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an application of artificial intelligence (AI) that provides systems the
ability to automatically learn and improve from experience without being
is intimately human. Helpless infants learn from their environment and those
around them and eventually become speaking, mobile young people that can
interact sensibly with others. They achieve this by learning as they go.
beings are in the process of building machines that will eventually act
autonomously and with human-like intelligence. In order to achieve this aim, we
need machines to, like infants, learn about the world around them on their own.
machine learning, programmers don’t create step-by-step rules for machines to
follow. They allow machines to learn and come to conclusions on their own. With
this approach, machines gather information on their own and in the process they
become more accomplished.
words, we are expecting machine learning algorithms to learn like babies from a
world they know nothing about.
learning neural networks are a subset of machine learning. Neural
networks are a set of algorithms, modeled loosely on the human brain.
They are designed to recognize patterns and interpret sensory data like images
computer neural networks that mimic the human brain teach us more about the
human brain? Well, scientists know that a deep learning neural network can be
just as good as human beings at identifying objects in pictures. The question
is, how does deep learning do it?
It seems deep
learning does it the same way the human brain does. This was the discovery of assistant
professor of psychology, Daniel Yamins, and the team at Stanford
NeuroAI Lab. This team uses deep learning systems to better understand the
Yamins and his team exposed their deep learning network to images and waited
for it to identify the images. When the system had completed the task, the
scientist compared how the deep learning system managed the task with how a
human brain does it.
followed next, was one of those wow moments for science and scientists: they
discovered the deep learning system and the human brain follow the same route
to solve problems. In fact, the computations the deep learning system performed
matched activity in the brain’s vision-processing circuits substantially better
than any other model of those circuits.
This is an
exciting discovery indicating that this kind of research might eventually lead
scientists to discover how the brain works.
instance, deep learning systems could help scientists understand why the vision
circuits of babies develop specific patches of neurons that cluster together. Specific
patches works for specific images, for instance, there are patches to recognize
not exactly clear why the brain forms these patches since these patches are not
necessary for the brain in order to recognize faces.
scientist think they can learn more about why the brain is laid out like this,
and what advantages there might be in this layout, by building deep learning
system like this one at Stanford.
just one puzzle about the brain that might be solved through machine learning.
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