Sandeep Maheshwari is a name among millions who struggled, failed and surged ahead in search of success, happiness and contentment. Just like any middle class guy, he too had a bunch of unclear dreams and a blurred vision of his goals in life. All he had was an undying learning attitude to hold on to. Rowing through ups and downs, it was time that taught him the true meaning of his life.
By lay persons, however, the term is mostly used to mean AI applications, such as advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), and competing at the highest level in strategic game systems (such as chess and Go).[2]
Artificial intelligence was founded as an academic discipline in 1956, and in the years since it has experienced several waves of optimism,[3][4] followed by disappointment and the loss of funding (known as an "AI winter"),[5][6] followed by new approaches, success, and renewed funding.[4][7] AI research has tried and discarded many different approaches, including simulating the brain, modeling human problem solving, formal logic, large databases of knowledge, and imitating animal behavior. In the first decades of the 21st century, highly mathematical and statistical machine learning has dominated the field, and this technique has proved highly successful, helping to solve many challenging problems throughout industry and academia.[7][8]
The various sub-fields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects.[a] General intelligence (the ability to solve an arbitrary problem) is among the field's long-term goals.[9] To solve these problems, AI researchers have adapted and integrated a wide range of problem-solving techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability, and economics. AI also draws upon computer science, psychology, linguistics, philosophy, and many other fields.
The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it".[b] This raised philosophical arguments about the mind and the ethical consequences of creating artificial beings endowed with human-like intelligence; these issues have previously been explored by myth, fiction (science fiction), and philosophy since antiquity.[11] Computer scientists and philosophers have since suggested that AI may become an existential risk to humanity if its rational capacities are not steered towards goals beneficial to humankind.[c] Economists have frequently highlighted the risks of redundancies from AI, and speculated about unemployment if there is no adequate social policy for full employment.[12] The term artificial intelligence has also been criticized for overhyping AI's true technological capabilities.[13][14][15]
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