The Top 5 Artificial Intelligence Trends for 2022 - AI Continues to Be the Biggest Technological Revolution of our Age - Arm
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The Top 5 Artificial
Intelligence Trends
for 2022
AI Continues to Be the Biggest
Technological Revolution of our Age
1
The Top 5
Artificial Intelligence
Trends for 2022
2
The Top 5
Artificial Intelligence
Trends for 2022
3
Why do we continue to talk about AI? Because of one simple
fact—AI continues to be the biggest technological revolution
of our age. AI will continue to change our lives in ways we
cannot yet predict as business, academic and engineering
communities continue to understand, evolve and explore
the capabilities of this incredible technology. So, will 2022
be the year that we finally plateau in the exponential growth
AI has seen, or will it continue its rapid growth beyond the
boundaries of traditional computing? Here are five key
developments to watch.
The rise of devices with an ever-growing
list of AI enabled capabilities
AI Continues to Expand
AI has seen extraordinary growth over the past few years with great results. Most of the early
phases of this growth has been in cloud applications where it is presenting a level of maturity
and stability, enabling a step change in functionality and user experience for a diverse range
of applications. Its potential is only just being realized in areas such as healthcare, safety and
energy efficiency. Unlike other technologies, we believe AI is unique in its growth and it will
largely move past the trough of disillusionment and expand into new territories including the
rise of devices with an ever-growing list of AI enabled capabilities.
AI on the Edge and Endpoint—AI Goes Tiny
A recent MIT Technology Review survey carried out with Arm shows that cloud continues
to dominate AI deployment strategies, with 77% of respondents deploying cloud-based AI
applications. But the reality is that AI on the cloud is expensive and comes with security and
network latency issues. Distributing AI capabilities to billions of devices on the edge and
endpoint will give the fastest, most reliable, and most secure experience, and this migration
has already begun. The survey also showed 22% of respondents are deploying AI at the
edge and 33% on endpoint devices. AI on the edge will complement the cloud by enabling
distributed computing and AI capabilities across the vast networks of our modern world.
This will usher in an era of low-power, efficient and secure AI technologies on all ranges of
devices from the infrastructure to our homes and our pockets.
4
“BMost Cortex-M
processors also include
an integration kit which
allows designers to carry
out system level simulations
out-of-the-box, supporting
Mentor Modelsim”
Dr. John Doe Data Engineer at Arm
Software: Taking AI Everywhere
—The Democratisation of AI
A huge part of the success of AI so far has been due to the software development community
which adapted and started to develop AI at an incredible pace. Modern software development
is complex and relies on an infrastructure of knowledge, examples, standards and tools.
It’s been amazing to watch the software community retool around AI. The community
continues to develop open standards and frameworks which support a vast range of AI use
cases, ensuring a continued pace of innovation. Tools like the various AutoML endeavours will
continue to make AI development easier, faster and more accessible. As this infrastructure
matures, the pace of AI adoption will continue to accelerate.
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“ AI, like many revolutionary The Year of MLOps
technologies before it,
While the development of various AI tools and frameworks has helped unlock the potential
has grown so rapidly that and unprecedented growth of AI, it also brings a level of complexity to the deployment of
regulations have not yet AI. The reality on the ground today is that while many continue to work on AI, very few are
caught up. ” able to deploy their technology effectively and at scale. This is where MLOps comes in, a set
of practices and tools for the deployment of AI, like DevOps for software development and
deployment. MLOps brings much needed simplicity, efficiency, automation and streamlining
for the development and deployment of AI. While it has been in place for a few years now,
with AI automation requirements growing in the past couple of years, MLOps will now be
adopted by many companies and forms a critical part of scaling AI in the market.
AI Ethics
AI, like many revolutionary technologies before it, has grown so rapidly that regulations
have not yet caught up. Recently we have seen more practical progress on regulation of
AI so it does not violate ethical standards as it continues to become more ubiquitous.
Greater dialogue between governments and the technology industry and between
technology companies themselves remains critical. However, overregulation has the potential
to stifle AI from reaching its potential, so the key is in finding the balance and focusing on
the most practical areas of concern. With the current focus on data privacy and security
standards, we are on the right track. Companies have also started greater standardization
and bench marking and this will also be key to sharing a common set of practices to ensure
ethical AI design and deployment.
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© Arm Ltd. 2022
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