Scope and Future Expectations of Artificial Intelligence

 Artificial Intelligence Definition

The simple definition of Artificial Intelligence (AI) is the concept of machine intelligence. Hierarchical Temporal Memory (HTM) is a potential future of AI, developed by Jeff Hawkins and Dileep George of Numenta, Inc.

HTM is based on the core concept of hierarchical knowing, which is the observation that the human brain's neocortex, the top layer of gray matter, is responsible for higher-level insights and calculations. HTM programming mimics the human brain's ability to learn from experience and create memories from sensory input to make predictions about the future. This model is hierarchical in structure, just like human brains and society. HTM-based AI has shown incredible speed improvements and does not suffer from becoming "dumber" with too many examples.

Artificial Intelligence future

Hawkins' UC Berkeley Ph.D. studies gave rise to a crucial insight that could shape the potential future of artificial intelligence. During a "Eureka" moment, he contemplated the sudden appearance of a blue coffee cup on his desk, leading him to a significant realization. This insight may hold the key to the scope and future expectations of artificial intelligence.

artificial intelligence development

The future development of artificial intelligence could hinge on Hawkins' insight, which suggests that all previous models and theories failed because they overlooked the essential truth that the human brain's ability is primarily founded on predicting both the near and distant future. As a result, they eventually collapsed or reached insurmountable obstacles.

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According to Hawkins, the downfall of past artificial intelligence models and theories stemmed from their failure to recognize the fundamental principle that the human brain's capability is rooted in predicting the future. As a solution, Hawkins and George are developing a software platform that emulates the human brain's innate nature of starting with a clean slate at birth. Although similar to humans, this artificial intelligence will possess instincts, which are pre-programmed protocols to facilitate learning.

 Scope and Future Expectations of Artificial Intelligence

HTM is predicted to be the next phase of artificial intelligence because it requires an A.I. to generate memories from sensory input, learn from past encounters, and utilize those processed experiences to forecast future events. This approach delves into the fundamental aspect of object recognition, where humans excel at identifying objects from partial, obscured, or distorted sensory data, a skill that the world's top chess computer program would be unable to accomplish.

Future hopes for artificial intelligence are extremely high. An artificial intelligence (A.I.) would begin its learning process from scratch, with a clean slate, and slowly amass experiences through which it would evolve and mature.

The foundation of HTM programming lies in the fundamental concept of hierarchical knowledge. This principle derives from the observation that the human brain's neocortex, which forms the top layer of the three layers of gray matter, accounts for over 60% of the brain's mass. The neocortex is where most higher-level cognitive processes and realizations, including Hawkins' personal breakthrough concerning the fundamental structure of human intelligence, occur. Interestingly, humans have the largest neocortex, by far, compared to any other mammal on Earth.


Artificial intelligence's future development will be constructed on an ancient model - the pyramid. Hawkins proposes that A.I. "neurons" are structured hierarchically, similar to the organization of neurons in the human brain, supported by ample neurological research. The lower-level neurons of the A.I. work like those that receive primary sensory input, such as sounds from a musical instrument. These tones are first picked up by the ear and interpreted by the lower-level neurons, which process the information and pass it on to the mid-level neurons. The mid-level neurons then perform further processing and send the information to the top-level neurons.

Also, See Introduction to Artificial Intelligence |What is AI | Deep Learning

After the top-level neurons receive the processed information, they perform the ultimate processing and send signals back down to the low-level neurons, teaching them like a more experienced guide or mentor. As with human intelligence, there are fewer high-level neurons than mid-level or low-level neurons. The future of artificial intelligence will, therefore, be hierarchically structured, just like human brains and human society.

"The future of artificial intelligence is hierarchical in structure, just like human brains, just like human society."

George spent several weekends constructing the original A.I. model for the human visual cortex, which became the foundation for Numenta's Hierarchical Temporal Memory (HTM) technology. Unlike traditional linear programming, George's model consisted of multiple parallel layers of nodes, each containing thousands of neurons in cortical columns, with each node functioning as a tiny computer program capable of processing information, pattern recognition, and prediction.

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Numenta has since collaborated with Edsa Micro, resulting in significant speed improvements for HTM-based A.I. Adib Nasle, Edsa's president, commented on the impressive nature of HTM's ability to avoid diminishing returns when given too many examples.

applications of artificial intelligence.

Numerous businesses and fields use artificial intelligence (AI), which has many uses. Here are some illustrations:

In the manufacturing industry, AI is utilized in predictive maintenance to detect probable equipment faults before they happen, minimizing downtime and maintenance costs. It is also used in quality control to find product flaws.

Education: AI is utilized in adaptive learning systems, which tailor instruction to each student's needs and speed. Chatbots that can respond to inquiries from students and give constructive criticism for their work, it is also utilized.

These are just a handful of the various uses for artificial intelligence. The potential applications of AI technology will probably increase as it advances and develops.

artificial intelligence future in Pakistan

As of right now, Pakistan's artificial intelligence market is still in its infancy due to low levels of government funding and a lack of qualified workers. However, interest in AI and its potential applications in a range of industries, including healthcare, agriculture, and finance, is growing. With programs like the National Centre for Artificial Intelligence and the formation of AI research labs in universities, the public and business sectors are promoting AI research and development. Pakistan's AI industry appears to have a bright future, with room for expansion and innovation across a range of industries.

artificial intelligence future trends

Hierarchical knowledge is the fundamental tenet of HTM programming. This useful knowledge is derived from the finding that the neocortex, the top layer of the human brain's three layers of grey matter, accounts for at least 60% of the entire brain on its own. The neocortex is where almost all higher-level discoveries and computations, like Hawkins' own discovery regarding the fundamental makeup of human intellect, are made. Fun fact: The neocortex of humans is by far the largest and makes up the highest percentage of any mammal on the planet.

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