It’s excusable if you didn’t notice it when a scientist named Daniel J. Buehrer, a retired professor from the National Chung Cheng University in Taiwan, published a white paper earlier this month proposing a new class of math that could lead to the birth of machine consciousness. Keeping up with all the breakthroughs in the field of AI can be exhausting, we know.
Robot consciousness is a touchy subject in artificial intelligence circles. In order to have a discussion around the idea of a computer that can ‘feel’ and ‘think,’ and has it’s own motivations, you first have to find two people who actually agree on the semantics of sentience. And if you manage that, you’ll then have to wade through a myriad of hypothetical objections to any theoretical living AI you can come up with.
We’re just not ready to accept the idea of a mechanical species of ‘beings’ that exist completely independently of humans, and for good reason: it’s the stuff of science fiction – just like spaceships and lasers once were.
Which brings us back to Buehrer’s white paper proposing a new class of calculus. If his theories are correct, his math could lead to the creation of an all-encompassing, all-learning algorithm.
The paper, titled “A Mathematical Framework for Superintelligent Machines,” proposes a new type of math, a class calculus that is “expressive enough to describe and improve its own learning process.”
Buehrer suggests a mathematical method for organizing the various tribes of AI-learning under a single ruling construct, such as the one suggested by Pedro Domingos in his book “The Master Algorithm.”