what is why, what artificial intelligence is now, what machine learning and deep learning are probably, don't over-myth AI, know the advantages of current AI, and know the limitations of current AI.
Different situations correspond to different requirements. Simply put, engineering can determine your lower limit, and theory and business understanding can determine your ceiling. The above is what Bian Xiao compiled for you today about "How about software engineers switching to artificial intelligence?" I hope it will help everyone.