Artificial intelligence [AI]

The intelligence of computers or software, as opposed to the intellect of people or animals, is known as artificial intelligence (AI). It is a branch of computer science that focuses on creating and researching intelligent machines. These devices could be referred to as AIs.

Artificial Intelligence is widely applied in government, industry, and academia. Advanced online search engines (like Google Search), recommendation engines (like YouTube, Amazon, and Netflix), speech recognition (like Google Assistant, Siri, and Alexa), self-driving cars (like Waymo), generative and artistic tools (like ChatGPT and AI art), and superhuman play and analysis in strategy games (like chess and Go) are a few high-profile applications.

The many subfields of AI study are focused on specific objectives and the use of certain instruments. Reasoning, knowledge representation, planning, learning, natural language processing, perception, and robotics support are among the traditional objectives of AI study.[A] One of the long-term objectives of the field is general intelligence, or the capacity to accomplish any activity that a human can.

Artificial intelligence (AI) researchers have employed a variety of problem-solving strategies, including as formal logic, artificial neural networks, search and mathematical optimization, and approaches from the fields of statistics, operations research, and economics, to address these issues. AI also incorporates ideas from philosophy, neuroscience, linguistics, psychology, and other disciplines.

intelligence" was Alan Turing.The academic field of artificial intelligence was established in 1956.There were several cycles of optimism in the field, which were followed by disappointment and funding losses with deep learning outperformed all prior AI techniques in 2012 and with the transformer architecture in 2017, funding and interest skyrocketed. As a result, the AI spring of the 2020s saw a large number of American businesses, academic institutions, and labs spearheading important advancements in artificial intelligence.

Objectives There are several smaller issues within the larger issue of mimicking (or producing) intelligence. These are specific attributes or skills that scientists anticipate an intelligent system to have. The characteristics listed below have drawn the most interest and include the range of AI study.

Reasoning and resolving issues Early scientists created algorithms that mimicked the methodical thinking that people employ to solve riddles and arrive at logical conclusions. By the late 1980s and early 1990s, techniques for handling ambiguous or partial data had been created, utilizing ideas from economics and probability.

A "combinatorial explosion" occurred in many of these algorithms, meaning that as the issues got bigger, they became exponentially slower, making them unsuitable for handling huge reasoning problems. The systematic inference that early AI research employed is hardly ever used by humans.

Knowledge illustration A knowledge base is a collection of information arranged in a way that a software may use it. A domain of knowledge's objects, relations, concepts, and attributes make up its ontology. Objects, their properties, categories, and relationships between them circumstances, events, states, and time causes and effects knowledge about knowledge (i.e., what we know about what other people know) default reasoning (i.e., beliefs that people hold to be true until proven false) and numerous other facets and fields of knowledge that need to be represented. The breadth of commonsense knowledge (the vast body of atomic facts that the average person knows) and the sub-symbolic form of most commonsense knowledge (a large portion of what people know is not represented as "facts" or "statements" that they could express verbally) are two of the most challenging issues in knowledge representation.The challenge of acquiring knowledge and the issue of doing so for AI applications are more issues.

Social acumen Kismet is a robot head that was created in the 1990s that has the ability to identify and mimic various emotions. Under the multidisciplinary heading of "affective computing," systems that can detect, decipher, process, or replicate human feeling, emotion, and mood are included. Certain virtual assistants, for instance, are designed to converse or even joke around; this gives the impression that they are more perceptive of the emotional dynamics of human-computer contact or that they are more sensitive to human emotions. But this often results in unsuspecting people having an inflated idea of how intelligent current computer agents are. Textual sentiment analysis and, more recently, multimodal sentiment analysis—in which artificial intelligence (AI) categorizes the affects exhibited by a recorded subject—are two moderately successful applications of affective computing.

Tasks Particular to a Certain Industry Additionally, dozens of effective AI applications are employed by particular organizations or businesses to address particular issues. One in five businesses said in a 2017 survey that they had included "AI" into part of their products or procedures. Applications that forecast court rulings, energy storage, supply chain management, medical diagnostics, military logistics, and foreign policy are a few examples.

Artificial intelligence (AI) has aided farmers in identifying regions that require fertilizer, irrigation, pesticide treatments, or higher yielding crops. AI is used by agronomists for research and development. AI has been applied to a variety of tasks, including predicting when crops like tomatoes will ripen, tracking soil moisture, controlling agricultural robots, performing predictive analytics, categorizing cattle emotions based on their calls, automating greenhouses, spotting pests and illnesses, and conserving water.

Astronomers are employing artificial intelligence to analyze the growing amount of data and applications available, primarily for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" such as finding exoplanets, predicting solar activity, and differentiating between signals and instrumental effects in gravitational wave astronomy. Additionally, it could be applied to space exploration tasks like data processing from space missions, real-time science decision-making for spacecraft, avoiding space junk, and more autonomous operation.

upcoming The singularity and superintelligence A superintelligence is an imaginary being with intelligence much above that of the most brilliant and talented human mind. Artificial general intelligence research could potentially develop software that is intelligent enough to be able to self-improve and reprogramme. With enhanced software, there would be a "singularity" or "intelligence explosion" as described by Vernor Vinge and I. J. Good, since the program would be much more adept at developing itself.

But technological advancements are finite and usually follow an S-shaped curve, slowing down as they approach the physical boundaries of their capabilities. The Transhumanist Movement Cyberneticist Kevin Warwick, inventor Ray Kurzweil, and robot designer Hans Moravec have all prophesied that in the future, humans and robots will combine to create more powerful cyborgs and more potent than both. Transhumanism is a concept that originated with Aldous Huxley and Robert Ettinger.

Edward Fredkin makes the claim that "artificial intelligence is the next stage in evolution," a claim that was initially made in Samuel Butler's 1863 work "Darwin among the Machines" and further developed by George Dyson in his 1998 book of the same name.