The Next Generation of AI Requires a Novel Approach Inspired by How the Brain Actually Works

Today’s machine learning systems are built on an old theory of how the human brain works – a mathematical theory that believes our brains process and understand information using calculations. We now know that the human brain uses patterns to process data and learn. So if our brains are pattern-based, why is current AI technology – which claims to mirror the brain – still based on old mathematical theories?

We believe the promise of artificial intelligence cannot be achieved with outdated theories and legacy machine learning models. The next generation of AI requires a truly novel approach that is inspired by the way the brain actually works.

Natural Intelligence Systems is dedicated to building the software and hardware that will emulate the pattern-based learning of the human brain and provide the new level of context and explainability to our AI systems.

The Natural Intelligence Team

Paul Dlugosch
Indranil Roy
Sr. VP of R&D
Matt Tanner
VP Customer Engineering
Terry Leslie
VP External R&D
Aimee Lougee
Senior Researcher
Raino Zoller
VP Marketing
Ray Hirschi
Program Director
Dan Skinner
VP Business Dev
Russ Lloyd
VLSI Design
Bill Tiffany
VSLI Design
Eric Neeley
SW Architecture
John Mosby
Systems Engineering
Harold Noyes
Senior Architect
Dave Roberts
VLSI Design Manager