I am convinced we’re at an important inflection point in the timeline of the discipline of computer science. When compared to other disciplines like mathematics, physics and biology, computer science is a very young field, starting around 1964. But something is happening now, in 2014, that is propelling the field into a new evolutionary period. What’s happening is data science and it’s facilitator machine learning.
One of the first computer scientists, John E. Hopcroft of Cornell University, gave a compelling talk late last year “Future Directions in Computer Science Research” where he reviews what he believes are important topics for the future of computer science. I think those topics are quite telling:
- Tracking the flow of ideas in scientific literature
- Tracking evolution of communities in social networks
- Extracting information from unstructured data sources
- Processing massive data sets and streams
- Extracting signals from noise
- Dealing with high dimensional data and dimension reduction
Most of these topics involve data science and machine learning. Indeed, Hopcroft’s “future” seems to be happening now.
I remember Professor Hopcroft well, and thus I respect his opinions implicitly. The Hopcroft and Ulman book “Introduction to Automata Theory, Languages and Computation” was the textbook for my upper division Formal Languages class at UCLA. Hopcroft’s talk can be viewed HERE and his slides can be downloaded HERE.
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