Artificial intelligence

It may sometimes feel like AI is a recent development in technology. After all, it’s only become mainstream to use in the last several years, right? In reality, the groundwork for AI began in the early 1900s. And although the biggest strides weren’t made until the 1950s, it wouldn’t have been possible without the work of early experts in many different fields.

Knowing the history of AI is important in understanding where AI is now and where it may go in the future. In this article, we cover all the major developments in AI, from the groundwork laid in the early 1900s, to the major strides made in recent years.

For hundreds of years, humans have been interested in the possibility of artificial intelligence, long before Alan Turing asked the crucial question: “Can machines think?” The concept of “nonhuman intelligence” traces back to ancient Greek philosophers. The concept of robots goes back to the Renaissance.

In our modern age, AI is everywhere. It’s in how we navigate transportation, how we communicate, and where we get our entertainment, just to name a few. And AI continues to grow, becoming a more integral part of modern societies by the day. Companies invest billions of dollars into the development of more advanced AI.

As a business, it can be confusing to navigate the ever-evolving world of AI. You want to be on the cutting edge, but don’t know exactly where to start. That’s why we created this complete guide. This article covers a range of topics, including:

The original definition of AI, defined in 1955 by John McCarthy, one of the original creators of the field, was pretty broad and all-encompassing: “The science and engineering of making intelligent machines.”

A slightly more modern definition of AI is: a broad branch of computer science concerned with creating machines that can learn, make decisions, and perform tasks to a human-like level. Advanced AI machines can learn and grow on their own, independent of human intervention. Even basic AI can handle complex tasks that would normally need a human touch but may need the help of a programmer to learn from its mistakes and improve.

How Does AI Work?

At the most basic level, AI functions by taking in data and using an iterative processing system and different algorithms to learn from patterns found in the data, and then react to it in a specific way. Advanced AI can also measure its own performance each time this sequence runs and start iterating and improving its own performance.

AI systems use something called the propensity model to make predictions based on the data it processes, and then use those predictions to respond to or initiate actions.

Different types of AI run off different baseline AI algorithms, which make them react and learn in different ways. Some do simple tasks of categorizing data or making predictions. Some do much more complex tasks, such as driving a car without a human at the wheel.

Types of AI

There are four main types of AI, and each type is defined based on how much data it can store, and how it uses that data. Some cannot store data at all and can only react to the stimulus directly in front of it. Some can store a limited amount of data. Some have the ability to store much data and use it to improve.

Of the four types of AI that are established, at present, the last two are simply theoretical. Researchers and programmers are still working toward achieving those levels.

The most basic level of AI functions on a “reactive” system. These machines cannot store data in their memory, and (as the name suggests) can only react to the data in front of them. These machines can’t learn or form any kind of memories, and always react to the same input with the same output.