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the business potential of artificial
intelligence has been on the horizon for
a long time but many businesses have
found AI hard to implement or even
imagined however thanks to some key tech
breakthroughs that future is now the
term artificial intelligence has been
around since 1956 scientists quickly
figured out that it was more efficient
to teach computers to learn than to
program them with every single skill
needed to complete a given task this
became known as machine learning deep
learning a subset of machine learning
that uses neural networks a set of
algorithms modeled on the human brain
enabled AI to tackle even bigger
problems nowadays we hear all the buzz
around machine learning use cases such
as voice recognition improve medical
diagnosis and even self-driving cars but
machine learning and deep learning in
particular have enormous potential for
the entire economy so why hasn't every
business already started using AI for
one a I can be super hard to implement
alone envisioning use cases hiring a
team to implement and then figuring out
how to integrate that AI into a
business's workflow can be a complex
undertaking
second it's computationally intensive
and expensive buying and running the
compute power necessary to implement
deep learning can be cost prohibitive
Amazon Web Services is uniquely
positioned to take on both of these
challenges AWS uses the same advanced
machine learning algorithms powering
everything from search recommendations
on amazon.com to voice interactions with
Alexa to remove the complexity of
developing AI applications AWS developed
the Amazon sage maker platform making it
easy to get started with and scale
machine learning users can select from
pre-installed algorithms that have been
optimized to perform ten times better
and label your data to get to ground
truth for training Amazon sage maker
also takes advantage of new techniques
such as reinforcement learning crucially
it allows agnostic support
developers have the flexibility to use
whichever deep learning frameworks they
are most comfortable with including
tensorflow
hi torch and Apache MX net to meet the
computational demands and high costs of
machine learning Amazon ec2 p3 instances
harness the power of nvidia tesla v100
tensor core GPUs new p3 instances also
provide the fastest network throughput
by three times what this means is that
any business can accelerate machine
learning in the cloud with high
performance compute industry leading
companies are already using AWS to
achieve business breakthroughs for
example machine learning on AWS has
enabled a leading financial service
companies data scientists to train new
machine learning models in hours instead
of days or even weeks models that the
company's agents rely on like one that
helps them troubleshoot customer
problems can now be trained in as little
as 30 minutes in banking cyber security
risks are being mitigated major
financial institutions use machine
learning to flag fraudulent or
questionable activity and alert account
holders in real time in medicine drug
discovery is sped up scientists that
biotechnology companies have used AI
technology to make sense of genes in
clinical trials more quickly with the
help of algorithms machine learning has
the potential to revolutionize the way
we do business but it needs to be easy
to use thanks to tech breakthroughs like
these from Amazon Web Services
businesses of all sizes can utilize the
power of artificial intelligence to
maximize the present and stay one step
ahead of the future
you
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