Artificial intelligence (AI) is the branch of computer science that deals with the creation of machines or systems capable of performing functions that would normally require human intelligence. These machines interact with the environment and behave according to the information they receive about it without any human intervention.
AI has been romanticized in science fiction literature and Hollywood movies. They have given us images of computers and robots that can talk, think, and act like human beings. The real state of AI is nowhere near this level yet. However, we are now seeing more and more machines that can play chess with human grandmasters, engage in intelligent conversations, and even drive cars.
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AI has been undergoing significant advancements, especially in the areas of machine learning (ML) and deep learning. These developments have resulted in several positive changes, particularly in the tech industry, although some continue to laud AI systems’ ability to equal humans with high proficiency. And it’s true, not all AI systems are created equal, most still have limited functionality.
4 Major Types of AI Systems
AI systems can be classified depending on their ability to mimic the capabilities of the human mind. Based on this criterion, there are four major types of AI systems, which are:
1. Reactive Machines
The most basic AI systems are those that are purely reactive. These machines cannot use their past experiences as the basis for the decisions they make. One concrete example of this is IBM’s Deep Blue. The chess-playing supercomputer may have beaten international grandmaster Garry Kasparov, but it didn’t do so by relying on experience. While the AI system can predict its opponent’s next move, it can’t learn from past movements. All it does is analyze the positions and potential moves each chess piece can make then decide, based on probability, what each move’s outcome will be.
2. Limited-Memory Systems
These AI machines are capable of looking at their past and applying learnings to current challenges. A solid example of these is self-driving cars. These AI systems observe the direction and speed of other vehicles on the road. The observation process involves object identification and monitoring over time, including traffic light changes, lane markings, and other relevant details that make up the car’s preprogrammed representations. The data analysis then lets the car decide if it’s safe to change lanes while avoiding collisions.
However, as the name implies, the information gathered remains limited to a specific time frame and changes constantly. It is not saved like a person’s experience.
3. Theory of Mind Machines
These machines are believed to have thoughts and emotions that impact their behaviors and perceptions. While they remain a concept still, developers hope to create them in the future.
4. Self-Aware Systems
Perhaps the culmination of AI development is when proponents finally build AI systems that can form representations of themselves. These machines will exhibit consciousness or self-awareness.
Conscious AI systems know they exist and can develop emotions. But many believe that self-aware systems can only surface after theory of mind machines come into fruition.
As shown, AI still has a long way to go. To date, we’ve only achieved the creation of the first two types.