Overview

CogDevLoopsv4

Cognitive scientist and a business intelligence professional. For the past 8 years I’ve been conducting research into the biological evolution of intelligence and the logical foundations of cognition. During my tenure at Northeastern, working towards a B.S in physics, I had the opportunity to work with semi-conductor robots, algorithms for brain monitoring EEG devices, and culturing neurons on a titanium nano-tubes. These experiences greatly influenced my undertaking of AI research. After a period of work in medical physics, I enrolled into a MBA program at the Zicklin School of Business. While at Baruch College I aimed to substantiate my inquiry for creating AI with research into consumer behavior, economic theories, and advertising tactics.

The research section of this site leads to my unpublished articles about the mathematical processes undergoing in our brain. It further investigates how our brains’ evolved the computational capacity to experience and behave rationally. The general theory of mind my research points to is that the origins of intelligent behavior stem from our evolved ability for vivid experiences.

This general theory of mind outlined in my research is essentially based on three principles. The first is the unreasonable effectiveness of mathematics, archaeological evidence for the Great Leap/modern human behavior, and the effects of experience/quale on biological systems. The emerging construct is a fundamental mathematical mechanism present in our brain as well as all other living matter.

My aim is to formalize the minimal requirements for a symbol grounding system and theorize how they progressed into intentional and rational agents. Ultimately, my goal is to deliver results on open access publications to support the development of AGI learning algorithms. My hypothesis for symbol grounding has rational agents arising from cooperation and altruism. Not only is benevolence inherent in these evolutionary interactions, it’s also the overarching necessity and priority for all goal directed behavior of an AGI system.

My research has identified a few facets of our rationality and intelligence that warrant further investigation.  Included in this research are symbol grounding, the reciprocal nature of intentionality and morality, numerical cognition (enumeration vs. subitizing), and the order of learning information for goal-directed behavior. Additionally, the investigation will span the space of potential mind designs by exploring animal, primate, and hominid cognition.

With these pivotal mechanisms the next steps are to mathematically construct these biological computations and access the feasibility of re-creating the mechanisms on an artificially created substrate.

LifeEngineV3


Future Outlook

Identifying brain computations and mechanisms opens the door to creating a learning algorithm that compares to human learning/plasticity. These mechanisms can be found by extrapolating the intelligence of our hominid ancestors, the primate mind, human children, and other types of life. A comparative analysis leads to a number of common mathematical relationships present in every instance of living matter.

Additional elements included in my research is our innate motivational theory, general tool building and its relation to Gödel incompleteness theorem. Lastly, the importance of the long-standing historical and philosophical dialectic regarding the tenuous mind-body problem must not be disregarded.

Threats

Hominid evolution indicates that there may be social and evolutionary based barriers that prevent an independent intelligent machine from having human-like behavior. Overcoming them is one of the next steps in my research. These social and evolutionary aspects of our intelligence are also the reason why AGI posses an existential threat.


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