The Little Story Behind Artificial Intelligence And Machine Learning
Artificial Intelligence & Machine Learning
Hello Data and AI enthusiasts,
Artificial intelligence is used everywhere and in every field now, from self-driving cars to recommendation systems, to chatbots, to facial detection and recognition, and these are just a few examples of many.
There are so many more examples, AI is being used daily in the world, and in our day-to-day lives. It has become such a big part of our lives that we don’t even notice it, but it is almost always there hidden and wrapped in other algorithms.
AI was founded as an academic discipline in 1956 according to wikipedia and experienced several years of optimism followed by disappointment and loss of funding - the famous event known as AI winter in AI history. This interest gets renewed in the beginning of the 21st century with Machine Learning, ML for short, a sub-field of AI.
Machine Learning
Machine learning is the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data.
-Oxford Languages
There is a widely used and widely known sub-field of Machine learning, I am talking obviously about Deep Learning.
And this is what the two components, Machine Learning and Deep Learning represent in reference to Artificial Intelligence.
Machine Learning and Intelligence
The learning and the adaptation nature is what makes or characterizes Intelligence. And since Machine Learning does that, then it is, or the processus is considered to be intelligent.
Another component of Intelligence is reasoning, and in this case, reasoning could be seen here as using and manipulating acquired information and knowledge to answer a new question. And once again, Machine Learning also does that.
Machine Learning and Statistics
Machine Learning is drawn from Statistics and Statistical models. The difference between Machine Learning and Statistics is their purpose.
According to Dsimcha’s answer on stats.stackexchange about the two cultures Statistics vs. Machine Learning :
Statistics emphasizes inference, whereas machine learning emphasized prediction. When you do statistics, you want to infer the process by which data you have was generated. When you do machine learning, you want to know how you can predict what future data will look like with reference to some variable…the two overlap…
To check more answers on the subject
What’s important to keep in mind about this is that the two indeed overlap and the major difference between the two is, let’s say for now, about their purpose. And they are not exactly the same thing.
Have a wonderful week,
-Hind