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How to do Research At the MIT AI Lab

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38 pages, Unknown Binding

Published October 1, 1988

4 people want to read

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David Chapman

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Displaying 1 of 1 review
Profile Image for Zhijing Jin.
347 reviews60 followers
January 5, 2021
This is an awesome guide for people who are curious how PhD in AI research is like, and it is also helpful for PhDs who are just embarking their academic journey.

Top takeaways:
1) We should be aware of the phenomenon that some research labs are sadly inbred and insular; people often mostly read and cite work done only at their own school.
2) Join the "Secret Paper Passing Network": Trend-setting work is formed at least a year before others know about it. Join the networking cycle to help give advice to cool work before it is published.
3) For interdisciplinary research: If you want to quickly learn a new field, find out who are the most famous in the field and read their books.
4) Pass your work to potential interested people and collect advice before you publish.
5) Important observation: Since a large degree students' thesis directions are shaped by their advisors, the direction and growth of the field as a whole depends a great deal on what advisors graduate students pick.

Other essential skills for a PhD:
- Identify good resources of papers and books
- Read a lot and develop reading strategies that can optimize your takeaways, e.g., reading with questions like "How can I use this?" "Does this really do what the author claims?" "What if...?"
- Don't be fully dependent on your advisor for advice, wisdom, comments, and connections. Build your own network with several close grad student friends.

More resources:
- The open-sourced PDF is at http://dspace.mit.edu/bitstream/handl...
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