Artificial Intelligence (AI) will and is currently taking over an important role in our lives — not necessarily through intelligent robots — but a learning algorithm is implemented in many intelligent technologies. Also, Machine Learning and Deep Learning are contemporary important terms in Computer Science. But those AI-related terms are often mixed up or falsely taken as synonyms, which will be clarified in the following.
The word “intelligence” alone is quite hard to define. One can try it through probably the most popular method: The Turing Test. It argues that intelligence can be identified behavior-based. For instance, regarding a chat-bot, one could say: If it is undistinguishable if the chat partner is a human or computer, the computer can be entitled as “intelligent”, even if it is just an imitation game without any awareness on the computer’s side. Consequently, intelligence has not necessarily something to do with human intelligence. The term Artificial Intelligence was primarily introduced by John McCarthy in 1956 offering a seminar with this as a title. He is therefore often referred to as the Father of AI. He stated: “The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it” and therefore sets a first stone in characterizing Artificial Intelligence. Initially, Machine Learning was not separated from the field of AI, which changed in the 1990s: The scientists started to tackle practical problems and went away from symbolic approaches regarding intelligence. The term of Deep Learning appeared in the year 2000 for the first time describing an Artificial Neural Network.
What is Artificial Intelligence?
Everyone might have some applications in mind coming from utopias presented in film and fiction or media. AI is basically working with a goal, which is trying to enable machines to make decisions. As already mentioned, the word intelligence can be misleading. Therefore, we now want to go back to the basics trying to bring the fundamental idea of these technologies to you by using examples. One popular example is using oranges and apples. The goal is to teach the machine what an apple and an orange look like and enabling it to separate them. Each fruit has certain features, which have to be told to the algorithm: An apple is red or green, whereas an orange is orange. It has a bumpy surface, while the apple is smooth. Translated to English, you implement in the algorithm: “If something is red or green, is round and has a smooth texture, you call it an apple” and “If something is orange, round and has a bumpy texture you call it an orange”. And this is the first step one must take when it comes to programming an AI-powered software. If the software now recognizes the mentioned features, it can give the output “orange” or “apple”. As a code it looks like this:
In this code certain features of oranges and apples are defined
We can set: Artificial Intelligence means enabling a machine to think and mimic human behavior as it is now possible to take its own decisions.
#machine-learning #artificial-intelligence #deep-learning #celu #deep learning
