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All the latest updates and information about New Sapience and our breakthrough technologies.
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.”
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.
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.
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.
“Expecting to create an AGI without first understanding how it works is like expecting skyscrapers to fly if we build them tall enough.”
“What is needed is nothing less than a breakthrough in philosophy, a new epistemological theory…”
David Deutsch, quantum computation physicist at the University of Oxford
Futurist Ray Kurzweil popularized the idea of the AI Singularity; when AIs first equal then far surpass humans in intelligence. But the advent of sapiens illustrates that AI is driven by knowledge not computing power. A revolution in how humans acquire, share, and use knowledge will indeed produce a singularity. But not for the first time.
Since its beginnings in the 1980s, the AI community has been rife with hyperbole and vague claims of programs that “think like humans,” but always without measurable results. Today New Sapience is using tools written for human students to assess sapiens comprehension.