Artificial Intelligence (AI) - Revision history

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 == See Also ==
-[[Artificial General Intelligence (AGI)]]<br />
+*[[Artificial General Intelligence (AGI)]]
-[[Artificial Neural Network (ANN)]]<br />
+*[[Artificial Neural Network (ANN)]]
-[[Human Computer Interaction (HCI)]]<br />
+*[[Human Computer Interaction (HCI)]]
-[[Human-Centered Design (HCD)]]<br />
+*[[Human-Centered Design (HCD)]]
-[[Cognitive Computing]]<br />
+*[[Cognitive Computing]]
-[[Machine-to-Machine (M2M)]]<br />
+*[[Machine-to-Machine (M2M)]]
-[[Machine Learning]]<br />
+*[[Machine Learning]]

@@ Line 66: / Line 66: @@
 *Real-time universal translation The application of natural language processing to enable two humans (with no common language) to understand each other in real-time.
 *Neuromorphic computing. Future generation computing [[hardware]] that mimics the function of the human brain in silicon chips.
-*Machine Learning. Algorithms that can learn from and make predictions on data. Overlaps with computational and Bayesian [[statistics]]. Underpins predictive [[analytics]] and data-mining.
+*Machine Learning. Algorithms that can learn from and make predictions on data. Overlaps with computational and Bayesian statistics. Underpins predictive [[analytics]] and data-mining.
 *Next gen cloud robotics. [[Convergence]] of AI, big data, cloud and the as-a-[[service]] model will enable a cloud-based robotic brain that robots can use for high powered intelligent and intuitive [[collaboration]] with humans.
 *Robotic personal assistants. Cloud-based AI learns from big data to enable human-like social robots that can perform usefully as personal assistants.

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	[[File:Artificial_Intelligence1.jpg\|500px\|What is Artificial Intelligence]]<br />		[[File:Artificial_Intelligence1.jpg\|500px\|What is Artificial Intelligence]]<br />
	source: [https://www.trollhetta.com/?page_id=5 Trollhetta]		source: [https://www.trollhetta.com/?page_id=5 Trollhetta]
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		+	__TOC__

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-[[File:Artificial_Intelligence1.jpg|400px|What is Artificial Intelligence]]<br />
+[[File:Artificial_Intelligence1.jpg|500px|What is Artificial Intelligence]]<br />
 source: [https://www.trollhetta.com/?page_id=5 Trollhetta]
 == Evolution of Artificial Intelligence ==
 '''The History of AI'''<ref>The Historical Overview of Artificial Intelligence [https://builtin.com/artificial-intelligence Builtin]</ref><br />
 Intelligent robots and artificial beings first appeared in the ancient Greek myths of Antiquity. Aristotle's development of the syllogism and it's use of deductive reasoning was a key moment in mankind's quest to understand its own intelligence. While the roots are long and deep, the history of artificial intelligence as we think of it today spans less than a century. The following is a quick look at some of the most important events in AI.
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 == The Need for Artificial Intelligence ==
 '''Why Use Artificial Intelligence [[Software]]?'''<ref>Why Use Artificial Intelligence Software? [https://www.g2crowd.com/categories/artificial-intelligence G2Crowd]</ref><br />
 The reason someone would use AI software is to build an intelligent [[application]] from scratch or add machine or deep learning to a pre-existing software application. AI software allows users to implement general machine learning, or more specific deep learning capabilities, such as natural language processing, computer [[vision]], and speech recognition. While this is the primary, and somewhat obvious, reason, there are many motivations behind this rationale, with the following being some of the most common themes:
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 == The AI Technology Landscape ==
 '''What the AI technology lanscape looks like'''<ref>What does the AI technology lanscape look like ?[https://www.callaghaninnovation.govt.nz/sites/all/files/ai-whitepaper.pdf Callaghan Innovation]</ref><br />
 AI is computer systems that exhibit human like intelligence. It is a group of science fields and technologies concerned with creating
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 == The Importance of Artificial Intelligence ==
 '''Why is artificial intelligence important?'''<ref>Why is artificial intelligence important? [https://www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html SAS]</ref><br />
 *AI automates repetitive learning and discovery through data. But AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
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 == Artificial Intelligence Applications ==
 '''The Industrial Applications of Artificial Intelligences'''<ref>he Industrial Applications of Artificial Intelligences [https://www.engineersgarage.com/blogs/top-10-industrial-applications-artificial-intelligence Engineers Garage]</ref><br />
 Although AI is a branch of computer science, today there’s no field which is left unaffected by this technology. The aim is to teach the machines to think intelligently just the way humans do. Till now, the machines have been doing what they were told to do but with AI they will be able to think and behave like a human being. The study focuses on observing the thinking and learning a pattern of humans and then the outcome is used to develop intelligent softwares and system. Below is a glimpse of  some industrial applications of AI
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 == Artificial Intelligence and Employment ==
 '''The [[Impact]] of Artificial Intelligence on Jobs'''<ref>Technological unemployment is unfortunately a byproduct of progress [https://www.ubs.com/microsites/artificial-intelligence/en/ai-coming-age.html UBS]</ref><br />
 The increasing integration of AI will ultimately [[yield]] greater [[productivity]] in the near term, the result of which has historically led to culls in employment.
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 == The Future of Artificial Intelligence ==
 '''Seven stages in the future evolution of Artificial Intelligence'''<ref>Seven stages in the future evolution of Artificial Intelligence [https://www.em360tech.com/tech-news/tech-features/artificial-intelligence/ EM360]</ref><br />
 With literally hundreds of thousands of developers and data scientists across the planet now working on AI, the pace of development is accelerating, with increasingly eye catching breakthroughs being announced on a daily basis. This has also led to a lot of confusion about what we can do with AI today and what might be possible at some point in the future.
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 == Artificial Intelligence - Risks ==
 '''The potential harm from Artificial Intelligence'''<ref>The potential harm from Artificial Intelligence [https://en.wikipedia.org/wiki/Artificial_intelligence Wikipedia]</ref><br />
 Widespread use of artificial intelligence could have unintended consequences that are dangerous or undesirable. Scientists from the Future of Life Institute, among others, described some short-term research goals to see how AI influences the economy, the laws and ethics that are involved with AI and how to minimize AI security risks. In the long-term, the scientists have proposed to continue optimizing function while minimizing possible security risks that come along with new technologies.
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 [[Human Computer Interaction (HCI)]]<br />
 [[Human-Centered Design (HCD)]]<br />
 [[Machine-to-Machine (M2M)]]<br />
 [[Machine Learning]]<br />
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 == References ==
 <references/>

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 *AI achieves incredible accuracy through deep neural networks – which was previously impossible. For example, your interactions with Alexa, Google Search and Google Photos are all based on deep learning – and they keep getting more accurate the more we use them. In the medical field, AI techniques from deep learning, image classification and object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.
 *AI gets the most out of data. When algorithms are self-learning, the data itself can become intellectual property. The answers are in the data; you just have to apply AI to get them out. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win.
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 == See Also ==
+[[Artificial General Intelligence (AGI)]]<br />
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 *10 Powerful Examples Of Artificial Intelligence In Use Today [https://www.forbes.com/sites/robertadams/2017/01/10/10-powerful-examples-of-artificial-intelligence-in-use-today/#76f369bc420d Forbes]
 *Artificial Intelligence for the Real World [https://hbr.org/2018/01/artificial-intelligence-for-the-real-world HBR]

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 == Evolution of Artificial Intelligence ==
-'''The History of AI'''
+'''The History of AI'''<ref>The Historical Overview of Artificial Intelligence [https://builtin.com/artificial-intelligence Builtin]</ref><br />
 Intelligent robots and artificial beings first appeared in the ancient Greek myths of Antiquity. Aristotle's development of the syllogism and it's use of deductive reasoning was a key moment in mankind's quest to understand its own intelligence. While the roots are long and deep, the history of artificial intelligence as we think of it today spans less than a century. The following is a quick look at some of the most important events in AI.
 *1943: Warren McCullough and Walter Pitts publish "A Logical Calculus of Ideas Immanent in Nervous Activity." The paper proposed the first mathematic model for building a neural network.
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 *Decrease in demand for human labor: The relationship between automation and employment is complicated. While automation eliminates old jobs, it also creates new jobs through micro-economic and macro-economic effects. Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; The Economist states that "the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution" is "worth taking seriously". Subjective estimates of the risk vary widely; for example, Michael Osborne and Carl Benedikt Frey estimate 47% of U.S. jobs are at "high risk" of potential automation, while an OECD report classifies only 9% of U.S. jobs as "high risk". Jobs at extreme risk range from paralegals to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy.[343] Author Martin Ford and others go further and argue that a large number of jobs are routine, repetitive and (to an AI) predictable; Ford warns that these jobs may be automated in the next couple of decades, and that many of the new jobs may not be "accessible to people with average capability", even with retraining. Economists point out that in the past technology has tended to increase rather than reduce total employment, but acknowledge that "we're in uncharted territory" with AI.
 *Autonomous weapons: Currently, 50+ countries are researching battlefield robots, including the United States, China, Russia, and the United Kingdom. Many people concerned about risk from superintelligent AI also want to limit the use of artificial soldiers and drones.

← Older revision		Revision as of 16:21, 28 February 2019
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−	'''~~Content Coming Soon~~'''	+	Jeremy Achin, CEO of DataRobot, defines '''Artificial Intelligence (AI)''' as, " An AI is a computer system that is able to perform tasks that ordinarily require human intelligence. These artificial intelligence systems are powered by machine learning. Many of them are powered by machine learning, some of them are powered by specifically deep learning, some of them are powered by very boring things like just rules."<ref>Definition: What does Artificial Intelligence (AI) Mean? [https://www.datarobot.com/wiki/artificial-intelligence/]</ref>
		+
		+
		+
		+	== The Importance of Artificial Intelligence ==
		+
		+	'''Why is artificial intelligence important?'''<ref>Why is artificial intelligence important? [https://www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html SAS]</ref><br />
		+	*AI automates repetitive learning and discovery through data. But AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
		+	*AI adds intelligence to existing products. In most cases, AI will not be sold as an individual application. Rather, products you already use will be improved with AI capabilities, much like Siri was added as a feature to a new generation of Apple products. Automation, conversational platforms, bots and smart machines can be combined with large amounts of data to improve many technologies at home and in the workplace, from security intelligence to investment analysis.
		+	*AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that the algorithm acquires a skill: The algorithm becomes a classifier or a predictor. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data. Back propagation is an AI technique that allows the model to adjust, through training and added data, when the first answer is not quite right.
		+	*AI analyzes more and deeper data using neural networks that have many hidden layers. Building a fraud detection system with five hidden layers was almost impossible a few years ago. All that has changed with incredible computer power and big data. You need lots of data to train deep learning models because they learn directly from the data. The more data you can feed them, the more accurate they become.
		+	*AI achieves incredible accuracy through deep neural networks – which was previously impossible. For example, your interactions with Alexa, Google Search and Google Photos are all based on deep learning – and they keep getting more accurate the more we use them. In the medical field, AI techniques from deep learning, image classification and object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.
		+	*AI gets the most out of data. When algorithms are self-learning, the data itself can become intellectual property. The answers are in the data; you just have to apply AI to get them out. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win.