What is Artificial Intelligence(AI)?

Artificial intelligence (AI) is a single or collection of computer systems able to process information and perform tasks usually done by humans.

AI can have simple forms of intelligence, such as recognizing speech or analyzing visual patterns in images. Or it can be more complex, such as learning from past mistakes and problem-solving.

What Is Artificial Intelligence?

To understand what artificial intelligence means, think about what you observe in nature which makes you convinced something has intelligence. Something as simple as a lab rat learning the correct path through a maze represents a simple form of intelligence (there are four types of AI). It involves memory and learning, similar to human intelligence.

In 1950, Alan Turing described "thinking machines" as recognizable because they could use reason to solve puzzles. In the 1950s, John McCarthy said computers could "do things, which, when done by people, are said to involve intelligence."

These ideas boil down to three characteristics used to identify a machine or computer as having "artificial intelligence." They can:

Use inputs, such as sensors or data, to analyze information.

Process vast amounts of data to identify patterns, trends, or correlations.

Adapt their decisions and actions based on learnings derived from inputs and data.

It's precisely how human intelligence helps humans learn and adapt in our daily lives.

Components Making Up Artificial Intelligence

An "intelligent" machine is made up of many different components. These all work together to help a machine take input from the real world and make decisions.

AI Sensors

If you think about how a human collects data from the real world, intelligent machines need sensors to collect the same information. These sensors can include:

Cameras: Visual cues to do things like facial recognition, avoiding obstacles, or infrared cameras to detect when objects are hot.

Microphones: Interact with humans via voice, detect activity in a room, or respond to music.

Tactile sensors: Lets robots adjust their grip or game consoles' strength to respond to how hard you're moving a game controller.

Position, temperature, or flow sensors: Provides information about gas or liquid flowing through pipes, temperatures of chemicals or metals, and even liquids' chemical makeup.

In fact, with modern-day sensor technology, machines can detect things about the world that even humans can't.

AI Data and Machine Learning

An essential component of AI is machine learning. It's the ability to collect vast amounts of information from multiple sources and analyze it for meaningful patterns and correlations.

For example, during vehicle crash tests, a computer can analyze pressures and temperatures. The computer can analyze the data and tell vehicle manufacturers where to place airbags to provide the highest safety level.

Machine learning also helps with troubleshooting problems. By collecting manufacturing data across hundreds of sensors, computers can identify anomalies that result in faulty products. Then, by correlating other sensor data, the computer can tell technicians which components in a process are flawed.

Since machine learning can do this in a fraction of the time a human can, companies can identify and fix problems faster, improve the quality of products, and boost overall production.

Deep Learning

A more advanced form of machine learning is "deep learning," when a machine identifies failures and learns the most efficient way to accomplish a task.

For example, a self-driving car will use machine learning to drive a car by watching road markings, looking for pedestrians, and identifying traffic lights. But a deep-learning, self-driving car would also learn how steering adjustments keep the car more in the center of the lanes. Over time, this car could teach itself how to become a better driver.

What's the Purpose of Artificial Intelligence?

Scientists are developing artificial intelligence so we can use machines to improve the quality of life for humans. It lets machines do repetitive tasks which might injure or be dangerous for humans. Artificial intelligence can improve the safety of cars and airplanes.

Ultimately, their purpose is to supplement humans with insights from vast amounts of data only computers can process.

Dan Prince, CEO and Founder of Illumisoft, says that the starting point for understanding AI is to understand our own intelligence.

"Humans have the capacity to learn, to solve problems, to recognize patterns, and to explain and predict natural phenomena (which are) all attributes commonly associated with intelligence," he says. "Perhaps most importantly, we’re able to act in ways that shape and transform our environment for our benefit. AI, understood most generally, refers to a system or group of systems that is able to simulate that kind of human intelligence. An intelligent system would be one that exhibits human-like capacities for reasoning, problem-solving, or even creativity.

"The ultimate goal for many researchers is to generate an artificial general intelligence (AGI), something analysts acknowledge has not yet been achieved. As technology currently stands, a particular AI might be good at simulating one aspect of human intelligence, but not others. There are AI systems, for example, that are proficient at understanding language, while others are good at fine motor control. There are very few that can do both."

Philosophers often question whether we can take AI too far. What if artificial intelligence surpasses human intelligence to the point where robots become superior? Then there's the question of whether machines will ever be able to understand emotion. Currently, there's no sensor capable of emotion.

However, most machines with AI are only capable of focused areas of learning. We can't apply it to the multitude of decisions an average human makes daily. Because of that, the idea of machines overtaking humans any time soon is not something anyone needs to worry about now.

What are the four types of AI?

The four types of AI are reactive machines, limited memory, theory of mind, and self-awareness.

How do you make an artificial intelligence?

Generally, creating an AI involves identifying the problem you want the AI to solve, collecting data, then training algorithms using the data you organized. Some platforms such as Microsoft Azure Machine Learning and Google Cloud Prediction API can help you build and deploy your AI.

Who invented artificial intelligence?

British computer pioneer Alan Turing was responsible for the earliest work in artificial intelligence in the 1930s. John McCarthy, a professor emeritus of computer science at Stanford, first coined the term "artificial intelligence" in a written proposal in 1955.

When was artificial intelligence invented?

The term “artificial intelligence” originates from a 1956 conference at Dartmouth College in New Hampshire. However, the earliest AI program was created by Christopher Strachey in 1951 at the University of Oxford.

What is artificial general intelligence?

Artificial general intelligence, or AGI, is the ability of a computer program to perform any intellectual task that can be performed by a human. Artificial intelligence is usually limited to more narrow tasks.

How will artificial intelligence change the future of education?

Artificial intelligence is already used in education to monitor student and teacher performance. AI-focused education modules are being developed that personalize lessons to students' learning styles.

The general benefit of artificial intelligence, or AI, is that it replicates decisions and actions of humans without human shortcomings, such as fatigue, emotion and limited time. Machines driven by AI technology are able to perform consistent, repetitious actions without getting tired. It is also easier for companies to get consistent performance across multiple AI machines than it is across multiple human workers.

Companies incorporate AI into production and service-based processes. In a manufacturing business, AI machines can churn out a high, consistent level of production without needing a break or taking time off like people. This efficiency improves the cost-basis and earning potential for many companies. Mobile devices use intuitive, voice-activated AI applications to offer users assistance in completing tasks. For example, users of certain mobile phones can ask for directions or information and receive a vocal response.

The premise of AI is that it models human intelligence. Though imperfections exist, there is often a benefit to AI machines making decisions that humans struggle with. AI machines are often programmed to follow statistical models in making decisions. Humans may struggle with personal implications and emotions when making similar decisions. Famous scientist Stephen Hawking uses AI to communicate with a machine, despite suffering from a motor neuron disease.

The Four Types of Artificial Intelligence

Reactive, Limited Memory, Theory of Mind and Self-Aware: What to know about the different levels of AI and how they compare to one another

Artificial Intelligence, or AI, is increasingly becoming a part of our everyday lives, even if we don't always know it. Because it's already here and only going to become more critical in the future, it's essential to understand the four types of artificial intelligence, how they're distinct, and which ones are in use today.

Overview of Artificial Intelligence

Artificial Intelligence is measured in comparison to the functions of the human mind. A true, fully complete AI could replicate—and likely extend—a human brain's functions.

It would be self-aware, have consciousness and memories, could learn and make predictions about likely future events—and would do these things on its own, without human intervention or input from programmers.

The Four Types of AI: Reactive Machines

The first and most basic kind of AI is Reactive Machines. These machines have intelligence that exists almost entirely in the present moment (eat your hearts out, meditators!). Programmers build Reactive Machines around complex sets of rules. In addition to those rules, they may include neural networks that allow them to learn and adapt in the moment.

Crucially, though, this type of AI can't form memories or act based on past experiences. Because they can't create memories, they can't take past occurrences, even those that happened to them, and use them to make new decisions.

In this way, they're restricted to the scenarios and information covered in their sets of rules. Because of this limitation, one can trick Reactive Machines into being defeated by forcing them to operate outside their limited set of rules.

Reactive Machines also don't have a concept of the future. They can use their rules to make extrapolations about what might come next, but only within the boundaries established by their rule sets.

Because they can't change their future actions based on past occurrences, Reactive Machines can't learn.

Examples: IBM Deep Blue (plays chess), IBM Watson (won at Jeopardy), Google AlphaGo (plays Go), recommendation engines like those found in streaming video and audio services

The Four Types of AI: Limited Memory

This more-advanced AI type has the abilities of reactive machines but adds a concept of the past. While Limited Memory AIs aren't forming memories, they are aware of a recent past and can use the data captured at that time to influence their decisions.

Self-driving cars are the best example here. They continuously monitor the conditions around them—what other vehicles are doing, where objects are, how pedestrians are moving, etc.—and holding that information in a temporary state to influence their actions.

As you might imagine, Limited Memory AIs process tremendous amounts of data and make decisions very quickly.

This AI level is called "Limited Memory" because these past experiences aren't stored permanently, and it can't use them for all future learning. Instead, these past experiences are saved for a short time while they're practical and then discarded.

Examples: Self-driving cars

The Four Types of AI: Theory of Mind

With Theory of Mind AI, we get closer to the science-fiction ideal of artificial intelligence. This level of AI includes all of the aspects of Reactive Machines and Limited Memory. But it adds a crucial and complex bit of understanding: that the living objects (people, animals, etc.) around them have a thing called a "mind."

Once an AI understands that other creatures have minds, it can then understand that it should learn and adjust its decisions based on those minds. It then understands minds generate thoughts and emotions (even if it doesn't truly understand what those things are yet) and that thoughts and emotions will influence behavior. The AI has to use those factors in its decision-making framework.

Examples: There are no known examples of Theory of Mind AI in existence (though some robots that attempt to understand and simulate point a direction for this type)

The Four Types of AI: Self Aware

Self-Aware AI is the final and most complex, and mature level of AI. It's a genuinely self-aware intelligence. Any AI from science fiction falls into this category. It's an entity with true consciousness.

It's aware of its existence and its internal states (and potentially emotions), can form memories of the past, and make predictions. It's aware of other consciousnesses and can take them into account when making decisions. Crucially, it can learn and become more intelligent based on its experiences.

A Self-Aware AI would require extremely flexible programming logic, an ability to update its logic on its own, and a tolerance for inconsistency since human behavior isn't always neatly predictable or rigidly patterned.

Examples: Self Aware AI doesn't exist currently and is likely many years away from being achieved

Should We Worry About AI?

Anyone passing familiar with science fiction about AIs knows that things often go wrong for humans once a machine achieves consciousness (hello, Skynet). So, should we be worried about AI?

There's no single answer to this question, but it's a good idea to be thoughtful and careful about how we go about creating and using fully self-aware AI.

There's the doomsday scenario of AIs replacing humans—whether that means taking human jobs and leaving people without work or income or the darker Terminator-style storyline. There are also ethical concerns: Is it acceptable to create a consciousness that can think and feel and then force it to do our bidding?

Some ethicists study AI and write about these questions. As AI becomes more advanced and more widespread, we'll need to make sure we listen to them, and our laws and governments adapt to the unique challenges—and possibilities—created by AI.