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Artificial Intelligence (AI), Deep Learning and Machine Learning Advance into Commercial Applications, Including Health Care and Robotics, Business and Industry Trends Analysis

While the practical definition and ultimate capabilities of AI are debated, industry has put AI to work and continues to invest very heavily in advanced development.  Today, AI has synergies with many highly advanced technologies such as virtual reality, factory automation, robotics, self-driving cars, speech recognition and predictive analytics.
The most compelling opportunities for the development and use of artificial intelligence software may be in engineering/research, investment analysis and, especially, health care.  Simply put, health care is one of the world’s largest and fastest-growing industries, and virtually all of the government and private health initiatives that pay for health care are desperately seeking ways to improve patient care outcomes, cut billing fraud, create operating efficiencies and generally slow the growth of costs overall.
Google and U.S. hospital chain HCA Healthcare, Inc. signed a deal in May 2021 to develop algorithms that will analyze data from digital health care records for 32 million patients.  The goal is to improve operating efficiency and promote better medical efficacy.  The technology may boost patient monitoring and assist medical personnel in making treatment decisions.  Google also signed a similar deal with the Mayo Clinic
IBM created a business unit called Watson Health, based on its advanced “Watson” supercomputing-artificial intelligence hardware/software technology, combined with massive health care database firms that it acquired.  In early 2016, IBM announced the acquisition of Truven Health Analytics, Inc. for $2.6 billion, for the Watson Health unit.  In early 2022, IBM agreed to sell some of its Watson Health unit data and analytics to private equity firm Francisco Partners for more than $1 billion. Technology firms have found that AI faces multiple challenges in analyzing complicated medical conditions in a manner that can improve treatments and outcomes.
By some estimates, the amount of digital health care data doubles every 60 days.  One of the first commercial applications of AI to medical equipment to be approved by the FDA was the Acumen Hypotension Prediction Index.  This system utilizes machine learning to alert doctors in real time to the probability that a patient’s blood pressure might plummet.  It is applicable to patients in life-threatening situations, such as those that doctors are attempting to stabilize after surgery or a trauma.  Likewise, AI has tremendous promise for enhancing the ability of ambulance and emergency room personnel to instantly diagnose patient conditions and suggest the best possible treatment—even before the patient arrives at the hospital.
In R&D, one of the most promising uses for AI lies in identifying and testing chemical compounds that have potential to become new drug therapies—possibly cutting years and millions of dollars from the process.  All major drug companies, including Astra Zeneca, are investing in their AI capabilities in the lab.
Elsewhere, demand is growing for advanced data tools in factories in order to monitor operations and equipment performance.  This will increase efficiency and speed as well as reduce waste.  According to some analysts, global manufacturers are expected to increase spending on data management and analytics to as much as $20 billion by 2026, up from approximately $5 billion in 2020.
However, a significant portion of the investment in systems that gather and analyze data needs to focus on cybersecurity.  Data gathering via sensors, customer/patient records, webcams and monitors is an invitation for hackers to attempt to use such devices and records as ways to hack into networks for ransomware or data theft.  Connected devices at homes and government/commercial facilities (including everything from webcams to digital door locks to smart thermostats) are extremely susceptible to easy hacking, unless they are properly installed with strong passwords and protected by firewalls or similar authentication systems.

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