Abstract
At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified agents with strong artificial intelligence based on communicative-associative logic by recurring development of professional skills, increasing visual, sound, subject, spatial and temporal sensitivity. For this purpose several diversifiable agents that try to get the same conclusion will give a more accurate result, so several diversifiable agents are combined into an ensemble. Then, based on the criteria of utility and preference, the final result is obtained based on the conclusions of diversifying agents. This approach increases accuracy. Bagging and Boosting techniques are used to form ensembles. Bagging is a combination of independent diversifiable agents by averaging patterns (weighted average, majority vote, or normal average). Boosting is the construction of ensembles of diversifiable agents consistently. The idea here is that the next agent will consider the errors of the previous agent. Due to the fact that diversifiable agents take into account errors committed by previous agents, it takes less time to get to a real response. The combination of Bagging and Boosting decision-making methods allows the development of intelligent artificial intelligence by ensembles of diversified agents. Cognitive virtual smart artificial intelligence becomes smarter through the accumulated professional experience of high-tech skills, competencies and knowledge, having increased visual, sound, subject, spatial and temporal sensitivity. Many researchers believe that the information technology industry is on the verge of a transition to smart universal artificial intelligence. The information technology industry is trying to find the boundaries of smart artificial intelligence. Standardization of strong artificial intelligence and the use of ensembles of intelligent compatible diversified agents will help to find boundaries in which smart artificial intelligence will benefit humanity and not harm.
Highlights
Modern artificial intelligence uses deep learning models
Technological smart artificial intelligence can detect novelty on the principle of opposite method from nasty based on objective conditions based on communicative associative logic
Smart artificial intelligence technology systems will consist of many smart components, such as visual detection subsystems, environmental perception, reasoning and decision making, and other smart subsystems
Summary
Modern artificial intelligence uses deep learning models. These are neural networks that run on graphics processors that perform hundreds of thousands of operations in parallel. It is still possible to increase the number of layers and accelerate calculations, this process quickly approaches the limit of computing power and energy consumption This requires a paradigm shift and moving beyond the current model of deep learning of neural networks. Project Cortex's new service uses machine learning and Microsoft Graph to create a "knowledge network" in which information will be collected from Microsoft 365 and external sources. This allows you to automate workflows and better manage companies. Technological smart artificial intelligence can compare thoughts, opinions, images and worldviews according to utility criteria. Technological smart artificial intelligence can choose thoughts, opinions, images and worldviews according to the criterion of preference. Technological smart artificial intelligence can detect novelty on the principle of opposite (optimal-not optimal; effective-not effective; dangerous-safe, etc.) method from nasty based on objective conditions based on communicative associative logic
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Intelligent Information Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
