1. Reactive Machines - These are the oldest forms of AI systems that have extremely limited capability. They emulate the human mind’s ability to respond to different kinds of stimuli. These machines do not have memory-based functionality. This means such machines cannot use previously gained experiences to inform their present actions, i.e., these machines do not have the ability to “learn.” These machines could only be used for automatically responding to a limited set or combination of inputs. They cannot be used to rely on memory to improve their operations based on the same. A popular example of a reactive AI machine is IBM’s Deep Blue, a machine that beat chess Grandmaster Garry Kasparov in 1997.
  2. Limited Memory - Limited memory machines are machines that, in addition to having the capabilities of purely reactive machines, are also capable of learning from historical data to make decisions. Nearly all existing applications that we know of come under this category of AI. All present-day AI systems, such as those using deep learning, are trained by large volumes of training data that they store in their memory to form a reference model for solving future problems. For instance, an image recognition AI is trained using thousands of pictures and their labels to teach it to name objects it scans. When an image is scanned by such an AI, it uses the training images as references to understand the contents of the image presented to it, and based on its “learning experience” it labels new images with increasing accuracy.  Almost all present-day AI applications, from chatbots and virtual assistants to self-driving vehicles are all driven by limited memory AI.
  3. Theory of Mind - While the previous two types of AI have been and are found in abundance, the next two types of AI exist, for now, either as a concept or a work in progress. Theory of mind AI is the next level of AI systems that researchers are currently engaged in innovating. A theory of mind level AI will be able to better understand the entities it is interacting with by discerning their needs, emotions, beliefs, and thought processes. While artificial emotional intelligence is already a budding industry and an area of interest for leading AI researchers, achieving Theory of mind level of AI will require development in other branches of AI as well. This is because to truly understand human needs, AI machines will have to perceive humans as individuals whose minds can be shaped by multiple factors, essentially “understanding” humans.
  4. Self-aware (Sentience) - This is the final stage of AI development which currently exists only hypothetically. Self-aware AI, which, self explanatorily, is an AI that has evolved to be so akin to the human brain that it has developed self-awareness. Creating this type of Ai, which is decades, if not centuries away from materializing, is and will always be the ultimate objective of all AI research. This type of AI will not only be able to understand and evoke emotions in those it interacts with, but also have emotions, needs, beliefs, and potentially desires of its own. And this is the type of AI that doomsayers of the technology are wary of. Although the development of self-aware can potentially boost our progress as a civilization by leaps and bounds, it can also potentially lead to catastrophe. This is because once self-aware, the AI would be capable of having ideas like self-preservation which may directly or indirectly spell the end for humanity, as such an entity could easily outmaneuver the intellect of any human being and plot elaborate schemes to take over humanity.  The alternate system of classification that is more generally used in tech parlance is the classification of the technology into Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI).
  5. Artificial Narrow Intelligence (ANI) - This type of artificial intelligence represents all the existing AI, including even the most complicated and capable AI that has ever been created to date. Artificial narrow intelligence refers to AI systems that can only perform a specific task autonomously using human-like capabilities. These machines can do nothing more than what they are programmed to do, and thus have a very limited or narrow range of competencies. According to the aforementioned system of classification, these systems correspond to all the reactive and limited memory AI. Even the most complex AI that uses machine learning and deep learning to teach itself falls under ANI. 
    Examples of narrow AI include:
    • Rankbrain by Google / Google Search.
    • Siri by Apple, Alexa by Amazon, Cortana by Microsoft and other virtual assistants.
    • IBM's Watson.
    • Image / facial recognition software.
    • Disease mapping and prediction tools.
    • Manufacturing and drone robots.
  6. Artificial General Intelligence (AGI) - Artificial General Intelligence is the ability of an AI agent to learn, perceive, understand, and function completely like a human being. These systems will be able to independently build multiple competencies and form connections and generalizations across domains, massively cutting down on time needed for training. This will make AI systems just as capable as humans by replicating our multi-functional capabilities.
    Examples of AGI include the following:
    • customer service chatbots;
    • voice assistants like Siri and Alexa;
    • recommendation engines such as those Google, Netflix and Spotify use;
    • marketing platforms used to gather business intelligence and customer sentiment; and.
    • facial recognition applications.
  7. Artificial Superintelligence (ASI) - The development of Artificial Superintelligence will probably mark the pinnacle of AI research, as AGI will become by far the most capable forms of intelligence on earth. ASI, in addition to replicating the multi-faceted intelligence of human beings, will be exceedingly better at everything they do because of overwhelmingly greater memory, faster data processing and analysis, and decision-making capabilities. The development of AGI and ASI will lead to a scenario most popularly referred to as the singularity. And while the potential of having such powerful machines at our disposal seems appealing, these machines may also threaten our existence or at the very least, our way of life.

At this point, it is hard to picture the state of our world when more advanced types of AI come into being. However, it is clear that there is a long way to get there as the current state of AI development compared to where it is projected to go is still in its rudimentary stage. For those holding a negative outlook for the future of AI, this means that now is a little too soon to be worrying about the singularity, and there's still time to ensure AI safety. And for those who are optimistic about the future of AI, the fact that we've merely scratched the surface of AI development makes the future even more exciting.

Size of the Global Artificial Intelligence Market

The worldwide Artificial Intelligence Market hit USD 328.34 billion in 2021. The market valuation is slated to increase from USD 387.45 billion in 2022 to USD 1,394.30 billion by 2029, expanding a 20.1% CAGR during the forecast duration. The market is expected to garner momentum in the next several years, driven by growing investment in AI technology by enterprises of all sizes across industries. The technology is being rapidly integrated into corporate processes across the world to accelerate business operations and improve customer experience. Future developments in AI will be influenced by rise of automation, cloud computing, 5G, and expanding databases, says Fortune Business Insights™, in its report titled “Artificial Intelligence (AI) Market, 2022-2029."

Top AI Statistics

  1. As of 2022, the global AI market is valued at over $136.6 billion.
  2. The worldwide artificial intelligence (AI) market valuation is slated to increase from USD 387.45 billion in 2022 to USD 1,394.30 billion by 2029, expanding at a CAGR of 20.1% during the forecast duration (2022-2029).
  3. AI industry value is projected to increase by over 13x over the next 8 years.
  4. The US AI market was $143.49 billion in 2021 and forecast to hit $299.64 billion by 2026.
  5. The AI market is expanding at a CAGR of 38.1% between 2022 to 2030.
  6. By 2025, as many as 97 million people will work in the AI space.
  7. AI market size is expected to grow by at least 120% year-over-year.
  8. 83% of companies claim that AI is a top priority in their business plans.
  9. Netflix makes $1 billion annually from automated personalized recommendations.
  10. 48% of businesses use some form of AI to utilize big data effectively.
  11. 38% of medical providers use computers as part of their diagnosis.

COMMENTARY:   A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. "Superintelligence" may also refer to a property of problem-solving systems (e.g., superintelligent language translators or engineering assistants) whether or not these high-level intellectual competencies are embodied in agents that act in the world. A superintelligence may or may not be created by an intelligence explosion and associated with a technological singularity.

University of Oxford philosopher Nick Bostrom defines superintelligence as "any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest".  The program Fritz falls short of superintelligence—even though it is much better than humans at chess—because Fritz cannot outperform humans in other tasks.  Following Hutter and Legg, Bostrom treats superintel-ligence as general dominance at goal-oriented behavior, leaving open whether an artificial or human superintelligence would possess capacities such as intentionality (cf. the Chinese room argument) or first-person consciousness (cf. the hard problem of consciousness).

Technological researchers disagree about how likely present-day human intelligence is to be surpassed. Some argue that advances in artificial intelligence (AI) will probably result in general reasoning systems that lack human cognitive limitations. Others believe that humans will evolve or directly modify their biology so as to achieve radically greater intelligence.   A number of futures studies scenarios combine elements from both of these possibilities, suggesting that humans are likely to interface with computers, or upload their minds to computers, in a way that enables substantial intelligence amplification.

Some researchers believe that superintelligence will likely follow shortly after the development of artificial general intelligence. The first generally intelligent machines are likely to immediately hold an enormous advantage in at least some forms of mental capability, including the capacity of perfect recall, a vastly superior knowledge base, and the ability to multitask in ways not possible to biological entities. This may give them the opportunity to—either as a single being or as a new species—become much more powerful than humans, and to displace them.

A number of scientists and forecasters argue for prioritizing early research into the possible benefits and risks of human and machine cognitive enhancement, because of the potential social impact of such technologies.

Courtesy of an article dated July 19, 2019 appearing in Forbes and an article appearing in Wikipedia and an article dated August 4, 2022 appearing in Exploding Topics and an article dated June 9, 2022 appearing in Fortune Business Insights