What is Artificial Intelligence, Machine Learning and Deep Learning?
In recent years, artificial intelligence (AI) has been a widely talked topic of intense hype. We are promised a future with robots, intelligent houses, self-driving car and much more, just as seen in many science fiction movies. However, you may be also hearing about other terms, such as Machine Learning (ML) and Deep Learning (DL), that are used interchangeably with AI. Even though they are related, each one have their specific definition, which will be covered in this article.
What’s the difference between AI, ML and DL?
A simple but concise definition of AI is coined by John McCarthy in 1956:
“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.”
Even though it seems general, this definition includes processes like planning, recognizing sounds and objects, learning and problem-solving. AI encloses machine learning and deep learning processes, but that also includes many more approaches that don’t involve any learning.
On the other hand, Machine Learning is related to algorithms that have the ability to learn without being explicitly programmed. This paradigm acquires their own knowledge by extracting patterns from raw data. Depending of what you are trying to accomplish, different ways to learn from the data may be applied, such as Supervised Learning, Unsupervised Learning, Reinforcement Learning and Deep Learning.
Finally, Deep Learning is a subset of Machine Learning that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning utilizes neural networks which, just like the human brain, contain interconnected neurons that can be activated or deactivated.
History of Artificial Intelligence
It is possible that you have already heard about artificial intelligence (AI) these days. However, it is good to remember that this term is not something new.
In 1950, Alan Turing questioned if machines could think and then proposed the Turing Test, where a human questioner asks a series of questions to another human and a machine. After some time, the human questioner tries to decide which terminal is operated by a human and which one is the computer. If the machine could carry on a conversation that was indistinguishable from a conversation with a human being, then it was reasonable to say that the machine was “thinking”.
The Dartmouth Conference of 1956 was the event that initiated AI as a research discipline. It was the moment that AI gained its name, its mission, its first success and its major players, and is widely considered the birth of AI. The years after the Dartmouth Conference were the golden years of IA. The programs developed were simply astonishing and a lot of investment was made. For example, in 1959 the MIT AI lab was set up, in 1961 the first robot is introduced into GM’s assembly line and in 1965 the first chatbot, called Eliza, was created.
In the early seventies, AI was subject to critiques and financial setbacks. Due to limited computer power and memory, most applications could not be developed and the high expectations raised in the golden years turned into disappointment, causing the funding for AI disappear. This period is known as AI winter.
Fortunately, the advances in technology in the first decade of the 21st century enabled the development of faster computers, higher storage capacity of memories and larger access to data (known as big data). Thus, the usage of artificial intelligence begins to hype once again and the development of AI algorithms flourishes: In 2009, Google starts building a self-driving car. In 2011, IBM Watson beats jeopardy champions. In 2015, Elon Musk and others announced a 1 billion dollars donation to open AI.
As you can see, AI is not new but the advances are progressing at an exponential pace, enabling the AI hype once again.
References
https://bit.ly/2QoaDLB
https://bit.ly/2L1mLBo
https://bit.ly/2Z0jkEN
https://medium.com/iotforall/the-difference-between-artificial-intelligence-machine-learning-and-deep-learning-3aa67bff5991
https://medium.com/datadriveninvestor/what-is-machine-learning-55028d8bdd53
https://www.investopedia.com/terms/d/deep-learning.asp
https://en.wikipedia.org/wiki/History_of_artificial_intelligence
https://singularityhub.com/2018/06/20/why-we-need-to-fine-tune-our-definition-of-artificial-intelligence/
