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The Different Types of Artificial Intelligence You Should Know
Self-aware, corrupt AI-powered entities with tremendous knowledge that are hell-bent on wiping out humanity in order to save humanity from itself as we’ve seen multiple times in sci-fi novel and film plots is even further away than a remote possibility.
But, yeah, AI is here, and it’s doing a very good job of assisting mankind in accomplishing goals that previously seemed impossible or impracticable.
Today, we have various examples of artificial intelligence in action, such as:
- Autopilot feature in commercial flights
- Intelligent virtual assistants, like Alexa, Google Assistant, and Siri
- Plagiarism checkers
- Self-driving cars
- Spam filters
Machine intelligence, often known as artificial intelligence, is the intelligence demonstrated by machines. It’s a topic of study that focuses on emulating human intelligence in robots. AI now comes in a variety of forms. But before we get into it, let’s look at how it compares to machine learning.
AI is not the same as machine learning.
Although there are some similarities between artificial intelligence and machine learning, they are not the same. There are significant distinctions between AI and machine learning, which distinguishes them as related but distinct disciplines of study.
Machine learning, like deep learning and neural networks, is a subset of artificial intelligence. Machine learning is a type of data analysis that automates the creation of analytical models.
Machine learning (ML) is a sub-field of AI that focuses on helping machines to learn from data, find patterns, and make judgments with minimal human participation. AI, on the other hand, has a considerably broader scope, with machine learning as one of its components.
Types of AI
The goal of AI research is to create robots and systems that can mimic human-like behavior, particularly in terms of thinking and accomplishing tasks. As a result, human intelligence is employed as a criterion to classify the various forms of AI.
All AI and AI-based systems can now be classified in one of two ways.
The first one groups AI based on capacity, whereas the second one groups AI based on functionality.
Narrow AI, General AI, and Superintelligence are the three types of artificial intelligence based on their capabilities, i.e. their ability to accomplish tasks in relation to human task performing ability.
Narrow AI a.k.a. Weak AI
Narrow AI is the most common type of artificial intelligence available today. The capacity to undertake dedicated, predetermined tasks limits its reach. Weak AI can be found in Google Assistant, Siri, and even the IBM Watson supercomputer.
Narrow AI is less intelligent than humans because it lacks consciousness and self-awareness. Weak AI can’t do anything beyond its defined capabilities because they’re only trained to complete a single task or a collection of tasks. When forced to do so, the outcomes are unpredictable and useless.
If a computer or system can do an intellectual work with human-like efficiency, it is considered general AI. The goal of general AI is to create an artificially intelligent system that can mimic the intelligence and thought processes of a typical human.
There is currently no example of broad AI available. To put it another way, generic AI is still theoretical and not yet practical.
AI researchers are increasingly concentrating their efforts on constructing systems that may be classified as general AI. Naturally, the time and effort necessary are unprecedented.
Super AI/Artificial Superintelligence (ASI)
Artificially intelligent systems outperform or surpass human intellect at the super AI level. Such AI systems are capable of performing tasks significantly better than humans, and with cognitive qualities to boot. The following are some key properties of superintelligence systems:
- Ability to think, reason, and make judgments
- Able to solve puzzles
- Can plan on its own
- Communicate effectively
- Learn from surroundings, such as people, environment, and incidents
ASI is a hypothetical idea that aids in the exploration of artificial intelligence’s limitless possibilities. If superintelligence is ever achieved, this type of artificial intelligence has the potential to change the entire world as we know it.
We’ll categorize AI based on its functionality. This taxonomy of AI considers how AI systems behave and feel, as well as their cognitive capabilities and common (machine) sense.
Reactive Machines, Limited Memory Machines, Theory of Mind, and Self-Aware AI are the four classes into which we can place any AI system based on its capabilities.
These are the most basic sorts of AI systems that we have now, similar to Narrow AI. Reactive machines are incapable of forming memories and, as a result, are unable to react to future conditions based on their previous experiences.
Only by reacting to current situations can reactive machines work at their optimum. The following are two examples of reactive machines:
- IBM Deep Blue — A chess-playing computer developed by IBM that became the first-ever computer chess-playing system, in 1997, to win a chess game against a reigning world champion, Garry Kasparov.
- Google AlphaGo — A Go-playing computer program that became the first AI system, in 2015, to beat a Go professional without handicap on a full-sized 19×19 board.
AI systems with limited memory can only save a few past experiences or a small amount of data for a short period of time. This information is only available for a limited time. Self-driving cars have been the best example of limited memory AI systems till now. They have the ability to store data such as:
- Speed of close by cars
- Distance from those cars
- Driving speed limit
- Road directions
Self-driving automobiles are memory-limited devices that navigate the road using their memory storage capacities. This does not, however, imply that they are error-free. Self-driving cars are still a long way from becoming a reliable alternative for everyday use.
The Mind’s Theory Artificial intelligence (AI) refers to robots or systems that can recognize human beliefs, emotions, intents, values, and so on.
Human-like AI systems may be able to reciprocate and respond to human emotions and/or expressions.
Despite the fact that no significant progress has been made in constructing Theory of Mind AI systems, academics and experts from all over the world are working diligently to develop such AI machines/systems.
Although self-aware AI does not exist in reality, it is a hypothetical idea that investigates AI-powered computers with higher thinking capabilities than a regular human mind.
In theory, self-aware AI systems have their own consciousness, reasoning, and feelings. They have individuality like every other human, yet they are far more intellectual than any other human on the planet.
Humans’ fascination with artificial intelligence has never waned. Even before AI was a reality, fiction authors, movie producers, and visionaries used concepts that resembled AI.
Artificial intelligence is now a fact of life. Although we have a long and difficult road ahead of us, it is a fascinating journey that may help humans better comprehend themselves and rethink many concepts, including nature and life.
The development of AI will result in the emergence of new philosophies.
It will be critical for us humans, who are responsible for summoning these void-of-flesh-and-blood beings into our domain, to appropriately embark on the journey of machine intelligence exploration.
Don’t forget to look for the rest of my Artificial Intelligence articles in my series. You can subscribe below to gain access.
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