Artificial Intelligence Stocks List

Artificial Intelligence Stocks Recent News

Date Stock Title
May 20 IQ iQIYI shares rise after announce of new content release
May 20 CYN Cyngn to Present at the H.C. Wainwright Global Investment Conference
May 20 IQ Is iQIYI, Inc. (NASDAQ:IQ) Trading At A 44% Discount?
May 20 IQ iQIYI Releases 213 New Titles, Providing Users with Inspirational Content
May 19 BBAI BigBear.ai Names Former Intelligence Officer Tony Barrett as President of Cyber and Engineering Division
May 19 IQ iQIYI's IP Universe Further Showcases China's Cultural Heritage to Global Audience with the Worldwide Premiere of "Wind Blows from Longxi"
May 19 J Jacobs chosen by TEPCO to support fukushima clean-up
May 19 J Jacobs Selected by TEPCO to Support Fukushima Clean-up
May 18 ROBO Best AI ETFs for Q3 2022
May 18 AGRI AgriFORCE Completes Acquisition Of Intellectual Property From Manna Nutritional
May 18 AGRI AgriFORCE Growing Systems Completes Acquisition of Food Production & Processing IP from Manna Nutritional Group (MNG)
May 18 CYN Cyngn Publishes White Paper Highlighting the Case for Autonomous Industrial Vehicles in the Future of Manufacturing
May 18 BBAI BigBear.ai Announces Date of 2022 Annual Meeting of Stockholders
May 18 J Jacobs renews maintenance services contract for Hartsfield-Jackson Atlanta airport
May 18 J Jacobs Awarded Contract Renewal with Atlanta Airlines Terminal Company
May 17 LIDR AEye is called a winner in the LiDAR sector by Guggenheim
May 17 AGRI AgriFORCE Growing Systems GAAP EPS of -$0.22 misses by $0.03
May 16 IQ IQIYI stock soars after J.P. Morgan swings to bullish from bearish, quadruples price target
May 16 AGRI 36 of the Best Ideas Companies to Present at the Spring into Action - Best Ideas Investor Conference on May 16th - 20th, 2022
May 16 LIDR AEye, Inc. 2022 Q1 - Results - Earnings Call Presentation

In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. More in detail, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet." For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations.
Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems: analytical, human-inspired, and humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an "AI winter"), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"), the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences. Subfields have also been based on social factors (particular institutions or the work of particular researchers).The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many others.
The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it". This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.

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