Artificial intelligence is a multidisciplinary field dealing with making humans as intelligent as possible by hot computers or machines. It is used to manipulate human cognitive functions. This theoretical discovery of artificial intelligence is known as “Artificial General Intelligence”.It is already being used in almost every industry.
A contributing factor to the growth and importance of AI over the past decade has been the results of big dummy data. The importance of search engines, social media, e-commerce, the Internet of Things, and online business analytics data is immense.
The Internet has made data available from anywhere in real-time to humans practically when computers lack human-like cognitive functions to process data independently. It is an alternative to imbuing computers with human-like intelligence that learns from data rather than relying on explicit programming.
AI is evolving and already expanding in the form of machine learning and deep learning. Machine learning is discovering more new discoveries by identifying data patterns and correlations between data and results. Deep learning focuses on representing artificial intelligence from data. Machine learning Deep learning is the source of current artificial intelligence.
Artificial Intelligence can be better cleared by categorizing the evolution and application of artificial intelligence. Classification of artificial intelligence is evolving based on its capabilities. There are three types of power.
⦁ Narrow AI (Weak AI)
⦁ General AI (Strong AI)
⦁ Super AI
Classification of AI identifies its technological application based on functionality. Arend Hintze, assistant professor of integrative biology and computer science at Michigan State University, gave this classification in an article in early 2016. Based on the task, four types of artificial intelligence are divided.
⦁ Reactive machines
⦁ Limited memory
⦁ Theory of mind
Let’s know about different types of artificial intelligence jobs.
A.Narrow AI/Weak AI:
Narrow AI, also known as “very weak AI”, is the most widespread and successful form of artificial intelligence. Narrow AI simulates human intelligence for a single specific task within a limited context. It has the ability to implement only a single subset of cognitive abilities to excel at a specific function. While the same subset may not be useful for other tasks, some examples of narrow AI include virtual personal assistants such as Siri, Alexa,
Image recognition programs, self-driving cars, IBM Watson, Google’s page ranking algorithm, Google Translate, recommendation engines, chatbots, and spam filtering are used in such work.
B.General AI/Strong AI:
General AI, also known as relatively strong AI or artificial general intelligence, is a term for implementing a full set of cognitive abilities that are not limited to the ability to apply human-level intelligence to any task. It relies on creating a universal algorithm for learning and acting in any environment. Researchers have yet to achieve powerful AI. In theory, a strong AI program must be lab tested with the Turing Test and the Chinese Room.
For example computer vision, natural language processing, fuzzy logic, robotics, machine learning, and deep learning. A human brain can perform a billion calculations per second while a supercomputer takes 40 minutes to perform the same number of calculations. .so strong AI doesn’t seem possible anytime soon.
Super AI refers to artificial intelligence at a higher level than human-level intelligence. It allows machines to plan and solve problems that can learn and reason better than humans.
Let us now discuss different types of artificial intelligence based on regular functions.
1. Reactive machines: A responsive machine is the first step in artificial intelligence. It has no memory to store past experiences. Therefore, it uses real-time data only. It receives data and gives feedback to perform a specific task. This type of artificial intelligence has very little power and works according to algorithms. The same algorithm will not apply even similar tasks elsewhere. A popular example of this reactive machine is IBM’s Deep Blue. Deep Blue is a chess-like supercomputer.
It looks at the current chess board and relies on its algorithm to determine the next possible moves and its opponent. Since it uses no memory, Et Tai cannot learn or improve from its past experiences. What it does is react to the current game and depend on the most favorable moves.
One example of a responsive machine is Google’s Alpha Go. It is a more sophisticated AI because it has neural networks to evaluate the game.
2. Limited memory: His artificial intelligence has a short-term memory system. It operates according to what it can learn from the immediate past experience of mastering a particular task. These machines have a static memory that applies to their work. They also have a dynamic memory where they retain only immediate past experiences. Interact with short-term memory by understanding a representation of the surrounding world from fixed memory.
A popular example of limited memory AI is self-driving small cars. Vehicles take signals from a static memory to detect traffic signals, traffic lights, and lane markers. They have a dynamic memory in which they receive and store the speed and direction of surrounding vehicles.
3. Theory of mind: All current AI systems are either reactive or limited memory devices, and they can read all narrow AI Imagine machines to represent the world, where they think, logic, feel, and make decisions. It may think that this is what will be achieved in the future. Some real-life efforts in this direction and robots like Sophia. Sophia is a robot with advanced computer vision capabilities that can recognize, socialize and communicate with people. Kismet is a robotic head made to recognize and mimic human emotions.
This is the ultimate vision of artificial intelligence, making machines on their own an accurate representation of the world and awareness of themselves. It makes machines aware of and visualizes their attributes, states, and internal states along with their feelings, beliefs and beliefs. Consciousness from one model of a self-aware machine will not require consciousness from another. Instead, there is his consciousness. It will signal what it wants and what it needs to do. Such a machine itself is like a living being.
The human mind itself is a complex puzzle so creating a copy of the human mind or something better is all but unknown.
All current artificial intelligence applications fall under narrow AI and have reactive nature or limited memory performance. Without any representation of the world or limited and specific representation, these applications are so valuable and reliable that they perform best in data-heavy and detail-oriented tasks. Normal people can’t do it. We can improve artificial intelligence in the future. You can express your opinion here.