“In human logic, everything is gray.”

By: Dr. Chris Tseng

The problem with traditional computing is that the logic flow has always been “if-then-else” and black and white. But that’s not the way human logic works.

There’s not always, will it go this way or that way? A lot of times even this answer may change depending on the environment, depending on the situation.

This is really what the traditional computer science algorithm cannot solve.

In the case of academic teaching, students begin to realize that a lot of this application and also development need not be restricted to the traditional rule base. “If you see this, then something happens.”

Once you come with cognitive computing, it’s adaptive.

It takes into consideration quality factor. It takes into consideration the problem. It takes into consideration how humans interact with the problem, and always will integrate it.

As a result, you are able to provide a solution that is as close as a real human expert — or millions at once — can provide.

We are now using cognitive computing to look at whether we can help Guiding Eyes for the Blind with their dog raising programs. They have a lot of structured and unstructured data, that can be mapped onto their performance data. I am excited to see the potential of where this can lead.

Hi, my name is Chris Tseng.

I’m a professor of computer science and also the director of data intelligence at San Jose State University. My interest area is in cognitive computing, big data analytics, and also machine learning. I teach mostly software engineering, software projects, and also machine intelligence classes. have been teaching ever since the late 1990s, so I have been in this field for almost 20+ years.