Tag Archives: cognitive science
10 Jun Knowledge is the New Foundation for Success
Joe Roushar – June 2020 Retooling for The Beginning of a New Age This year, 2020 will be the turning point in AI adoption because successful implementations will be available to small and large organizations without breaking the bank. Success will be measured in specific business value achieved. Affordability will dramatically improve because of AI […]
04 Jul Cognitive Multi-Processing
Joe Roushar – July 2017 Divide and Conquer Swarm computing applications, with large numbers of autonomous agents are beginning to appear and deliver stunning results. The combination of autonomy, simple tasks and parallelism has great power. Today I’ll address parallel computing and models for breaking down computational problems. I will not address the question of autonomy today, […]
27 Oct The Nature of Innovative Thinking
Mental Exploration The shape of the world changed radically when folks from the eastern and western hemispheres became aware of one another and of their respective geographies. The Age of Exploration (AKA the Age of Discovery) was amazing – or should I say “it is amazing”? While the focus has changed from continents and cultures, to galaxies […]
26 May AI Domains and Approaches
Grouping, Classifying and Categorizing How do you solve big technical problems? Rather than selecting or inventing an approach and then attempting to apply it to a problem to see how well it works, let’s analyze the problem and see if we can find or invent a solution that matches the problem space, and see if […]
20 May Cybernetic Modeling for Smarty-Pants
Introduction Model railroads come in several scales: O, HO and N gauge enable hobbyists to model real-world objects in miniature using successively smaller standards. In N gauge it is possible to build an entire city in the basement. A good model photographed with still or motion pictures may be so realistic that viewers believe they are looking […]
06 May Impulse Waves in Layers
Layered Model Just as the brain has areas with three to six distinct layers, a typical artificial neural systems (ANS) also has several layers. The example at right shows a network with three layers that illustrate a neural network‘s distributed architecture. The uniform circles connected by lines are symbolic of the state of an ANS at […]
30 Apr Exceptional Logic
Exceptions to the Rules In natural language, exceptions to rules of grammar and other characteristics are frequent, and exhibit little consistency or predictability. They may multiply in discourse and in situations where the speaker/writer’s competence is limited. Idioms and irregular verbs are common exceptions which can be quite difficult to categorize or describe using formal descriptive grammar. Further exceptions […]
28 Apr Mosaic of Concepts
KR Mosaic On our way to knowledge representation (KR), we’ve looked at concepts and logical propositions and words and taxonomies. I know this can all be a bit confusing, but please bear with me a little longer. Word relations are more than a two-dimensional mosaic of related concepts – they form a deep hierarchy with multiple […]
26 Apr Continuity of Learning
Production and Comprehension We know that comprehension and language production occur in different areas of the brain and occupy opposite ends of the continuum in the communicative model. The relative independence of the production and comprehension centers suggests one of three possibilities: Syntactic and lexical data are replicated in both the production and comprehension centers of […]
25 Apr Conceptual Paradigms
Conceptual Structure The different functions of language are acquired at different stages. As described by Sowa, these functions show why semantics can be considered a guide to how we learn syntax: “First, children associate words with concrete concepts used in perceiving the world and acting upon it. Next, they learn syntactic rules for mapping concepts […]