AI is playing a much bigger role in our lives now. This chapter will describe what AI is and explain its impact in our lives. Keep scrolling!
Emerging around 1956, AI has made significant progress in recent years.
The Industrial Revolution changed the world. Similarly, many people predict AI will bring another revolution that will affect the way we live in an equally, if not more, significant way.
Unlike what is depicted in Hollywood movies and science fiction films, AI is not a big scary robot taking over the world. but is actually all around you. AI applications can be subtle things that we use every day, like the algorithm that recommends a TV show to watch.
In concise words, AI is the computerization of tasks that usually require human intelligence. If you are still picturing a robot in your head, then think of AI as the brain of that robot, not the physical hardware. Just as steam engines freed humans from intense repetitive physical labor, AI is freeing us from low-level, tedious brain labor.
Today’s AI is still what scientists describe as Artificial Narrow Intelligence (ANI). An ANI can only perform a specific task - like driving and face detection.
Scientists and researchers are working to reach the ultimate goal of AI, Artificial General Intelligence (AGI), in which algorithms can perform and complete any intellectual tasks that humans can.
3327 - number of AI companies that can be found on Crunchbase (Crunchbase)
4 billion - number of devices with smart voice assistants, like Siri and Alexa, in 2017 (Motley Fool)
$5 billion - amount of venture capital invested in AI-related firms in 2017 (datanami)
$37 billion - an estimated amount of total revenue in AI by 2025 (Tractica)
An algorithm is very much like a cooking recipe. It is a set of clear instructions that you or a machine can follow to achieve a certain purpose. Computers do not understand vague high-level instructions that humans do; algorithms are precise machine-level operations that computers can follow.
Machine Learning (ML) is a specific area of AI. The word “machine” here refers to algorithms, instead of physical machines. As described by its name, machine learning aims to train a machine to learn based on data rather than pre-defined rules. After the algorithm is trained with large amounts of data, it will be able to perform tasks at a relatively high level of performance.
Deep Learning (DL) is a branch of machine learning that centers around Artificial Neural Networks (ANN). The following chapters focus on explaining concepts in this subfield of AI. Deep learning algorithms need even more data than traditional machine learning algorithms, but are more flexible and powerful.
In this chapter, we looked at what AI is, and its impact on society. It is worth noting that, although we have seen exciting advancements of AI, we are still far from achieving AGI. In the next chapter, we dive deeper into deep learning, the area of AI that witnessed major development in recent years.
Algorithm: A set of instruction that tells the machine
how to achieve a certain purpose.
Artificial Intelligence (AI): The computerization of tasks that usually require human intelligence.
Machine Learning (ML): The area of AI that trains algorithms to perform tasks without specific instructions.
Deep Learning (DL): The branch of ML that centers around artificial neural networks to perform more complex tasks.