The Embeddings World and Artificial General Intelligence

TL;DR

This paper explores the role of pre-trained embeddings in constructing an intelligent world necessary for achieving Artificial General Intelligence (AGI), emphasizing a continuous, world-based approach over traditional algorithmic methods.

Contribution

It proposes that AGI is a process rooted in building an intelligent world with pre-trained embeddings, shifting focus from algorithms to world construction and continuous development.

Findings

Pre-trained embeddings are crucial for embodying common sense and unconscious knowledge.

Building an intelligent world with embeddings facilitates characteristics of human-level intelligence.

AGI is a continuous process, not a fixed product or algorithm.

Abstract

From early days, a key and controversial question inside the artificial intelligence community was whether Artificial General Intelligence (AGI) is achievable. AGI is the ability of machines and computer programs to achieve human-level intelligence and do all tasks that a human being can. While there exist a number of systems in the literature claiming they realize AGI, several other researchers argue that it is impossible to achieve it. In this paper, we take a different view to the problem. First, we discuss that in order to realize AGI, along with building intelligent machines and programs, an intelligent world should also be constructed which is on the one hand, an accurate approximation of our world and on the other hand, a significant part of reasoning of intelligent machines is already embedded in this world. Then we discuss that AGI is not a product or algorithm, rather it is a continuous process which will become more and more mature over time (like human civilization and wisdom). Then, we argue that pre-trained embeddings play a key role in building this intelligent world and as a result, realizing AGI. We discuss how pre-trained embeddings facilitate achieving several characteristics of human-level intelligence, such as embodiment, common sense knowledge, unconscious knowledge and continuality of learning, by machines.