Project NARS expected to bolster Future AI’s graph-based AI system
WASHINGTON, DC, DISTRICT OF COLUMBIA, USA, Nov. 15, 2022 /EINPresswire.com/ — Future AI has awarded a grant to Temple University’s NARS project, one of the artificial general intelligence (AGI) systems the most efficient currently available. NARS, which stands for Non-Axiomatic Reasoning System, includes features such as reasoning, learning, planning, perception, and temporal/procedural control that will be merged into Future AI’s existing graph-based AGI architecture.
Designed to understand in the same way as humans and serve as the basis for real-world applications of artificial intelligence (AI), Future AI’s technologies include a sophisticated self-adaptive hypergraph as the basis for reasoning and control, language processing natural to transpose English to the internal representation of knowledge, and a small robot as material.
“By using the general-purpose reasoning model developed for the NARS project, we believe we can strengthen our efforts to ensure that Future AI’s graph-based AI system will exhibit desirable cognitive capabilities,” says Charles Simon, Founder and CEO of Future AI.
Dependent on a single basic technique for performing various cognitive functions and solving various problems, NARS is built on a reasoning system framework, with a logical component (consisting of a formal language for knowledge representation, a semantic theory of language, and a set of inference rules) and a control component (consisting of a memory structure and a control mechanism).
Based on the belief that the essence of intelligence is the principle of adapting to the environment while working with insufficient knowledge and resources, NARS features “a rich and expressive internal language (narrais), taking decision, planning, temporal reasoning (anticipation and prediction), explainability, and real-time learning with little or no prior knowledge,” according to Pei Wang, Ph.D., NARS research lead. The NARS model also addresses several Fundamental theoretical issues not addressed by other AGI projects, including uncertainty management, resource allocation, and conceptual representation.
To date, Future AI has developed two products: Sallie, a prototype software and artificial entity that learns in real time with vision, hearing, speech and mobility, giving it the ability to draw conclusions; and Brain Simulator II, which allows experimentation with various AI algorithms to create an end-to-end AGI system with modules for vision, hearing, robotic control, learning, internal modeling, planning, imagination and foresight.
“Working with the NARS team, we expect shared lessons to be learned in perception, reasoning and decision-making as Future AI’s system matures, allowing Sallie to cultivate an understanding of relationships cause-and-effect complexes, develop a meaningful understanding of physical objects, and actively perceives the flow of time using his sensory capacity for the development of vision, hearing, touch and speech,” concludes Simon .
Future AI has already raised $2 million in seed funding to accelerate the development of its technology and algorithms, including its Universal Knowledge Store (UKS) which aggregates different types of information and creates links between them, similar to processes cognitions of human intelligence. Modeled in neurons, the UKS has biological plausibility and the ability to learn and function unsupervised as children do.
Future AI was also recently named one of the top AI companies to watch by AI Time Journal, an AI industry leader, for its work “pioneering and developing implementable solutions to achieve the ‘IAG’.
For more information on Future AI, visit https://FutureAI.guru
About Future AI
Future AI is an award-winning startup that develops technologies that think with breakthrough AI algorithms to create artificial general intelligence. Winner of IT World’s “Startup of the Year in AI” award, Future AI’s technologies are designed to understand like humans and serve as the foundation for a variety of real-world AI applications, from self-driving cars to fully automated customer service.
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