Sapiens and Chatbots
Seldom in the history of AI has a new product release been met with such widespread enthusiasm and consternation as OpenAI’s ChatGPT. New Sapience has been working on a compact scalable way to endow machines with knowledge of the underlying reality that language refers to and is built upon. Naturally we are being asked about how ChatGPT relates to our work. Is it a giant step toward Strong AI (or AGI) or is it just a better (and perhaps scarier) illusion of intelligence?
The Internet of Minds
6th and final webinar of the Artificial Intelligence and Human Psychology Series
A New Science of Artificial Intelligence
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.
Why I invested in New Sapience
Excerpt from a webinar hosted by author Lynn Woodland in which Dr. Bandy explains why he invested in New Sapience
A look into the future of AI
Webinar Moderated by author Lynn Woodland with Physicist Dr. Willam Bandy and New Sapience CEO Bryant Cruse
Tyranny of the Statistical Algorithms
Data science has many useful applications in the area of pattern recognition but never forget that ML algorithms themselves only compile statistics, they are mindless, there is nothing like intelligence in there. Yet these algorithms are being used every day to decide who gets a loan, who gets a job, and who gets admitted to schools. There are even cases of people being falsely arrested. When ML is used to make decisions that affect people’s lives, they can only treat people as statistics. re you okay with that?
Aspirational AI
It happens like this: someone has a theory about what intelligence is and develops some software to implement it. Even if it does not work or doesn’t do anything that looks like intelligence, it is still considered “AI” because that is what they were aspiring to create.
The Hidden Structure
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.”
Artificial Neural Networks
Today, the technical community, including Big Tech, government and academia have embraced artificial neural networks (ANNs) and Machine Learning (ML) as their preferred methodology. While this “data science” has led to many amazing applications that are impacting the way we live and work, misconceptions about what it is and its potential are widespread.
How we got here.
Some inventions, like our sapiens, come “out of left field,” the result of a series of unforeseeable influences and events, pieces of a puzzle that come together at a certain point in time independent of and often contrary to the technology mainstream.
Knowledge and Language
The relationship between language and knowledge has fascinated philosophers since ancient times. One theory is that language is a prerequisite for knowledge and that knowledge cannot exist without it. We talk as though language contains knowledge. But a simple thought experiment proves otherwise.
The New Sapience Thesis
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.
