Artificial intelligence (AI) is a single or group of computer systems capable of processing information and performing tasks typically performed by humans.
Artificial intelligence 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 solving problems.
To understand what artificial intelligence means, think about things you observe in nature that convince you that something is intelligent. 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 artificial intelligence). It involves memory and learning, similar to human intelligence.
In 1950, Alan Turing, best known for conducting an experiment to determine whether computers possessed artificial intelligence, described "thinking machines" as identifiable because they could use reason to solve difficult problems. In the 1950s, John McCarthy said that computers could "do things done by humans, said to involve intelligence."
These ideas boil down to three characteristics that identify whether a machine or computer has "artificial intelligence." A device can be considered artificial intelligence when it meets the following conditions:
- Use inputs such as sensors or data to analyze information.
- Process large amounts of data to identify patterns, trends, or correlations.
- Align decisions and actions based on knowledge gained from inputs and data.
This is exactly how human intelligence helps humans learn and adapt in their daily lives.
"Smart" machines are made up of many different components. These factors work together to help machines take input from the real world and make decisions.
If you think about how humans collect data from the real world, smart machines need sensors to collect the same information. These sensors can include:
- Camera : Visual cues for facial recognition, obstacle avoidance, etc., or infrared cameras for detecting when objects are getting hot.
- Microphone : Interact with humans via voice (like Alexa or Siri), detect activity in the room, or react to music.
- Tactile sensors : Let the robot adjust the strength of its grip or console in response to how hard you move the game controller.
- Position, temperature or flow sensors : Provide information about the temperature of gases or liquids, chemicals or metals flowing through pipes, and even the chemical composition of the liquid.
In fact, with modern sensor technology, machines can detect things in the world that even humans cannot.
An important component of artificial intelligence is machine learning. It is the ability to collect large amounts of information from multiple sources and analyze it for meaningful patterns and correlations.
For example, during vehicle crash testing, computers can analyze pressure and temperature. Computers can analyze the data and tell automakers where to place airbags to provide the highest level of safety.
Machine learning can also help solve problems. By collecting manufacturing data from hundreds of sensors, computers can identify anomalies that lead to product failure. Then, by correlating other sensor data, the computer can tell technicians which components in the process are defective.
Because machine learning can accomplish this task in a fraction of the time it takes humans, companies can identify and solve problems faster, improve product quality, and increase overall throughput.
A more advanced form of machine learning is "deep learning," where machines can identify failures and learn the most efficient way to complete a task.
For example, self-driving cars will use machine learning to drive by observing road markings, finding pedestrians, and recognizing traffic lights.
But deep learning self-driving cars will also learn how to adjust steering to keep the car more in the center of its lane. Over time, the car can teach itself how to become a better driver.
Scientists are developing artificial intelligence so that we can use machines to improve the quality of human life. It lets machines perform repetitive tasks that can cause harm or danger to humans. Artificial intelligence can improve the safety of cars and airplanes.
Ultimately, their purpose is to provide humans with insights into the vast amounts of data that only computers can process.
Dan Prince, CEO and founder of Illumisoft, said the starting point for understanding artificial intelligence is understanding our own intelligence.
“Humans have the ability to learn, solve problems, recognize patterns, and explain and predict natural phenomena (which are) attributes commonly associated with intelligence,” he said. “Perhaps most importantly, we are able to behave in ways that shape and change our environment for our benefit. Artificial intelligence, most commonly understood, refers to a system or set of systems capable of simulating human intelligence. The system will be a representation of Systems that mimic human reasoning, problem-solving, and even creativity.
"The ultimate goal of many researchers is to produce artificial general intelligence (AGI), but analysts acknowledge that this goal has not yet been achieved. With current technology, a specific AI may be good at simulating one aspect of human intelligence, but not Other aspects. For example, some AI systems are good at understanding language, while others are good at fine motor control, but few can do both.”
Philosophers often question whether we can take artificial intelligence too far. What if artificial intelligence surpasses human intelligence and makes robots even better? The next question is whether machines can understand emotions. Currently, there are no sensors capable of sensing emotions.
However, most machines with artificial intelligence can only perform focused learning areas. We can’t apply it to the many decisions ordinary people make every day. Because of this, no one now needs to worry about the idea that machines will soon surpass humans.
FAQThe four types of artificial intelligence are reactive machines, limited memory, theory of mind, and self-awareness.
Generally speaking, creating AI involves identifying the problem you want the AI to solve, collecting data, and then training the algorithm using your organization's data. Some platforms, such as Microsoft Azure Machine Learning and Google Cloud Prediction API, can help you build and deploy AI.
British computer pioneer Alan Turing was responsible for the earliest work in the field of artificial intelligence in the 1930s. John McCarthy, professor emeritus of computer science at Stanford University, first coined the term "artificial intelligence" in a written proposal in 1955.
