CCF: Small: Paradox and Brain-inspired Computer Architecture

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

In order to achieve true machine intelligence, the structural organization of the brain must be understood in the context of its potential impacts on future computer architecture. Current research in artificial intelligence and machine learning are focused on creating complex programs that requires large datasets for training and do not provide insight as to how the structure of the brain achieves intelligence, utilizes massive amounts of parallelism, trades off accuracy for real-time response, and creates new solutions from relatively few experiences. The brain utilizes large amounts of structural parallelism that current computer architecture cannot accommodate. It must also operate in real-time and provide the best possible answers based upon relatively few prior experiences. In order to utilize the vast structural parallelism in the brain, the best possible answer must be drawn from a set of independent possible answers, held simultaneously. But different answers result in conflict which may be the foundation of intelligence but which is inconsistent with conventional computer architecture. The brain is organized into a conscious and subconscious mind, with the subconscious mind utilizing the greatest amount of parallelism. Insight to how the brain achieves intelligence may lie in an examination of conflict in the subconscious – the production, accommodation and resolution of multiple, competing answers. Paradox is a logical result which produces a simultaneous true and false result – something computer circuitry cannot accommodate. While computer programs force such conflict resolution, the brain likely holds multiple results without resolving them, instead holding and developing multiple, conflicting models which continue to develop, over time, and are selected on an as needed basis. Instead of resolving the conflict, the brain picks and chooses, depending upon circumstances. Fundamentally, paradox produces multiple, conflicting answers to the same question. While computer programs operate on vast amounts of logic, they cannot accommodate paradox. Instead of holding the conflict, they force an answer. By focusing on paradox, the structural properties of the brain in the context computer architecture can be examined. Thus, the significance of the structural organization of the brain will be better understood, future computer architecture can utilize parallelism towards the order of the brain, and true machine intelligence can be studied in a new light. By focusing on a striking property of the brain, that of how the brain accommodates paradox, the brain likely functions as an MISD (Multiple Instruction Single Datastream) computer. Machine Learning results in algorithmic solutions, but does not provide insight into how the structure of the brain achieves true intelligence, including creativity. At the same time, conventional computer architecture has been unable to accommodate the vast amount of parallelism and complexity found in the human brain. MISD models of computing have been considered non-sensical because, like paradox, they result in multiple conflicting results. However, because they produce different results and do not need to converge, MISD computing can be the foundation of nearly perfect parallelism, thus may hold the secret to how the brain accommodates vast degrees of parallelism as well as accommodate conflict. The brain must also operate in real-time, and thus likely holds different solutions to the same set of inputs with some accommodating a quick answer, but not the best overall, but one which is necessary to survival. This work will focus on algorithm/processor pairs such as sort and speech recognition for which different algorithms process the same set of inputs, producing different results. The best result is then chosen as a tuple of time and quality, where quality is sacrificed in the interest of time. For example, the spoken word might be processed imprecisely at first, but in a better than nothing mode. However, more thinking might result in a different answer. These two modes of processing would process the same set of inputs, but be held in different parts of the brain that operate in nearly perfect independence. In this way, novel brain-inspired computer architecture can result in which the subconscious mind contains vast amounts of MISD parallel algorithms that operate in nearly perfect independence, and the conscious mind is viewed as a selector of the many possible answers. Since creativity also requires conflict, this research may also reveal how the brain’s structure results in creativity, which is required for true machine intelligence. This project will conduct experiments to demonstrate problems that have multiple possible algorithmic solutions with varying degree of accuracy dependent upon time and resources. This will form the basis of a high-level foundation for a new architecture that accommodates high degrees of parallelism, accommodates time and quality trade-offs, resolves conflict resolution and leads to an initial investigation of how the brain creates. Experiments will be conducted to illustrate our approach and generalization of the architecture and approach will be developed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.