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FAQ   

  1. What is Artificial Intelligence (AI)?
  2. What branches of AI are there?
  3. What is Artificial Cognition (AC)?
  4. What Contemporary Theories of Cognition are There?
  5. What is the Artificial Cognition Engine (ACE)?
  6. In What Applications is ACE Used Now?
  7. How can I use AC Technologies?
  8. As a client, how can iCognate help me?
  9. Are there more references for AI and AC R&D?
What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is the capacity of a digital computer or computer-controlled robot device to perform tasks commonly associated with the higher intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. The term is frequently applied to that branch of computer science concerned with the development of systems endowed with such capabilities.

Theoretically, there are two conjectures concerning the ability of AI to accomplish these higher intellectual processes characteristic of humans: 1) Strong Equivalence (Strong AI) and 2) Weak Equivalence (Weak AI). The Strong Equivalence makes the bold claim that computers can be made to think on a level (at least) equal to humans, while the Weak Equivalence simply states that some "thinking-like" features can be added to computers to make them more useful tools.  

At present, most experts agree that we have already achieved the Weak Equivalence, e.g. witness expert systems, speech recognition software, and chess playing.  However, the Strong Equivalence is still a topic of much debate and perhaps more fundamentally to this debate is the question of exactly what does 'think' and 'thinking-like' mean?  These questions are at the heart of understanding the capabilities and limitations of today's AI and have increasingly grown to include other areas of study ranging from  as Neurology to Psychology to Philosophy.

Regardless of the position taken in this debate, it is a fact that present-day digital computers and computers-controlled robot devices only operate under the control of computer programs (software). This means that any intelligence that systems demonstrate will be the direct result of the emergent behavior from computer programs that run on these platforms.  

The computer programs used today to perform AI tasks are designed to manipulate symbolic information at extremely high speeds, in order to compensate for their partial lack of human knowledge and selectivity. Some of these programs are called expert systems. Other programs are designed to simulate human capabilities for problem solving through the use of highly selective search and recognition methods, rather than through superhuman processing speeds.  Yet other programs, knowledge-based expert systems, enable computers to make decisions for solving complicated non numerical problems. These expert systems consist of hundreds or thousands of "if-then" login rules formulated with knowledge gleaned from leading authorities in a given field.  Both expert systems and programs simulating human methods have attained the performance levels of human experts and professionals in performing certain specific tasks, however, there are still no expert systems that match human flexibility over wider domains or in tasks requiring much everyday knowledge.

Major and continuing advances in computer processing speeds and memory sizes have facilitated the development of AI programs. Although most AI programs attempting to simulate higher mental functions incorporate the bottleneck of limited short-term memory, which restricts humans to carrying out one or a few mental tasks at a time, many investigators have begun to explore how the intelligence of computer programs can be enhanced by incorporating parallel processing, i.e. the simultaneous execution of several separate operations by means of computer memories that allow many processes to be carried out at once. The question of which portions of the human brain (and their corresponding thought processes) operate serially and which operate in parallel has been a topic of intense debate by researchers in both the cognitive sciences and AI, but no clear verdict has yet been reached.

The largest computer memories now contain elementary circuits that are comparable in number to the synaptic connections (about 10 trillion) in the human brain, and they operate at speeds (billions of operations per second) that are far faster than elementary neural speeds (which are at most thousands of operations per second). The challenge driving AI research is to understand how computers' capabilities must be organized in order to reproduce the many kinds of mental activity that are comprised by the term "thinking." AI research has thus focused on understanding the mechanisms involved in human mental tasks and on designing software that performs similarly, starting with relatively simple ones and continually progressing to levels of greater complexity

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What branches of AI are there?

Artificial Intelligence (AI) spans an enormous breadth and depth of applications and theoretical areas of study including:

  • Artificial Life
  • Automated Deduction/Theorem Proving
  • Case-Based Reasoning/Analogical Reasoning
  • Cognitive Modeling
  • Cognitive Science
  • Computational Biology
  • Computer Vision: See Machine Vision
  • Connectionism/Neural Networks
  • Decision Theory AI
  • Distributed AI
  • Emotion
  • Fuzzy Logic
  • Genetic Algorithms
  • Integrated AI Architectures/Software Agents
  • Intelligent Tutoring, AI & Education
  • Knowledge Representation
  • Legal Reasoning AI
  • Logic Programming and Logic-based AI
  • Machine Discovery
  • Machine Learning
  • Machine Vision
  • Manufacturing AI
  • Medicine AI
  • Natural Language Processing (NLU, NLG, Parsing, NLI, Speech)
  • Nonmonotonic Reasoning
  • Philosophy of AI
  • Planning
  • Qualitative Physics and Model Based Reasoning
  • Reasoning Under Uncertainty (Probabilistic Reasoning, Approximate Reasoning, etc.)
  • Robotics
  • Search
  • Temporal Reasoning

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What is Artificial Cognition (AC)?

Artificial Cognition (AC) is artificially based natural language - sentential parsing, processing, and recognition.  AC is one of two main themes in the field of cognitive science and modeling.  Cognitive science and modeling are themselves branches of AI.  These two distinct themes in cognitive science and modeling are: 1. Natural Cognition (NC) - language parsing, processing, and recognition by human beings and 2) Artificial Cognition (AC) - artificially based natural language - sentential parsing, processing, and recognition.

In theory, NC explores linguistic theory, psycholinguistics, linguistic methodology, philosophy of language, acquisition of language, symbolic systems (mathematics), memory and language, while AC explores text analysis, computational linguistics, natural language processing, and alternative architectures for performing these tasks.  In practice, NC and AC are more intimately related.  

Both NC and AC investigate the processes involved in knowing, or the act of knowing, which includes perception and judgment.  Cognition includes every mental process that can be described as an experience of knowing as distinguished from an experience of feeling or of willing.  This involves all processes of consciousness by which knowledge is built up, including perceiving, recognizing, conceiving, and reasoning. The essence of cognition is judgment in which a certain object is distinguished from other objects and is characterized by some concept or concepts.

In addition, AC is often used as a tool for understanding the nature of human intelligence, i.e. NC, by creating computer models to elucidate and replicate processes of cognition in humans.  Programs have been developed that enable computers to comprehend commands in a natural language, e.g. ordinary English.  However, software systems of this type that have been produced so far are limited in their vocabulary and knowledge to specific, narrowly defined subject areas. They contain large amounts of information about the meaning of words pertaining to that subject, as well as information about grammatical rules and common violations of those rules.

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What Contemporary Theories of Cognition are There?

The nature of cognition and the relationship between the knowing mind and external reality have been exhaustively discussed by philosophers since antiquity. Cognition and its development have been subjected to many viewpoints and interpretations. The psychologist is concerned with the cognitive process as it affects learning and behavior.

There are two broad approaches to contemporary cognitive theory. The information processing approach attempts to understand human thought and reasoning processes by comparing the mind to a sophisticated computer system that is designed to acquire, process, store, and use information according to various programs.

The second approach is based on the work of Swiss psychologist Jean Piaget (1896-1980), who viewed cognitive adaptation in terms of two basic processes: assimilation and accommodation. Assimilation is the process whereby an individual interprets reality in terms of his own internal model of the world based on previous experience; whereas, accommodation is the process of changing that model by developing the mechanisms to adjust to reality. Piaget believed that representational thought does not originate in a social language but rather in unique symbols that serve as a foundation for a later, acquired language.

The American psychologist Jerome S. Bruner (b. 1915) broadened Piaget's concept by suggesting that the cognitive process is effected by the three modes we use to represent our world: the enactive mode involves representation through action; the iconic mode uses visual and mental images; and the symbolic mode uses language.

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What is the Artificial Cognition Engine (ACE)?

Our proprietary Artificial Cognition Engine (ACE) technology is a natural language - sentential recognition system.  It parses, process, and recognizes sentential information.  ACE is built on a proprietary meta-parsing system of natural language that incorporates elements of Bayesian machine learning for sentential recognition.

ACE can be used in standalone mode for query-command interactivity or as the kernel of a larger application to function as the "cerebrum" of intelligent applications. At present, his meta-language parsing and sentential recognition system is used in three distinct applications that are being developed and offered:1) iWork™, 2) iTrade™, and 3) iSearch™.

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In What Applications is ACE Used Now?

At core, our products are build on our proprietary Artificial Cognition Engine (ACE) technology.  This meta-language parsing and sentential recognition system is currently used in three distinct applications that are being developed and offered:

  1. iWork™- to create a human-like information experience with your computer...a personal worker on your computer desktop!
  2. iTrade™ - to increase trading profitability through cognitive textual processing...an intelligent trader who continually scans the news and markets and indicates potentially profitable trades for you!
  3. iSearch™ - to improve and extend data mining accuracy and searching capabilities...an advanced search assistant dedicated to helping you understand your data bases like never before!

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How can I use AC Technologies?

Briefly, you can use artificial cognition (AC) technologies in almost anything related to your use of the computer and information.

Here's a simple Gedanken Experiment (GE) to orient your thinking about how AC technologies can be used in practice.  Start by choosing a verb that describes an activity performed around your workplace or at home with the computer.  For example, since you access things around the office and home, choose the verb, access.  Now, choose a suffix that might be a plausible complement of the verb.  For example, the suffix, "information needed to answer customer questions from large databases."  Then, add the interrogative prefix: What would be the effect if I could automatically, cognitively...?"  Put it all together and you have, "What would be the effect if I could automatically, cognitively...access...information needed to answer customer questions from large databases?"

These type of questions help you identify how you might begin to use artificial cognition technologies (AC) technologies to transform your business challenges into profitable business opportunities.  To continue the questioning process, try our simple Gedanken Experiment Expert (GEE...) below.  Give it a try, it's free to ask GEE...

QUESTION: What would be the effect if I could automatically, cognitively...

...

...

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As a client, how can iCognate help me?

We at iCognate can help clients through our three types of solutions offerings: 1) our iProducts, 2) our iSoftware, and 3) our iServices.  Overall, our solutions transform your business challenges into business opportunities through the use of our artificial cognition technologies for the coming information age.  The results you experience include enhanced efficiency, increased accuracy, and improved profitability in your information experience.

Briefly, our iProducts are build on our proprietary Artificial Cognition Engine (ACE) technology and include 1) iWork™, 2) iTrade™, and 3) iSearch™.  Our iSoftware offering includes designing, developing, and delivering customized practical software in three major areas of focus: 1) Customization, 2) Integration and Development, and 3) Application Service Provider (ASP). Our iServices offerings assists, analyzes, and advises clients on the best solutions to their business challenges!  Our solutions offerings are built around our iCOGNATE.4 Process, for details click on the Client page.

Our iCOGNATE.4 Process start with assisting you to imagine the transformation that advanced cognition technologies could bring to you in your workplace or at home.  With these changes in mind, we analyze each scenario for its increased efficiency, productivity, and value added vis-a-vis your information experiences.  Finally, we advise you on the best business solution for your specific business challenges, even if our solutions involve products or software from other vendors.  

Get started transforming your business challenges into profitable business opportunities with iCognate.  We have helped others obtain results that enhance efficiency, increase accuracy, grow improve profitability.  We would welcome an opportunity to do the same for you and your business!

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Are there more references for AI and AC R&D?

References

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