Cognitive Computing - Revision history

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User: Created page with "'''Cognitive Computing (CC)''' is the simulation of human thought processes in a computer model. It is a technology platform based on the scientific disciplines of artificial..."

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Created page with "'''Cognitive Computing (CC)''' is the simulation of human thought processes in a computer model. It is a technology platform based on the scientific disciplines of artificial..."

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'''Cognitive Computing (CC)''' is the simulation of human thought processes in a computer model. It is a technology platform based on the scientific disciplines of artificial intelligence and signal processing. In summary, a cognitive computer ploughs through un/structured data, to find hidden knowledge and present data in an actionable form. It is worth noting that CC is an iterative process, with humans verifying or discarding any new discoveries. This allows the system to ‘learn’ over time, and become better at identifying patterns.<ref>Definition - What Does Cognitive Computing mean? [https://mse238blog.stanford.edu/2017/07/jgokani/cognitive-computing/ Stanford.edu]</ref>

Looking back at the origin of Cognitive computing, it was first mentioned by Alan Turing in 1950, through his ‘Computing Machinery and Intelligence’ paper. He proposed the Turing Test, to assess a machine’s ability to exhibit intelligent human behavior. The science behind Cognitive computing has only recently gained momentum, with advancements made within fields such as data mining and natural language processing. The graph below shows a timeline of the progression of Cognitive computing:

[[File:Path of Cognitive Computing.png|400px|Mapping the Path to Cognitive Computing.png]]<br />
source: Stanford University

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 == See Also ==
 *[[Cognitive Bias]]
 *[[Cognitive Dimensions of Notations]]

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-[[File:Evolution of Cognitive Computing.jpg|400px|Evolution of Cognitive Computing]]<br />
+[[File:Evolution of Cognitive Computing.jpg|600px|Evolution of Cognitive Computing]]<br />
 source: Jorge Leonel
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 *[[Automatic Content Recognition (ACR)]]
 *[[Autonomous System (AS)]]
 *[[Distributed Computing]]
 *[[Computational Finance]]

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 '''Cognitive Computing (CC)''' is the simulation of human thought processes in a computer model. It is a technology platform based on the scientific disciplines of [[Artificial Intelligence (AI)|artificial intelligence]] and [[Signal Processing|signal processing]]. In summary, a cognitive computer ploughs through un/structured data, to find hidden knowledge and present [[Data|data]] in an actionable form. It is worth noting that CC is an iterative process, with humans verifying or discarding any new discoveries. This allows the system to ‘learn’ over time, and become better at identifying patterns.<ref>Definition - What Does Cognitive Computing mean? [https://mse238blog.stanford.edu/2017/07/jgokani/cognitive-computing/ Stanford.edu]</ref>
-[[File:Path of Cognitive Computing.png|400px|Mapping the Path to Cognitive Computing.png]]<br />
+[[File:Cognitive Computing.png|400px|Cognitive Computing]]<br />
-source: Stanford University
+source: Peter Summer, IBM
@@ Line 13: / Line 39: @@
 As computers become more able to think like human beings, they will also expand our capabilities and knowledge. Just as the heroes of science fiction movies rely on their computers to make accurate predictions, gather data, and draw conclusions, so we will move into an era when computers can augment human knowledge and ingenuity in entirely new ways.
@@ Line 50: / Line 84: @@
 *Leaner & More Efficient [[Business Process|Business Processes]]: Cognitive computing can analyze emerging patterns, spot business opportunities and take care of critical process-centric issues in real time. By examining a vast amount of data, a cognitive computing system such as Watson can simplify processes, [[Risk Mitigation|reduce risk]] and pivot according to changing circumstances. While this prepares businesses in building a proper response to uncontrollable factors, at the same time it helps to create lean business processes.
 *Improved Customer Interaction: The technology can be used to enhance customer interactions by implementing [[Robotic Process Automation (RPA)|robotic process automation]]. Robots can provide contextual information to customers without needing to interact with other staff members. As cognitive computing makes it possible to provide only relevant, contextual and valuable information to the customers, it improves customer experience, thus making [[Customer Satisfaction|customers satisfied]] and much more [[Customer Engagement|engaged with a business]].

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 [[File:Path of Cognitive Computing.png|400px|Mapping the Path to Cognitive Computing.png]]<br />
 source: Stanford University
@@ Line 39: / Line 36: @@
 *Education: Even if Cognitive Computing can not take the place of teachers, it can still be a heavy driving force in the education of students. Cognitive Computing being used in the classroom is applied by essentially having an assistant that is personalized for each individual student. This cognitive assistant can relieve the stress that teachers face while teaching students, while also enhancing the student’s learning experience over all. Teachers may not be able to pay each and every student individual attention, this being the place that cognitive computers fill the gap. Some students may need a little more help with a particular subject. For many students, Human interaction between student and teacher can cause anxiety and can be uncomfortable. With the help of Cognitive Computer tutors, students will not have to face their uneasiness and can gain the confidence to learn and do well in the classroom. While a student is in class with their personalized assistant, this assistant can develop various techniques, like creating lesson plans, to tailor and aid the student and their needs.
 *Healthcare: Numerous tech companies are in the process of developing technology that involves Cognitive Computing that can be used in the medical field. The ability to classify and identify is one of the main goals of these cognitive devices. This trait can be very helpful in the study of identifying carcinogens. This cognitive system that can detect would be able to assist the examiner in interpreting countless numbers of documents in a lesser amount of time than if they did not use Cognitive Computer technology. This technology can also evaluate information about the patient, looking through every medical record in depth, searching for indications that can be the source of their problems.
-*Industry work: Cognitive Computing in conjunction with big data and algorithms that comprehend customer needs, can be a major advantage in economic decision making. The powers of Cognitive Computing and AI hold the potential to affect almost every task that humans are capable of performing. This can negatively affect employment for humans, as there would be no such need for human labor anymore. It would also increase the inequality of wealth; the people at the head of the Cognitive Computing industry would grow significantly richer, while workers without ongoing, reliable employment would become less well off. The more industries start to utilize Cognitive Computing, the more difficult it will be for humans to compete. Increased use of the technology will also increase the amount of work that AI-driven robots and machines can perform. Only extraordinarily talented, capable and motivated humans would be able to keep up with the machines. The influence of competitive individuals in conjunction with AI/CC with has the potential to change the course of humankind.
+*Industry work: Cognitive Computing in conjunction with big data and [[Algorithm|algorithms]] that comprehend [[Customer Needs|customer needs]], can be a major advantage in economic decision making. The powers of Cognitive Computing and AI hold the potential to affect almost every task that humans are capable of performing. This can negatively affect employment for humans, as there would be no such need for human labor anymore. It would also increase the inequality of wealth; the people at the head of the Cognitive Computing industry would grow significantly richer, while workers without ongoing, reliable employment would become less well off. The more industries start to utilize Cognitive Computing, the more difficult it will be for humans to compete. Increased use of the technology will also increase the amount of work that AI-driven robots and machines can perform. Only extraordinarily talented, capable and motivated humans would be able to keep up with the machines. The influence of competitive individuals in conjunction with AI/CC with has the potential to change the course of humankind.
@@ Line 46: / Line 43: @@
 For example, Google Maps and Fitbit use [[Big Data|big data]], [[Machine Learning|machine learning]], and [[Predictive Analytics|predictive analytics]] in their problem solving methods. Siri, Alexa, Watson, and company-specific chatbots do as well, but they can receive and deliver [[Information|information]] naturally, leveraging both structured and unstructured data. These products are AI technologies embodied with human-like names and personalities.

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 The neural network, inspired by the architecture of neurons in the human brain, comprises systems of nodes — sometimes termed neurons — with weighted interconnections. A deep neural network includes multiple layers of neurons. Learning occurs as a process of updating the weights between these interconnections. One way of thinking about a neural network is to imagine it as a complex decision tree that the computer follows to arrive at an answer.
 In deep learning, the learning takes place through a process called training. Training data is passed through the neural network, and the output generated by the network is compared to the correct output prepared by a human being. If the outputs match (rare at the beginning), the machine has done its job. If not, the neural network readjusts the weighting of its neural interconnections and tries again. As the neural network processes more and more training data — in the region of thousands of cases, if not more — it learns to generate output that more closely matches the human-generated output. The machine has now “learned” to perform a human task.
@@ Line 16: / Line 27: @@
 Preparing training data is an arduous process, but the big advantage of a trained neural network is that once it has learned to generate reliable outputs, it can tackle future cases at a greater speed than humans ever could, and its learning continues. The training is an investment that pays off over time, and machine learning researchers have come up with interesting ways to simplify the preparation of training data, such as by crowdsourcing it through services like Amazon Mechanical Turk.
-When combined with NLP capabilities, IBM’s Watson cognitive computing combines three “transformational technologies.” The first is the ability to understand natural language and human communication; the second is the ability to generate and evaluate evidence-based hypotheses; and the third is the ability to adapt and learn from its human users.
+When combined with [[Natural Language Processing (NLP)|NLP]] capabilities, IBM’s Watson cognitive computing combines three “transformational technologies.” The first is the ability to understand natural language and human communication; the second is the ability to generate and evaluate evidence-based hypotheses; and the third is the ability to adapt and learn from its human users.
 While work is aimed at computers that can solve human problems, the goal is not to push human beings’ cognitive abilities out of the picture by having computing systems replace people outright, but instead to supplement and extend them.
-== What Cognitive Computing Does<ref>What can cognitive computing do? [https://www.forbes.com/sites/bernardmarr/2016/03/23/what-everyone-should-know-about-cognitive-computing/?sh=488583495088 Forbes]</ref> ==
+[[File:How Cognitive Computing Works.jpg|400px|How Cognitive Computing Works]]<br />
-For example, according to a TED Talk from IBM, Watson could eventually be applied in a healthcare setting to help collate the span of knowledge around a condition, including patient history, journal articles, best practices, diagnostic tools, etc., analyze that vast quantity of information, and provide a recommendation. The doctor is then able to look at evidence-based treatment options based on a large number of factors including the individual patient’s presentation and history, to hopefully make better treatment decisions.
+source: Smatsheet

← Older revision		Revision as of 14:15, 27 October 2021
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	[[File:Path of Cognitive Computing.png\|400px\|Mapping the Path to Cognitive Computing.png]]<br />		[[File:Path of Cognitive Computing.png\|400px\|Mapping the Path to Cognitive Computing.png]]<br />
	source: Stanford University		source: Stanford University
		+
		+
		+	How Cognitive Computing Works
		+	So, how does cognitive computing work in the real world? Cognitive computing systems may rely on deep learning and neural networks. Deep learning, which we touched on earlier in this article, is a specific type of machine learning that is based on an architecture called a deep neural network.
		+
		+	The neural network, inspired by the architecture of neurons in the human brain, comprises systems of nodes — sometimes termed neurons — with weighted interconnections. A deep neural network includes multiple layers of neurons. Learning occurs as a process of updating the weights between these interconnections. One way of thinking about a neural network is to imagine it as a complex decision tree that the computer follows to arrive at an answer.
		+
		+	In deep learning, the learning takes place through a process called training. Training data is passed through the neural network, and the output generated by the network is compared to the correct output prepared by a human being. If the outputs match (rare at the beginning), the machine has done its job. If not, the neural network readjusts the weighting of its neural interconnections and tries again. As the neural network processes more and more training data — in the region of thousands of cases, if not more — it learns to generate output that more closely matches the human-generated output. The machine has now “learned” to perform a human task.
		+
		+	Preparing training data is an arduous process, but the big advantage of a trained neural network is that once it has learned to generate reliable outputs, it can tackle future cases at a greater speed than humans ever could, and its learning continues. The training is an investment that pays off over time, and machine learning researchers have come up with interesting ways to simplify the preparation of training data, such as by crowdsourcing it through services like Amazon Mechanical Turk.
		+
		+	When combined with NLP capabilities, IBM’s Watson cognitive computing combines three “transformational technologies.” The first is the ability to understand natural language and human communication; the second is the ability to generate and evaluate evidence-based hypotheses; and the third is the ability to adapt and learn from its human users.
		+
		+	While work is aimed at computers that can solve human problems, the goal is not to push human beings’ cognitive abilities out of the picture by having computing systems replace people outright, but instead to supplement and extend them.
		+
		+
		+	== What Cognitive Computing Does<ref>What can cognitive computing do? [https://www.forbes.com/sites/bernardmarr/2016/03/23/what-everyone-should-know-about-cognitive-computing/?sh=488583495088 Forbes]</ref> ==
		+	For example, according to a TED Talk from IBM, Watson could eventually be applied in a healthcare setting to help collate the span of knowledge around a condition, including patient history, journal articles, best practices, diagnostic tools, etc., analyze that vast quantity of information, and provide a recommendation. The doctor is then able to look at evidence-based treatment options based on a large number of factors including the individual patient’s presentation and history, to hopefully make better treatment decisions.
		+
		+	In other words, the goal (at this point) is not to replace the doctor, but expand the doctor’s capabilities by processing the humongous amount of data available that no human could reasonably process and retain, and provide a summary and potential application. This sort of process could be done for any field in which large quantities of complex data need to be processed and analyzed to solve problems, including finance, law, and education. These systems will also be applied in other areas of business including consumer behavior analysis, personal shopping bots, customer support bots, travel agents, tutors, security, and diagnostics. Hilton Hotels recently debuted the first concierge robot, Connie, which can answer questions about the hotel, local attractions, and restaurants posed to it in natural language. The personal digital assistants we have on our phones and computers now (Siri and Google among others) are not true cognitive systems; they have a pre-programmed set of responses and can only respond to a preset number of requests. But the time is coming in the near future when we will be able to address our phones, our computers, our cars, or our smart houses and get a real, thoughtful response rather than a pre-programmed one.
		+
		+	As computers become more able to think like human beings, they will also expand our capabilities and knowledge. Just as the heroes of science fiction movies rely on their computers to make accurate predictions, gather data, and draw conclusions, so we will move into an era when computers can augment human knowledge and ingenuity in entirely new ways.
		+
		+
		+	== Applications of Cognitive Computing<ref>Applications of Cognitive Computing [https://en.wikipedia.org/wiki/Cognitive_computing Wikipedia]</ref> ==
		+	*Education: Even if Cognitive Computing can not take the place of teachers, it can still be a heavy driving force in the education of students. Cognitive Computing being used in the classroom is applied by essentially having an assistant that is personalized for each individual student. This cognitive assistant can relieve the stress that teachers face while teaching students, while also enhancing the student’s learning experience over all. Teachers may not be able to pay each and every student individual attention, this being the place that cognitive computers fill the gap. Some students may need a little more help with a particular subject. For many students, Human interaction between student and teacher can cause anxiety and can be uncomfortable. With the help of Cognitive Computer tutors, students will not have to face their uneasiness and can gain the confidence to learn and do well in the classroom. While a student is in class with their personalized assistant, this assistant can develop various techniques, like creating lesson plans, to tailor and aid the student and their needs.
		+	*Healthcare: Numerous tech companies are in the process of developing technology that involves Cognitive Computing that can be used in the medical field. The ability to classify and identify is one of the main goals of these cognitive devices. This trait can be very helpful in the study of identifying carcinogens. This cognitive system that can detect would be able to assist the examiner in interpreting countless numbers of documents in a lesser amount of time than if they did not use Cognitive Computer technology. This technology can also evaluate information about the patient, looking through every medical record in depth, searching for indications that can be the source of their problems.
		+	*Industry work: Cognitive Computing in conjunction with big data and algorithms that comprehend customer needs, can be a major advantage in economic decision making. The powers of Cognitive Computing and AI hold the potential to affect almost every task that humans are capable of performing. This can negatively affect employment for humans, as there would be no such need for human labor anymore. It would also increase the inequality of wealth; the people at the head of the Cognitive Computing industry would grow significantly richer, while workers without ongoing, reliable employment would become less well off. The more industries start to utilize Cognitive Computing, the more difficult it will be for humans to compete. Increased use of the technology will also increase the amount of work that AI-driven robots and machines can perform. Only extraordinarily talented, capable and motivated humans would be able to keep up with the machines. The influence of competitive individuals in conjunction with AI/CC with has the potential to change the course of humankind.