Dexa/Machine Learning Street Talk (MLST)

Neural Networks, Symbolic Reasoning

Walid delves into the essence of deep learning, highlighting the necessity of symbolic representation for computational efficiency. He emphasizes the trade-off between compute and storage, shedding light on the misconception of neural networks as computational entities when, in reality, they function more as hash tables.

In this clip
From this podcast
Machine Learning Street Talk (MLST)
#68 DR. WALID SABA 2.0 - Natural Language Understanding [UNPLUGGED]
Related Questions
- How do deep learning models remember?
- How does the architecture of neural networks relate to their ability to reason in the episode Ilya Sutskever: Deep Learning | Lex Fridman Podcast #94 and the clip Neural Networks and Reasoning?