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We have embarked on a journey to find an algorithm able to develop cognitive capabilities, thus fulfilling the following requirements:
Universal: it should be able to process any kind of information, thus input-agnostic.
Primitive-based: it should be based on a fundamental primitive, with all the primitive instances working concurrently to produce emergent behaviors.
Scalable: it should be able to scale to produce different levels of cognition, from basic instantaneously reactive cognition to higher-order symbolic one.
Continuous: it should be able to work in pure continuous learning mode, without differentiated learning and testing phases.
Bio-plausible: it should be feasible that nature produced it, as natural intelligence is the only reference of true intelligence we are aware of.
Our bet to find this algorithm is our technology, Synthetic Cognition, a pattern-matching, representation-centric primitive that scales into the development of a full cognitive architecture.
We have designed a novel cognition framework of natural cognition, based on a novel Self-Projecting Persistence Principle and Function-Representation model of computation.
We have developed a game-changing technology that solves Artificial General Intelligence based on our cognition framework, and an API to easily use it.
We have identified multiple different tasks our technology can solve, and tested it over multiple real-world cases with astounding results.
We have particularly applied our technology in the biohealth field.
Our Purpose
We believe that general intelligence will bring a revolutionary new breed of Artificial Intelligence systems. These machines will be digital cognitive systems able to solve problems in the same way biological intelligence does: learning and acquiring any knowledge to gain understanding, and being able to reason building smart inferences about their world in order to make intelligent decisions.
Current AI algorithms are unable to genuinely understand and reason. As AIs are not truly intelligent many problems are still unsolvable. And problems currently solved by AI require brute-force, huge amounts of training data and computing power. Current AI solutions are narrow and not reusable for other problems.
Solving General Intelligence will open a new era of Cognitive Computing where truly intelligent AIs won’t need to be programmed, but educated to gain genuine understanding and reasoning.
We want to lead this new era of AI, ensuring that our algorithm is available to everyone. Consequently we are not only focused on the validation and demonstration of our General Intelligence algorithm, but also on developing the most usable platforms so anyone can seamlessly use our algorithm to build their own intelligent AI, digitizing their expert knowledge to cognitively solve any problem.
For the moment we are focused on applying Synthetic Cognition to health data analytics, where any new knowledge and explainable prediction extracted from the data saves lives.
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