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A Brief History of Artificial Intelligence (AI) and the State of the Industry Today, Business and Industry Trends Analysis

The concept of artificial intelligence (often referred to as “AI”) continues to evolve, as scientists and software engineers gain a greater understanding of reasonably possible goals for this technology.  In 1956, John McCarthy may have been the first to use the phrase, describing artificial intelligence as “the science and engineering of making intelligent machines.”  This was a pretty dramatic statement, considering the barely advanced state of computers and robotics at the time.
In 1950, computer pioneer Alan Turing proposed, in a paper titled Computing Machinery and Intelligence, a test that could determine whether or not a machine could “think.”  Essentially, he suggested that, in a situation where a person asked the same questions of both a machine and a human being, if he couldn’t tell the difference between text answers coming from the machine and the human in blind results, then it might be reasonable to call the machine “intelligence.”  The Turing Test clearly avoids any discussion of what “consciousness” is.
Gary Marcus, a scientist at New York University, proposed another test, the Ikea Construction Challenge, to see whether or not a machine could assemble a piece of Ikea furniture when provided with a pile of parts and related instructions. 
Near the end of 2015, a group of well-known Silicon Valley investors, including Elon Musk and Peter Thiel, announced a long-term commitment to raise funds of as much a $1 billion for a new organization to be known as OpenAI,   OpenAI is a nonprofit group, dedicated to moving AI ahead to the point that it “will benefit humanity.”
Another well-funded AI organization is the Allen Institute for Artificial Intelligence (AI2).  Located in Seattle, the group was co-founded by Paul Allen, one of the co-founders of Microsoft, and scientist Oren Etzioni.  AI2 has developed its own complex test for artificial intelligence called a GeoSolver.
The rapid growth of cloud computing at reasonable cost has been among the biggest accelerators to the development of AI.  The extension of the internet of things (IoT) will likewise boost AI.  However, one of the most interesting boosters has been the advent of an open-source software coding language known as Python.  Hundreds of thousands of pre-written parcels of code are available to Python developers via a simple online portal known as the “CheeseShop.”  Among them are a large number of code packs that enable users to rapidly create neural networks and other AI tools with limited effort.
Massive investments in research, development and applications of AI and machine learning are being made by government and industry on a global scale.  Global spending on AI on a broad basis, including software, hardware and services, has been estimated for 2021 at $341.8  billion by analysts at IDC.  This amount could triple by 2022.  For example, in 2018 Samsung announced it would invest more than $22 billion over the following three years in development of advanced technologies, including AI.  It planned to create a staff of at least 1,000 researchers and engineers dedicated to artificial intelligence by 2020.
Elsewhere, the semiconductor industry is especially focused on creating advanced chips capable of delivering on the full potential of AI.  An ever-accelerating amount of data to be filtered and analyzed via machine learning and AI will require ever more powerful chips that can operate at blinding speed. Leading chip makers are in a race to create the industry’s best semiconductors for AI computing.  (Consider, for example, the processing power required to learn from the billions of internet searches conducted by business and consumers daily, or to analyze the billions of photos and comments posted to social media and other web sites each month.)  Nvidia is considered to be the leading maker of high-powered chips for AI, with its competitors trying hard to keep pace.  Other companies, such as startup Run:AI are developing software that will help AI chips run more efficiently.
Today, a serious battle is in place between the United States and China for long-term dominance of the AI sector.  While the U.S. has long made the highest total investments in AI research, China, in July 2017, announced that it wants to grow the output of its AI-based industries to 10 trillion yuan (about $1.5 trillion in U.S. currency) by 2030.  Firms based in China with very significant and growing reliance on AI include Alibaba, Baidu, Tencent, Huawei and iFlyTek, along with specialty firms Megvii and SenseTime that have superb capabilities in applying AI to facial recognition.  In 2020, AI proved its use in rapid development of Coronavirus vaccines and in tracking the disease.

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