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The artificial intelligence industry is worth more than you think. It has a market size of about $387 billion and is bound to hit trillions in less than a decade. Here’s another thing I bet you didn’t know: there are seven types of artificial intelligence.
Are you curious about this new technology and how it mimics the human brain using machine learning? If yes, then you’re in the right place. Read on as we explore the seven types of AI.
After reading this, you’ll learn about the seven types of artificial intelligence, their risks, and the future of AI technology.
What is Artificial Intelligence (AI)?
Simply put, artificial intelligence uses advanced mathematical computations, known as machine learning, to give computers the ability to handle problems that require complex or human reasoning. People use AI systems in applications like natural language processing, visual recognition, and decision-making.
It is a relatively new field study that combines data science and computer science (among other disciplines).
As the notoriety of artificial intelligence grows globally, brands have become desperate to market their products as AI-enabled tools to piggyback off the hype surrounding this new technology.
You might wonder how self-driving cars and artificial intelligence-powered writing assistants use the same underlying technology.
Short answer. There are seven types of AI with a diverse range of industrial applications. The seven different types of artificial intelligence vary according to function and the degree of work they can handle.
You’ll see what I’m talking about in the following sections.
What Are the Different Types of Artificial Intelligence?
There are seven different types of artificial intelligence. However, the AI community classifies the different types of AI into two groups based on capability and functionality. In other words, people divide AI according to performance and problem-solving ability.
In terms of capability, there are three types of artificial intelligence:
- Artificial Narrow Intelligence (Narrow AI)
- Artificial General Intelligence (Strong AI)
- Artificial Superintelligence (Super AI)
Under functionality, we have four types of artificial intelligence:
- Reactive Machines
- Limited Memory
- Theory of Mind
- Self Aware
Let’s take a deeper look at each type of artificial intelligence.
What Are the 3 Types of AI Based on Capability?
In this category, you can group AI systems according to their level of competency. Narrow AI systems are the weakest of the bunch, while the latter—Artificial General Intelligence and Artificial Superintelligence—perform tasks ascribed to human intelligence.
Each subsequent type of artificial intelligence in the list requires more computing power than the last.
1. Artificial Narrow Intelligence (ANI)
Artificial Narrow Intelligence, abbreviated as ANI, is also known as weak AI or narrow AI. Nearly all existing applications of AI fall into this category.
Developers design this type of AI system for specific purposes. These machines are powerless in situations outside a small range of cognitive ability.
Weak AIs are commonly used to develop tools that automate mundane activities which barely task a human mind but consume a lot of time. For example, robot vacuum cleaners, virtual assistants, google translate, biometric scanners, and so on.
Thankfully, these types of artificial intelligence help to improve everyday life.
A prime example of an AI-powered virtual assistant is Alexa. It is a virtual home assistant that can only handle a finite set of automotive tasks: casual conversation, calling a contact, playing music, etc. Alexa might find requests that require more complex reasoning difficult; however, she is powered by natural language processing.
To throw more light on the limited scope of an ANI, the IBM supercomputer Watson, which parses human questions using machine learning and a combination of other AI development techniques, does this one task of answering questions terrifically.
2. Artificial General Intelligence (AGI)
Also referred to as Strong AI, Artificial General Intelligence (AGI) is a computer trained to possess the full-cognitive ability of the average human being.
To be clear, AGI does not exist yet. However, an investment fund called OpenAI raises funding for the cause. Several big tech companies have pumped billions of dollars into AGI research through this platform.
Though general AI has yet to arrive, some researchers have made commendable progress in that direction. Several AI researchers have built supercomputers with incredible computing power to stimulate human neural activity.
AGI will become one of the most important types of artificial intelligence in the near future. These intelligent machines will harness the power of neural networks, machine learning, natural language processing, and deep learning for solving future problems.
However, despite the generous funding and aggressive efforts, we still have a long way to go before General AI becomes a reality. Considering the progress so far and the long road ahead, it’ll be several years into the future before we realize general intelligence.
3. Artificial Superintelligence (ASI)
While Artificial General Intelligence is supposed to have human intellect, Artificial Super Intelligence goes beyond. At the moment, Super AI only exists as an idea. We are probably light years away from possessing the caliber of technology that makes it possible.
ASI describes an AI that reaches self-awareness, understands human emotions, and even develops an independent will. Other characteristics of Super Artificial Intelligence involve decision-making, puzzle-solving, and thinking.
Super AI is a hot topic of debate globally. There is a theory that the rise of robots with Artificial Super Intelligence will be a tipping point for human civilization. Some fictional works have emphasized the grim turnout of Super Artificial intelligence, like the book “Do Androids Dream of Electric Sheep” by Philip K. Dick.
That brings us to the four types of artificial intelligence based on functionality.
What Are the 4 Types of AI Based on Functionality?
One cannot classify the different types of artificial intelligence without considering their operating principle. This category factors in the elements that influence the actions of artificial intelligence systems.
It describes how such a system parses data to determine its output. While Reactive Machines have no working memory and strictly take actions based on the present moment, Limited Memory AI stores data and uses them to perform improved computations—they factor past and current events to determine the following line of action.
Theory of Mind and Self-Aware AI only exist in theory and fantasy. Speculation says they can do things beyond the human intellect.
4. Reactive Machines
Reactive machines are the oldest type of AI system. They are stateless AI machines that don’t take account of previous events while taking new actions. Instead, these machines calculate the best possible outcome based on an immediate combination of inputs.
On that note, there’s no way for such machines to learn from previous data and improve their function. Reactive Machines don’t measure up to the cognitive faculties of the human brain. Such systems are only good at reacting to external stimuli and cannot gain knowledge from past data.
However, that doesn’t mean we shouldn’t undermine the ability of Reactive AI. A quintessential example of a Reactive Machine is Deep Blue by IBM. In 1997, this AI machine defeated a chess Grandmaster, Garry Kasparov.
5. Limited Memory
Limited Memory artificial intelligence is an improvement on Reactive Machines. In addition to responding to immediate input, Limited Memory AI makes more informed decisions by retrieving historical data from storage. In other words, they are more sophisticated than Reactive Machines.
Just as human beings build neurons through continuously practicing the same activity, Limited Memory devices are fed with a large set of training data—using machine learning and deep learning—to serve as a reference for solving tasks and enhancing precision.
Limited Memory AI has many present-day AI systems like self-driving cars and deepfakes.
6. Theory of Mind
Theory of Mind is a sentient AI machine. Unlike Limited Memory AI, the Theory of Mind AI is sensitive and doesn’t mechanically respond to past data. It is capable of empathy, reading the target’s emotions, and being aware of their belief systems.
Although the Theory of Mind AI doesn’t exist yet, it is an active area of artificial intelligence research (so be on the lookout for this one). While it is a work in progress with leading AI researchers on the case, such an AI depends on innovation in other industries to reach actualization.
In the future, Theory of Mind AI has the potential to provide more humanized virtual assistants, including other captivating applications. They will sound indistinguishable from other humans and speak with natural human language.
7. Self-Aware
As you may have guessed, these machines have self-awareness. That means they are actively conscious of themselves. At the moment, sentient AI only exists as a concept. Arguably, this is one of the most terrifying types of artificial intelligence, but as of today, there’s no substantial research in this area.
As the ultimate objective of AI research, Self-Aware Artificial Intelligence will mark the final stage of evolution in AI technology. However, it will take a long while before AI development reaches this point, assuming we eventually do.
Self-aware AI is a frequent theme in sci-fi, where it is either painted in a utopian or dystopian light. Stanley Kubrick’s 2001: A Space Odyssey is one of the most popular presentations of the seedy side of sentient AI on TV.
What Are the Dangers of Artificial Intelligence?
Should we be worried about creating machines that could make us regret their future actions?
Artificial intelligence is a disruptive technology that has sparked controversial conversations around the globe. While many advocate its potential to improve the quality of life, others argue that the net negative effect of AI technology cancels out its pros.
Elon Musk, CEO of Tesla, the AI-powered company famous for self-driving cars, has never been comfortable with unchecked AI research. On another occasion, Elon Musk warned that the dangers of AI development pose a more serious threat to world peace than the North Korean dictator and described it as “summoning the devil.”
In 2017, at a National Governors Association meeting, Elon opined that AI progress needs regulation to prevent research and innovation in this area from spiraling out of control. Leading by example, Tesla Motors has remained under the regulatory guidelines of the National Transportation Safety Board.
It is noteworthy that Elon Musk also founded a startup called NeuralLink, which he claims will help people form symbiotic relationships with artificial intelligence using brain chips. Whether Elon Musk is concerned about the risks of AI or merely trying to incite mass fear so he can assert NeuralLink as a solution and sell brain chips remains debatable.
Aside from Elon Musk, other notable figures and voices in tech have aired their fears about AI technology. The co-founder of Microsoft, Bill Gates, echoed Elon Musk’s call for regulation to curb the side effects of AI. Bill Gates believes that properly monitored AI progress leads to more pros than cons.
Although the threat of AI machines to world peace has been over-fictionalized in sci-fi movies, it doesn’t make it any less possible. There’s the chance that nations could weaponize AI systems by building an army of automotive, murderous machines.
Besides the mortal dangers, there’s the ethical question regarding the creation of consciousness through Self-Aware types of artificial intelligence. That means anyone dabbling in AI development must fully understand the conduct of ethical design.
What is the Future of AI?
It’s easy to see a bright future ahead of artificial intelligence. This revolutionary technology is already taking the world by storm, dominating innovation in other emerging technologies like IoT, big data, and robotics.
It has become an integral part of our lives—whether you notice it or not, you interact with artificial intelligence daily.
In the coming years, the capability of AI technology will become indistinguishable from the imagination of sci-fi movies. Fully-functional robots will shoulder the burden of handling dangerous, boring, and repetitive tasks, and they will solve real-world problems. Siri will sound convincingly human and personal, and other incredible innovations await.
However, the issue of the unethical use of AI is one aspect that casts a shadow of doubt over this disruptive technology’s future. But we must be prepared to take the good with the bad.
Like every other emerging technology, AI will undoubtedly be a dangerous tool in the wrong hands. It is up to government regulations to subdue these side effects by closely monitoring AI research to prevent developers from overstepping.
Summary
Under the seven types of AI systems listed in this digest, we have encountered the existing, the work-in-progress, and the fantasy. I like to think of this as another way to classify the different types of artificial intelligence. Considering the speed at which the AI industry is moving, we can expect this trilogy to dissolve into only the ‘existing’ in the coming years.
