Predicting the Trajectory of AI Utilizing the Markov Model of Machine Learning

The next generation of Artificial Superintelligence (ASI) poses a variety of important societal problems, including the possible crises and upheavals of the AI machine, which could cause fundamental changes. As the discussion around Artificial Superintelligence underscores the importance of continual dialogue between man and its ability to control technology, it also raises the problem of designing intelligent interactive and collaborative tools and systems to allow this dialogue. Historically, the term “AI” was used from 1950 to 1975, then fell out of favor during the” AI winter” from 1975 to 1995, and was narrowed to ANI (Artificial Narrow Intelligence). As a result, terms like “Machine Learning,” “Natural language Processing,” and “Data Science” were frequently mislabelled as AI. Today, AI has allowed clinicians to rely heavily on ML which is highly integrated with coding, billing, medical records, scheduling, contracting, medication ordering, and administrative functions. AI is now a thriving industry with massive capital investments and once again is on the verge of a great revolution. There are compelling reasons to investigate artificial super intelligence. This type of AI is capable of surpassing human intellect by expressing cognitive skills and developing its own mental capabilities. ASI is a highly sophisticated, and intelligent type of AI that goes beyond normal intellectual capacity. This paper will discuss the societal impact and the current academic impact of ASI. Finally, this study would attempt to utilize the Markov Decision Model of Machine Learning to predict the trajectory of ASI in the very near future.