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

AI and related ML (machine learning) are already having a very significant impact on everyday life.  Much of this AI use is running in the background, determining the risk in insurance policy applications, checking for fraud when consumers login to payment platforms and ecommerce sites, powering smart chatbots on websites, and enabling transportation systems and manufacturing plants to operate more efficiently.
While most of its uses are relatively new, AI research has been conducted for many decades.  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.
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 for a new nonprofit organization to be known as OpenAI,  OpenAI is dedicated to moving AI ahead to the point that it “will benefit humanity.”
In 2023, OpenAI created a for-profit partnership as a separate entity, accepting a substantial investment from Microsoft.  Importantly, it has launched leading-edge AI interfaces, including ChatGPT, that are easy to use in the automated creation of text (such as magazine articles), art (such as illustrations for websites), music and even complex computer code.  While these AI tools produce very impressive results, they remain a work in progress, with continuing refinement needed.  Meanwhile, the use of AI tools such as these that learn from the works of millions of human producers (machine learning), and then create new text, art, etc., will lead to significant debate as to copyrights, fair use and other aspects of ownership.

In early 2023, Microsoft announced that it is investing $10 billion in AI research pioneer OpenAI, which was founded as a nonprofit organization, but later established a for-profit partnership that can commercialize on certain AI projects.  The deal values the for-profit side of OpenAI at $29 billion.  According to reports at the time of investment, Microsoft will receive a 75% share of OpenAI’s profits until it has received a complete return of its money, and then will own a 49% stake in the business unit.  The types of advanced research and development that OpenAI is conducting requires deep funding.  It also requires access to massive computing power, which Microsoft can provide via its Azure cloud computing platform.
Microsoft stated that it will increase its investments in its supercomputing systems in order to accelerate OpenAI’s research.  In addition, Microsoft has big plans to make AI an integral part of its major product lines, stating that it will “…deploy OpenAI’s models across our consumer and enterprise products and introduce new categories of digital experiences built on OpenAI’s technology.”  Strategies include Microsoft’s Azure OpenAI Service, which enables software developers to utilize cloud computing connected to OpenAI models to build advanced products and services that are AI-driven.  Microsoft also vastly enhanced its Edge/Bing search tools by integrating Chat/AI.

     A well-funded nonprofit 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 has been estimated for 2023 at $154 billion by analysts at IDC.  This amount is expected to reach $300 billion by 2026.
Microsoft is investing billions of dollars in its own AI capabilities in addition to its major commitments to OpenAI (owner of ChatGPT).  Microsoft (with its Azure unit) and Amazon (with its highly profitable AWS unit) continue to rapidly build their cloud computing capabilities and revenues, with a focus on serving the booming needs of AI-using enterprises.

SPOTLIGHT: Google’s Outstanding Offering of AI Tools and Services Make New Products Easy for Customers to Launch
Google is investing billions of dollars in AI, not only in developing its own in-house capabilities and services, but also in startups such as Anthropic with promising technologies of their own.  Google’s outside investments include major positions in companies like AI chatbot Character.AI.  Google is aggressively marketing and enhancing its own AI software and cloud offerings—tools that make it fast and relatively easy for nearly any enterprise to launch sophisticated AI-based initiatives.  It is providing superb support for potential users and is investing substantial efforts in providing free education and training for AI customers.  Google’s AI tools include:
=         Vertex AI, a unified data and AI platform that provides ready-to-use ML models as well as tools and infrastructure.
=         AutoML, which enables users to train custom ML models with minimal effort and expertise.
=         Natural Language AI, which analyzes unstructured data such as conversations with customers in email messages, social media, and chat sessions.
=         Translation AI, which translates content in apps, webpages and documents into the languages that an enterprise’s customers speak. 
=         Vision AI, which enables users to build, deploy, and manage computer vision applications that automatically analyze videos and images for object detection and classification.

     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.

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