The possibility of building machines that are intelligent in the sense that we perceive ourselves to be intelligent has always been accompanied by a very reasonable concern: how can we make sure our creations will always serve us and not the other way around?
People familiar with New Sapience know we are one of the few companies that claim to be making progress towards Artificial General Intelligence (AGI). OpenAI is another. Many of our followers and investors want to get our take on the current controversy surrounding OpenAI’s ChatGPT and other Large Language Models (LLMs).
The issues are not something that can be fairly dealt with in a couple of Twitter posts. So here is a concise roadmap to the controversy and how it looks from the New Sapience perspective.
A new theory on the nature and structure of knowledge and its relation to reality does for AI what the Periodic Table of the Elements did for Chemistry.
Complex ideas are aggregates of simpler ones. The inescapable conclusion is that, if you keep decomposing ideas into their components, at some point you get to the end, or rather the beginning. This is the same conjecture that Democritus made about the material world: if you keep breaking things apart, eventually you get to the indivisible pieces he called “atoms.”
New Sapience began with a simple thesis: the quickest way to create a thinking machine is to give it something to think about. The symbolic crowd was on the right track when they focused, not on emulating the human brain like the connectionists, but on the end product of human cognition: knowledge. But there was a fatal flaw in their approach: the symbols themselves.