Author: Bryant Cruse

Bryant Cruse has been a pioneer in the application of AI technology to difficult real-world problems. He graduated from St. John’s College in Annapolis, Maryland, known for its unique liberal arts program and where he a acquired his life-time interest in “how we know what we know.” After graduation he served for eight years as a Naval Aviator then returned to school for an MS in Space Systems Engineering from Johns Hopkins. While on the Mission Operations team for the Hubble Telescope he found a personal mission to change the way spacecraft were operated by seeking a way to capture human knowledge in computers. This work led him to a 6-month residency in AI (MS equivalent) at the Lockheed AI Center in Palo Alto. He went on to found two successful AI companies, both of which were ultimately acquired by public corporations. New Sapience is his third AI company.

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?

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.