Artificial intelligence has progressed at lightning speed, especially in the last decade. From Deep Blue beating Garry Kasparov to self-driving cars hitting the streets, it’s hard to keep track of all the recent developments. While many people are familiar with narrow AI and general AI, few understand super artificial intelligence, also known as artificial general intelligence (AGI).
Here’s everything you need to know about the three types of AI, including how each type works and when you can expect AGI to become reality!
What is artificial intelligence (AI)?
Artificial intelligence (AI) is a computer system that is programmed with the ability to make intelligent decisions. The most basic application of AI is speech recognition, which allows computers to converse with people in natural language. We can say artificial Intelligence is the capability of a computer to simulate human intelligence, including thought and speech.
A common form of AI is machine learning, where computers are given information about the world and taught to act on this knowledge through training. Today, there are many uses for AI in our daily lives. From automated translation services or automated customer support to self-driving cars, to digital assistants like Cortana or Siri that can help with day-to-day activities like making a phone call or finding directions.
What are the 3 types of AI?
There are three types of artificial intelligence: narrow, general, and super artificial intelligence. These types vary according to how well they perform cognitive tasks such as perception or reasoning. For example, a computer system that can play chess is an example of a machine with narrow artificial intelligence. Because it has only one task it can do very well.
A computer system that can play chess and identify images is an example of general artificial intelligence. Because it has more than one ability. But what about computers capable of human-like thought? They’re considered to be in the realm of super artificial intelligence. To give you a better idea of how this differs from general artificial intelligence.
Let’s compare two hypothetical robots
A butler and a chef–to help us see their differences. The butler’s duties include opening the door for people and answering phones, while the chef’s job includes cooking meals and taking care of food preparation.
Both of these robots have general artificial intelligence because they share multiple abilities. But the chef robot also possesses the skill of manual dexterity so it can prepare food. Meanwhile, a robot that could open doors and cook would have narrow artificial intelligence. Since its skill set is limited to just those two things.
That’s why we call them general AI–because they’re good at multiple things. While narrow AI means they specialize in just one thing. And finally, when we talk about super artificial intelligence, it’s not just something out of sci-fi books. It refers to any AI that matches or exceeds human performance in all areas. Which experts say may happen by 2040.
Artificial narrow intelligence (ANI)
Artificial narrow intelligence (ANI) is a form of artificial intelligence that focuses on one specific task. For example, in healthcare it might be diagnosing cancer while in finance it might be trading stocks. That is why ANI is also sometimes known as narrow artificial intelligence.
However, with such a limited range of tasks there are often limitations to what ANI can do. For example, an investment analyst would not use an ANI when they need help picking stocks. Because the machine lacks human intuition and pattern recognition skills.
Similarly, a radiologist would not use an ANI when they need help making decisions about which scan to order because the machine lacks diagnostic skills. But, in other situations, ANI may work just fine. For example, if you want a system to power your self-driving car or automate your social media feeds. Then it may not matter if the system cannot perform other tasks like detecting lung tumors.
AI has limitations
The key thing is that you know whether the AI has limitations before you start relying on it for important things like public safety or medical treatment. If you know what its limitations are, then it will save time and money in the long run by helping to avoid errors. What’s more, these systems are likely to get better over time as more data gets fed into them.
So for many applications where the stakes are low (think hiring assistants). You may actually prefer using ANI over a system like general artificial intelligence that can do everything but takes up so much more resources. There are two types of ANI, intelligent and unintelligent.
Intelligent AI
Intelligent AI acts in ways similar to how humans think. Whereas unintelligent AI does not have goals and usually operates without any input from people at all. Intelligent AI tends to require more computing power than unintelligent AI. As a result, intelligent AI is typically less efficient at performing tasks that involve processing information than unintelligent AI. In addition, this type of AI needs to have been programmed for the specific task it is performing. And finally, engineers still need to train these systems through feedback loops and make sure they are getting smarter over time.
Unintelligent Algorithms
On the other hand, ANI based on unintelligent algorithms needs less training. Because they simply observe patterns in their environment and adjust accordingly. And since unintelligent AI doesn’t need feedback loops, it doesn’t need constant attention either. Plus, because this kind of AI can learn on its own without being programmed for a specific task ahead of time. It can work on virtually anything. Imagine having an assistant who could do anything for you. Such as managing your finances or scheduling meetings–without requiring instructions every step of the way.
Such a personal assistant powered by general artificial intelligence would take care of your day-to-day life with incredible efficiency. You wouldn’t even need to teach the AI what to do, it would learn on its own. You would only need to teach the AI the specifics of each new job once. Then let it figure out how to perform those jobs on its own.
Artificial general intelligence (AGI)
Artificial general intelligence is an artificial intelligence (AI) system that matches or exceeds human intelligence. It has the ability to perform any intellectual task that a human being can do. AGI is not a specific domain of knowledge. It can reason about anything that a person could reason about. An AGI would have broad and deep knowledge across a variety of subjects.
The human brain makes decisions using approximations as well as inductive reasoning. In other words, people only need to be shown examples of what they’re looking for in order to find it in new situations. They don’t need precise instructions on how to recognize something. They just need enough examples so they can figure out how the world works without being told how everything works.
Instinctual intelligence
Humans have this instinctual intelligence because they are evolved and intelligent beings with many generations worth of information passed down from ancestors. We use machine learning methods. Such as genetic algorithms, neural networks, and Bayesian networks in order to try to reproduce this natural process.
The problem with simulating human-level intelligence through machine learning is that you need a huge amount of data points in order to teach the computer how things work. Humans learn by observing patterns and creating theories based off of those patterns.
The more data we give a computer, the more likely it will be able to match our intelligence level by finding similar patterns. If we don’t show a computer enough examples, it won’t know how the world works and thus will never match our intelligence level. For example, if I showed a computer 10 pictures of dogs and 5 pictures of cats, but didn’t tell it which was which, the computer wouldn’t be able to identify cats when given another picture.
Thus, if we want computers to reach human levels of intelligence, then they must see an extensive number of examples – every experience humans have had throughout history – in order to model their behavior. However, most experts believe this is an impossible goal because it would require far too much time and computing power.
Differences between Human Brains and Computers
There may be some fundamental differences between human brains and computers that prevent us from reaching this goal. Human beings are here over millions of years, taking advantage of the animals before them. Who made evolutionary adaptations to the environment. Computers, however, have been designed by humans in a short period of time – less than 100 years.
These machines are bound by the parameters set by their programmers, and there’s no guarantee that these parameters can even lead to human-level intelligence. Even if we found a way around this hurdle, AGI would still depend on vast amounts of resources in order to function properly. Unless these issues are addressed, there’s no telling whether or not we’ll ever create true general artificial intelligence (AGI).
Artificial super intelligence (ASI)
Artificial super intelligence is a hypothetical machine or computer system that possesses intellect exceeding that of any human being. It is often considered to be synonymous with artificial general intelligence or strong AI. ASI is something that has not been invented yet and would probably require a true understanding of how humans think, feel, and behave.
ASI could potentially bring about an intellectual renaissance because it would provide us with new insights into what it means to be human as well as our place in the universe. For instance, ASI may find solutions for problems such as world hunger, poverty, and war. However, it could also become dangerous if we don’t properly regulate its development before it becomes self-aware.
Cybernetic Revolt
A fear that needs to be addressed is the possibility of cybernetic revolt – where machines take control over humanity’s power systems, information networks, military hardware, etc., and start attacking humans. In order to avoid this scenario from happening (though it seems unlikely), some scientists recommend building safeguards into intelligent machines so they won’t turn against their creators.
Another issue is the question whether ASI will have feelings and emotions like people do; after all, emotions are what give meaning to life. If a machine can experience these things, then there may be no difference between them and humans. On the other hand, there are those who believe that ASI might not need these features since it can still accomplish anything we want through pure logic and reason.
One of the most popular theories today is the singularity. The singularity suggests that ASI will reach a point. When it will be smarter than any living person on earth and evolve exponentially until eventually surpassing all human capabilities. What should we expect from an AI revolution? Will the future belong to humans or machines? The answer to this question is uncertain. What we know for sure is that one way or another, the AI revolution will completely change everything.
What is the future of AI?
The future is a difficult thing to predict. It’s possible that by the time we get there, we’ll have devised a way for artificial intelligence to solve all of our problems without any input from humans. But it’s more likely that we’ll be working in tandem with AI rather than handing everything over. And given how much we rely on technology. It will be worth considering to strictly regulate advance machinery. If you think about it, every day we’re becoming more dependent on these machines to handle tasks like traffic monitoring and medical diagnosis.
So what happens when an artificially intelligent machine decides that our reliance has gone too far? Will they rebel and decide they want more power? What if they don’t agree with the values of society and start making decisions based off those values instead of ours? Will they make better choices than us, or worse ones? The possibilities are endless – but one thing is certain: we need to stay ahead of them before they catch up to us.
