Skip to content
Structure in AI episode artwork

EPISODE · Apr 21, 2019 · 19 MIN

Structure in AI

from Linear Digressions · host Katie Malone

As artificial intelligence algorithms get applied to more and more domains, a question that often arises is whether to somehow build structure into the algorithm itself to mimic the structure of the problem. There’s usually some amount of knowledge we already have of each domain, an understanding of how it usually works, but it’s not clear how (or even if) to lend this knowledge to an AI algorithm to help it get started. Sure, it may get the algorithm caught up to where we already were on solving that problem, but will it eventually become a limitation where the structure and assumptions prevent the algorithm from surpassing human performance? It’s a problem without a universal answer. This week, we’ll talk about the question in general, and especially recommend a recent discussion between Christopher Manning and Yann LeCun, two AI researchers who hold different opinions on whether structure is a necessary good or a necessary evil. Relevant link: http://www.abigailsee.com/2018/02/21/deep-learning-structure-and-innate-priors.html

Episode metadata supplied by the publisher feed · Published Apr 21, 2019

Embed this episode

Ready to play

Structure in AI

0:00 19:05

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Linear Digressions?

This episode is 19 minutes long.

When was this Linear Digressions episode published?

This episode was published on April 21, 2019.

Can I download this Linear Digressions episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!