Machine Learning Street Talk (MLST)

#66 ALEXANDER MATTICK - [Unplugged / Community Edition]

Feb 28, 2022

Join Alexander Mattick, a prominent voice in Yannic's Discord community and an AI aficionado, as he dives deep into the intricacies of neural networks. He reveals fascinating insights on spline theory and the complexities of abstraction in machine learning. The discussion also touches on the balance between exploration and control in knowledge acquisition, alongside the philosophical implications of causality and discrete versus continuous modeling. Alex champions the value of a broad knowledge base, illustrating how diverse insights can enhance problem-solving.

50:31

Creator website

Episode guests

Alexander Mattick

AI Chapters

Episode notes

Intro

2min

Neural Networks: Extrapolation and Abstraction

17min

Navigating the Maze of Machine Learning

6min

Navigating the Duality of Knowledge and Control

5min

Navigating Knowledge: The Interconnectedness of Research

7min

Navigating Causality in Machine Learning

13min

We have a chat with Alexander Mattick aka ZickZack from Yannic's Discord community. Alex is one of the leading voices in that community and has an impressive technical depth. Don't forget MLST has now started it's own Discord server too, come and join us! We are going to run regular events, our first big event on Wednesday 9th 1700-1900 UK time.

Patreon: https://www.patreon.com/mlst

Discord: https://discord.gg/HNnAwSduud

YT version: https://youtu.be/rGOOLC8cIO4

[00:00:00] Introduction to Alex

[00:02:16] Spline theory of NNs

[00:05:19] Do NNs abstract?

[00:08:27] Tim's exposition of spline theory of NNs

[00:11:11] Semantics in NNs

[00:13:37] Continuous vs discrete

[00:19:00] Open-ended Search

[00:22:54] Inductive logic programming

[00:25:00] Control to gain knowledge and knowledge to gain control

[00:30:22] Being a generalist with a breadth of knowledge and knowledge transfer

[00:36:29] Causality

[00:43:14] Discrete program synthesis + theorem solvers

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