Interview with Tom Mitchell

interviewer: Davor Orlič, Knowledge 4 All Foundation Ltd.
interviewee: Tom Mitchell, Carnegie Mellon University
published: Feb. 25, 2007,   recorded: September 2006,   views: 73865

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Tom Mitchell is the first Chair of Department of the first Machine Learning Department in the World, based at Carnegie Mellon. The Videolectures.Net team spoke to him in Pittsburgh at CMU where we discussed about how he started the department, what was the response of the broader community and its past, present and future. "The university said you can only have a department if you have a discipline that is going to be here in one hundred years otherwise you can not have a department."

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Reviews and comments:

Comment1 tom mitchell, August 20, 2007 at 4:46 a.m.:

you have the same name as me... lmao!

Comment2 Judy B. Okawa, Ph.D., January 5, 2009 at 1:41 a.m.:

Dr. Mitchell, I wonder if you are the person who appeared on 60 Minutes this evening (Sunday, Jan. 4) talking about work on thought identification. I'm very interested in this subject, as I'm a psychologist and am frequently in the position of trying to determine if someone is being truthful with me.
Thank you,
Judy Okawa

Comment3 Yingyuan Yang, November 22, 2009 at 11:59 a.m.:

That’s wonderful!
I am an undergraduate student in China; I love this area very much. Indeed, my major is computer software. Machine Learning is a complex theory, like psychology. It not only includes AI algorithm, but also contain theory of brain, neurology, recognizing technique, even psychology. However, the direction in machine learning has been misleading, at least in China. Too many researchers emphasize on comprehension of human language or literature which may extreme hard to make an accurate data. Maybe we should put our attention down to those simple communications, like learning process on birds or cold blood animal. A highly developed science always comes from simple. To directly study human’s complex communicational skill is too fast for us. No one can build two-storey house without the first floor.

Comment4 nesredin, December 25, 2009 at 2:11 p.m.:

I am a beginner for ML. I didnt know it existed before I found out that my problem could only be solved using statistical and learning mechanism.

I found what is called Machine Learning in the internet. Thanks God! I was relieved. But I had this question all the time. The area looks very challenging and narrow. Am I alone? Or are thre some people around the world who can direct me somewhere?...I think this interview helps a lot. Thank you Michell.

Comment5 steve, August 3, 2010 at 11:40 a.m.:

Thanks a lot for sharing. Been playing around with machine learning both professionally and as a hobby.

One of my projects ( ) is using simple genetic algorithms to teach itself what each product type is.

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Comment6 Hazem Migdady, September 3, 2011 at 10:34 a.m.:

I read your book about machine learning and it provided me with a robust knowledge in the field of ML.. Best wishes for you Dr.

Comment7 David, March 7, 2012 at 1:27 a.m.:

Thank you for your wonderful book. Is there the chance that somewhen an updated version with a chapter about SVMs and unsupervised learning algorithms??

Comment8 Behnaz, August 19, 2013 at 1:35 p.m.:

I've been always looking for a field or major that collides popular subjects(biology, psychology, business and so on) to create something totally amazing. There it is, Machine Learning. Enjoyed the interview.

Comment9 Tinozivashe Sibanda, March 15, 2017 at 10:28 p.m.:

Thank you Mr. Mitchel for this video.

I was doing some research into your background because my lecturer advised your book for his course at the University of the Witwatersrand.

Your explanations are clear on the objectives of Machine Learning as a field of study.

Kind Regards

Comment10 David, June 10, 2021 at 9:45 a.m.:

I rewatched the video, very interesting thank you !

Comment11 Robert, August 6, 2021 at 7:15 a.m.:

I love this area very much. Indeed, my major is computer software. Machine Learning is a complex theory, like psychology.

Robert |

Comment12 Madison Wilson, August 9, 2021 at 12:02 p.m.:

Too many researchers emphasize on comprehension of human language or literature which may extreme hard to make an accurate data. Maybe we should put our attention down to those simple communications, like learning process on birds or cold blood animal.

Madison |

Comment13 Davidson, August 10, 2021 at 7:17 a.m.:

Hello, Mr. Michell. It was a great interview! There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity and experimentation. Thanks for enlightening us!

Keep safe.
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Comment14 Robert, August 19, 2021 at 5:34 a.m.:

Maybe we should put our attention down to those simple communications, like learning process on birds or cold blood animal. A highly developed science always comes from simple. To directly study human’s complex communicational skill is too fast for us.


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