Introduction
Artificial intelligence (AI) allows machines to model and improves physical and mental human abilities. From the invention of self-driving cars to the proliferation of intelligent assistants like Siri and Alexa, AI is developing smart innovations for helping everyday life. Going through all the facts above, many tech companies are investing in artificially intelligent technologies.
What is artificial intelligence (AI)?
Artificial intelligence is a branch of computer science concerned with building intelligent machines (robotics) capable of performing tasks that typically require human intelligence.
Defining artificial intelligence (AI)
The major limitation in defining AI is simply developing intelligent machines and what makes machines intelligent. AI is an interdisciplinary science with different or multiple approaches but advancements in developing machine learning and deep learning are creating a paradigm shift in virtually every sector of the technology industry.
However, various new tests have been suggested recently that have been largely accepted, including a 2019 research paper entitled “On the Measure of Intelligence.” In the paper, veteran deep learning researcher and Google engineer François Chollet argue that intelligence is the “rate at which a learner turns its experience and priors into new skills at
valuable tasks that involve uncertainty and adaptation.” In other words: The most intelligent systems can take just a little amount of experience and you can predict what would be the outcome in many varied situations.
Stuart Russell and Peter Norvig go on to explore four different approaches in their book “Artificial Intelligence: A Modern” Approach that has historically defined the field of AI
Artificial intelligence is defined by four types of approaches
- Thinking humanly: copying thought based on the human mind.
- Thinking rationally: copying thought based on logical reasoning.
- Acting humanly: acting in a way that mimics human behavior.
- Acting rationally: acting in a way that is meant to achieve a particular goal.
The first two approaches concern thought processes and reasoning, while the others deal with behavior. Norvig and Russell focus especially on rational agents that act to achieve the best outcome, noting “all the skills needed for the Turing Test also allows an agent to act rationally.”
The Future of AI
When you consider the computational costs and the technical data infrastructure running behind artificial intelligence (AI), then you will come to know how executing AI is a complex and costly business. Fortunately, there have been massive advancements in computing technology nowadays, as indicated by Moore’s Law, which states that the number of transistors on a microchip doubles about every two years while the cost of computers is reduced by fifty percent.
Although many experts believe that Moore’s Law will come to an end anytime in the 2020s, this has had a major impact on modern AI techniques without it, deep learning would be out of the question, pecuniary speaking. Recent research tells us that AI innovation has outperformed Moore’s Law, doubling every six months or so as opposed to two years.
By that logic, the advancements in artificial intelligence (AI) made across a variety of industries have been major over the last several years. And the potential for an even greater impact over the next several decades seems all but inevitable.
Types of artificial intelligence
There are four types of artificial intelligence (AI):
- Reactive machines: Able to perceive and react to the world in front of it as it performs limited tasks.
- Limited memory: Able to store old data and predictions to inform predictions of what may go next.
- Theory of mind: Able to make choices based on their perceptions of how others feel and make choices.
- Self-awareness: able to operate with human-level consciousness and understand its entity.
