World’s first AI major students at Carnegie Mellon become multidisciplinary specialists

education Institute’s around the world
are rushing to establish degrees and programs specializing in artificial
intelligence and Carnegie Mellon University in the US has introduced the
world’s first AI department our Oh Sooyoung has the story Jennifer Bowen isn’t a computer
scientist but she’s learning to work with artificial intelligence by teaming
with students from the machine learning department so we’re trying to actually
take patient’s own cells and bio-print them into new organ it has so many
factors so many variables that go into the process that the human brain is just
it’s very difficult for us to optimize so we’re using machine learning as a way
to help us to tune the perfect way to print these organs so that they’re
repeatable and have high fidelity each time this is one of the ways that
Carnegie Mellon University has been using education and AI to produce
innovative research and new technology with the proliferation of AI and its
potential to transform all sectors of society governments over the past year
have been rushing to set up university courses and graduate schools in the
field many are looking to the u.s. as an example as the country is perceived to
have the highest proportion of AI professionals compared to demand from
businesses many attribute the country’s success to the early adoption of
research programs in the field Carnegie Mellon in 1958 offered the first
University level course in computer programming it later created the first
PhD program in robotics as well as the world’s first machine learning
department the school has produced many world-class researchers and spin-off
firms that have driven innovation across a wide range of sectors this is still a
relatively new field and the students who go into the major in AI
tend to be ones who are more forward-thinking you know employment in
artificial intelligence doesn’t have quite as long a track record as
employment in other areas so some of the students are a little wary about what
the job prospects are but the ones who are willing to take that chance I think
are going to be very well rewarded in addition to courses on machine learning
robotics and decision making the school has been encouraging multidisciplinary
collaboration a big part of this is actually learning about the you know
information about the problems themselves and domain information from
the sciences to try to understand them better and see how we can apply machine
learning to them we’re seeing a global talent search for young experts in
artificial intelligence but that’s not to say everyone needs a rigorous
knowledge of coding the way forward seems to be collaboration was young a
young news Pittsburgh

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