Conscious Mind, Resonant Brain

2021 ◽  
Author(s):  
Stephen Grossberg
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Large Scale ◽  
Neural Circuits ◽  
Physical World ◽  
Brain Regions ◽  
Human Condition ◽  
Learning Technology ◽  
Large Scale Problems ◽  
The World

The book is the culmination of 50 years of intensive research by the author, who is broadly acknowledged to be the most important pioneer and current research leader who models how brains give rise to minds, notably how neural circuits in multiple brain regions interact together to generate psychological functions. The book provides a unified understanding of how, where, and why our brains can consciously see, hear, feel, and know about the world, and effectively plan and act within it. It hereby embodies a revolutionary Principia of Mind that clarifies how autonomous adaptive intelligence is achieved, thereby providing mechanistic explanations of multiple mental disorders, biological bases of morality, religion, and the human condition, as well as solutions to large-scale problems in machine learning, technology, and Artificial Intelligence. Because brains embody a universal developmental code, unifying insights also emerge about all living cellular tissues and about how mental laws reflect laws of the physical world.

scholarly journals Classification of Tennis Video Types Based on Machine Learning Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xun Gong ◽  
Fucheng Wang
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Rapid Development ◽  
Video Data ◽  
Learning Technology ◽  
Video Content ◽  
Video Classification ◽  
The World ◽  
Spatial Detection

With the rapid development of online video data, how to find the required information has become an urgent problem to be solved. This article focuses on sports videos and studies video classification and content-based retrieval techniques. Its purpose is to establish a mark and index of video content and to promote user acquisition through computer processing, analysis, and understanding of video content. Video tennis classification has high research and application value. This article focuses on video tennis based on the selection of the basic frame of each shot and proposes an algorithm for classification of shots based on average grouping. Based on this, we use a color-coded spatial detection method to detect the type of tennis match. Then, it integrates the results of audiovisual analysis to identify and classify exciting events in tennis matches. According to statistics, although the number of people participating in tennis cannot enter the top ten, the number of spectators ranks fourth. Four tennis tournaments, masters, and crown tournaments are held every year around the world. Watching large-scale international tennis matches has become a pillar of leisure and vacation for many people. Tennis matches last from two hours to four hours or more, and there are countless large and small tennis matches around the world every year, so the number of tennis records created is staggering. And artificial intelligence technology is rarely used in tennis in the sports world (5%), but football has reached 50%. Therefore, when dealing with such a large amount of data, we urgently need to find a fast and effective video retrieval classification method to find the required information. The experiment of tennis video classification research based on machine learning technology proves that the accuracy of tennis video classification reaches 98%, so this system has high feasibility.

scholarly journals Latest Advances of Natural Language Processing and their Applications in Everyday life

2020 ◽  
Vol 6 (10) ◽  
pp. 31-35
Author(s):  
Sai Sri Nandan Challapalli Shalini Jaiswal and Preeti Singh Bahadur
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Constraint Satisfaction ◽  
Large Scale ◽  
The World ◽  
Dramatic Shift

Natural language processing (NLP) area of Artificial Intelligence (AI) has offered the scope to apply and integrate various other traditional AI fields. While the world was working on comparatively simpler aspects like constraint satisfaction and logical reasoning, the last decade saw a dramatic shift in the research. Now large-scale applications of statistical methods, such as machine learning and data mining are in the limelight. At the same time, the integration of this understanding with Computer Vision, a tech that deals with obtaining information from visual data through cameras will pave way to bring the AI enabled devices closer to a layman also. This paper gives an overview of implementation and trend analysis of such technology in Sales and ServiceSectors.

scholarly journals AI in global healthcare: Need for robust governance frameworks

2020 ◽  
Author(s):  
Sandeep Reddy ◽  
Sonia Allan ◽  
Simon Coghlan ◽  
Paul Cooper
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Developing Countries ◽  
Clinical Care ◽  
Ethical Guidelines ◽  
Popular Discourse ◽  
The World ◽  
Healthcare Need

The re-emergence of artificial intelligence (AI) in popular discourse and its application in medicine, especially via machine learning (ML) algorithms, has excited interest from policymakers and clinicians alike. The use of AI in clinical care in both developed and developing countries is no longer a question of ‘if?’ but ‘when?’. This creates a pressing need not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort?

Conclusion

2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Risk Assessment ◽  
Big Data ◽  
The United States ◽  
Blaise Pascal ◽  
Division Problem ◽  
The World

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.

Mapping Continents, Inhabited Quarters and The Four Seas. Divisions of the World and the Ordering of Spaces in Latin-Christian, Arabic-Islamic and Chinese Cartography in the Twelfth to Sixteenth Centuries. A Critical Survey and Analysis

2018 ◽  
Vol 5 (2) ◽  
pp. 295-367 ◽  
Author(s):  
Christoph Mauntel ◽  
Klaus Oschema ◽  
Jean-Charles Ducène ◽  
Martin Hofmann
Keyword(s):  
Large Scale ◽  
Physical World ◽  
Critical Survey ◽  
Cultural Backgrounds ◽  
The World ◽  
Christian Thought ◽  
Geographical Space

Abstract This paper explores the presence and development of large-scale geographic categories in pre-modern cartography (twelfth to sixteenth centuries) in a combination of comparative and transcultural perspectives. Analysing Latin-Christian, Arabic-Islamic and Chinese maps, we demonstrate the varying degrees of importance accorded to large-scale geographic structures. The choice of related as well as independent traditions allows for the identification of specific emphases which reflect the influence of the respective cultural backgrounds and strategies applied in the ordering of space. While the analysed Chinese material concentrates on a geographical space that was perceived to form an ideal political and cultural unity without representing the entire physical world, Latin-Christian and Arabic-Islamic traditions share the focus on the whole “oecumene” that they both inherited from antique models. However, only Latin-Christian maps consistently and explicitly present a tripartite world that resonates with Trinitarian structures in Christian thought.

Uber and the making of an Algopticon - Insights from the daily life of Montreal drivers

2020 ◽  
Vol 44 (2) ◽  
pp. 241-260
Author(s):  
Rabih Jamil
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Daily Life ◽  
The World ◽  
Taxi Industry ◽  
Platform Economy

Using machine learning and artificial intelligence, Uber has been disrupting the world taxi industry. However, the Uber algorithmic apparatus managed to perfectionize the scalable decentralized tracking and surveillance of mobile living bodies. This article examines the Uber surveillance machinery and discusses the determinants of its algorithmically powered ‘all-seeing power’. The latter is being figured as an Algopticon that reinvents Bentham’s panopticon in the era of the platform economy.

scholarly journals Machine learning challenges and impact: an interview with Thomas Dietterich

2017 ◽  
Vol 5 (1) ◽  
pp. 54-58 ◽  
Author(s):  
Zhi-Hua Zhou
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Driving Force ◽  
Professor Emeritus ◽  
State University ◽  
Learning Society ◽  
Learning Challenges ◽  
The World ◽  
The Usa ◽  
Oregon State University

Abstract Machine learning is the driving force of the hot artificial intelligence (AI) wave. In an interview with NSR, Prof. Thomas Dietterich, the distinguished professor emeritus of computer science at Oregon State University in the USA, the former president of Association of Advancement of Artificial Intelligence (AAAI, the most prestigious association in the field of artificial intelligence) and the founding president of the International Machine Learning Society, talked about exciting recent advances and technical challenges of machine learning, as well as its big impact on the world.

Evaluation of maker space index system based on machine learning and intelligent interactive system

2020 ◽  
Vol 39 (4) ◽  
pp. 5941-5952
Author(s):  
Yang Chunhe
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Index System ◽  
Evaluation System ◽  
Learning System ◽  
Interactive System ◽  
Learning Technology ◽  
Integrated Learning System ◽  
Performance Evaluation System ◽  
Innovation Space

Machine learning technology is the core of artificial intelligence and the basis of computer intelligence. In recent years, machine learning technology has integrated and developed different learning methods, and the research of integrated learning system with more flexible and efficient form is also emerging. In this paper, the authors analyze the maker space index system based on machine learning and intelligent interactive system. As a comprehensive innovation and entrepreneurship platform, mass innovation space has the characteristics of both existing entrepreneurship service system and knowledge innovation driven. Through the index score calculation, the related evaluation system is constructed, the final score of social support system is 61.4.Multi-factor performance evaluation system based on machine learning and artificial intelligence,this paper reveals the development and change law of maker space, and provides theoretical basis for the future operation and decision-making of maker space.

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