We will be covering all the domains and concepts involved under the umbrella of
artificial intelligence. She will also be showing you a couple of use cases and
practical implementations by using Python. So there 's a lot to cover in this session
and let me quickly run you through today's agenda. 1950 was speculated to be
one of the most important years for the introduction of artificial intelligence. In
1950, Alan Turing published a paper in which he speculated about the possibility
of creating machines that think. Alan Turing created what is known as the Turing
test. This test is used to determine whether a computer can think intelligently like
a human being. AI started off as a hypothetical situation. Right now, it 's the most
important technology in today 's world. Everything around us is run through AI
deep learning or machine learning. AI covers domains such as machine learning,
deep learning, neural networks, natural language processing, knowledge-based
systems and so on.
AI is rapidly growing both as a field of study and as an economy. The term
artificial intelligence was first coined in the year 1956 by John McCarthy at the
Dartmouth Conference. AI is the theory and development of computer systems
able to perform tasks that normally require human intelligence. In a sense, AI is
a technique of getting machines to work and behave like humans. AI has reached
a stage wherein it can compute the most complex of complex problems in a matter
of seconds. Even though AI can not think and reason like humans, but their
computational power is very strong compared to humans. IBM Watson
technology was able to cross reference 20 million oncology records quickly and
correctly diagnose a rare leukemia condition in a patient. AI implements
computer vision, image detection, deep learning to build cars that can
automatically detect any objects or any obstacles and drive around without human
intervention. Netflix uses AI to create a personalized movie recommendation
engine for each of its users. Apart from Netflix, Gmail also uses AI on an
everyday basis to classify emails as spam and non-spam.
artificial intelligence. She will also be showing you a couple of use cases and
practical implementations by using Python. So there 's a lot to cover in this session
and let me quickly run you through today's agenda. 1950 was speculated to be
one of the most important years for the introduction of artificial intelligence. In
1950, Alan Turing published a paper in which he speculated about the possibility
of creating machines that think. Alan Turing created what is known as the Turing
test. This test is used to determine whether a computer can think intelligently like
a human being. AI started off as a hypothetical situation. Right now, it 's the most
important technology in today 's world. Everything around us is run through AI
deep learning or machine learning. AI covers domains such as machine learning,
deep learning, neural networks, natural language processing, knowledge-based
systems and so on.
AI is rapidly growing both as a field of study and as an economy. The term
artificial intelligence was first coined in the year 1956 by John McCarthy at the
Dartmouth Conference. AI is the theory and development of computer systems
able to perform tasks that normally require human intelligence. In a sense, AI is
a technique of getting machines to work and behave like humans. AI has reached
a stage wherein it can compute the most complex of complex problems in a matter
of seconds. Even though AI can not think and reason like humans, but their
computational power is very strong compared to humans. IBM Watson
technology was able to cross reference 20 million oncology records quickly and
correctly diagnose a rare leukemia condition in a patient. AI implements
computer vision, image detection, deep learning to build cars that can
automatically detect any objects or any obstacles and drive around without human
intervention. Netflix uses AI to create a personalized movie recommendation
engine for each of its users. Apart from Netflix, Gmail also uses AI on an
everyday basis to classify emails as spam and non-spam.
