N/Visnium AI Inc

Itoric has developed a linguistics-based platform on which it is building a system of general intelligence. Its core is based in linguistics, enabling it to go where AI cannot readily go and do what AI cannot possibly do. It skirts the current industry paradigm of creating software-based products whose logic is based on a human programmer's knowledge and ability. We have dubbed this new realm 'Human-Like Intelligence' (HLI). The HLI 'agent' is trained in English rather than with numbers and data. For analysis and problem solving, it does not use scripted or programmed methods. For its enabling technology, Itoric has one patent issued, one pending and another in process . HLI contrasts with AI-based intelligent systems is that it quite accurately mimics human thinking. Traditional situationally-dependent programming or scripting is not used, neither by Itoric nor the end customer. HLI instead depends upon English-language teaching, back-stories, observations and situational briefings. Itoric's HLI is Subject-Matter Expert (SME) trained, something for which no equivalent exits under the AI paradigms of the past 70 years. For autonomous systems, the accuracy and completeness of an HLI's assessments and decisions are driven by the completeness of its text-based training. Unlike programmed autonomous systems, performance does not depend on how accurately software requirements were defined or how insightful its programmers were. Beginning in 2013, the founder created new IP for a method of storing concepts and knowledge in a now-patented specific form of data graph. Access to the HLI's gained knowledge is linguistics-based, and every neuron in it is self-describing, in English. Its internal data graph design allows for rapid multi-dimensional accesses of concepts and knowledge. With superior linguistic approaches, it understands every-day nuanced meanings and purpose for every word in a sentence or fragment of speech. Concepts in its graph-like memory are learned, managed and updated primarily in ordinary English. Training is text-based, created by subject-matter experts, whether dealing with how to walk or the implications of human action. The enabling technology was its patented neuron structure that each represents a single concept. With this, the creation of a robust English parser and related semantic analyzer were possible. The analysis of external text's emotional content is a natural byproduct of the HLI's semantic analyzer, as it the very concept of topic. Both of these are difficult for conventional systems, as is the correct interpretation of colloquial idioms in context. Here, they are natural outcomes flowing from the semantic analyzer. Many fundamental paradigms, tenants and methods of Artificial Intelligence (AI) are demonstrated to be self-limiting and self-perpetuating. They have confined Artificial Intelligence to niches far removed from the original lofty dreams of a "general intelligence". That is, AI cannot be applied almost anywhere human-like intelligence is needed, whereas Itoric's HLI system can be. The timeframe for AI arriving at such an inflection of general intelligence remains 20 years distant, a prognostic delayed year over year. In its persistence, Itoric has overcome high barriers to entry for general intelligence, having solved intractable unbounded problems. The HLI is not bio-mimetic. Rather, the psycho-mimetic nature of the Visel Mind Model readily handles cultural idioms, regional culture, human values, political issues, and even the broken English that makes up today's (English) communication. The initial target market for Itoric's HLI are the autonomous analysis of intelligence, finding its implications, and the control of systems where a human in the loop is not practical. A general manager from one of the three-letter agencies disagreed with the founders assessment as to the HLI's market estimate of $200B. He insisted that the more realistic estimate is $3T. The founder has since come to r

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