Science Of Intelligence
Modern Computer Science technologies like artificial intelligence, machine learning, data science and big data have become the buzzwords which everybody talks about, but no one fully understands.
People often get confused by complex concepts in AI, ML and data science. It is somehow very hard to understand the difference between them and how there are being used in real-world projects.
"Artificial Intelligence has been around for a long time – the Greek myths contain stories of mechanical men designed to mimic our own behavior. Very early European computers were conceived as “logical machines” and by reproducing capabilities such as basic arithmetic and memory, engineers saw their job, fundamentally, as attempting to create mechanical brains."
"Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning" in 1959 while at IBM. A representative book of the machine learning research during the 1960s was the Nilsson's book on Learning Machines, dealing mostly with machine learning for pattern classification."
"Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases). Data mining uses many machine learning methods, but with different goals; on the other hand, machine learning also employs data mining methods as "unsupervised learning" or as a preprocessing step to improve learner accuracy. "
"During "small data" days, data was difficult and tedious to collect. Only the data that was needed to answer a specific question was collected. But we have now entered the world of "big data," where data is constantly collected on everything and everyone. We have an unprecedented amount of data, and classic statistical approaches often do not work on the type of data we have."
There are so many interesting topics introduced and discussed by genius computer scientists. We can try to fit them into following 6 categories:
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Computer Vision ( Pattern Recognition, Image Processing )
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Natural Language Processing ( Speech Recognition, Dialog Systems)
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Cognitive & Reasoning
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Robotics (Control, Motion Planning, Scheduling)
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Algorithmic Game Theory
All of these categories should be coved under a big umbrella:
Science of Intelligence