Meaning Versus Information, Prediction Versus Memory, and Question Versus Answer

TL;DR

This paper discusses core concepts like information and memory in brain science and AI, proposing new perspectives to address current limitations and advance understanding of the mind and intelligent systems.

Contribution

It offers a novel conceptual framework for understanding brain and AI functions, emphasizing the distinction between meaning and information, and prediction and memory.

Findings

Highlights the importance of conceptual clarity in brain and AI research

Proposes new perspectives to overcome current limitations in understanding

Encourages rethinking fundamental concepts for future progress

Abstract

Brain science and artificial intelligence have made great progress toward the understanding and engineering of the human mind. The progress has accelerated significantly since the turn of the century thanks to new methods for probing the brain (both structure and function), and rapid development in deep learning research. However, despite these new developments, there are still many open questions, such as how to understand the brain at the system level, and various robustness issues and limitations of deep learning. In this informal essay, I will talk about some of the concepts that are central to brain science and artificial intelligence, such as information and memory, and discuss how a different view on these concepts can help us move forward, beyond current limits of our understanding in these fields.