In this technological era, Artificial Intelligence and Machine learning are now becoming hot topics. We can relate technology with artificial intelligence and machine learning because nowadays in AI is implementing in every gadget and technology. The demand for these is rising day by day and bringing a lot of innovations which we can’t deny. AI technology is changing everything which is beyond our imaginations. As per the research 77% of the devices that we currently use have AI technology build into them.
We can’t even imagine that AI and Machine Learning transformed many
businesses and help to generate revenue in many ways even than before. We
becoming advanced only because of these technologies. If we estimate the
revenue of these technologies then we get around $156.5 billion generated
worldwide, a growth of 12.3% over the previous year, as per IDC
research.
The AI and Machine Learning industry is currently rising at a rapid pace
and providing enough growth opportunities for organizations to make the
requisite transformations. According to Gartner, about 37% of all
businesses are using AI in some form, and by 2022, it is expected that around
80% of new technologies will be focused on AI and machine learning.
Many new technologies and Machine Learning Trends are expected to emerge
in 2021. There are many applications of Machine Learning in the industry such
as its incorporation with the Internet of Things, and its more widespread use
in industries like cybersecurity, finance, and medicine.
So here we discuss the emerging Artificial Intelligence and Machine
Learning technology trend to watch in 2021:
AI & ML powered Hyperautomation
Gartner has described Hyperautomation as a new technology trend.
Forrester refers to it as "Digital Process Automation," while IDC
refers to it as "Intelligent Process Automation." It brings together
the best technology for automating, simplifying, finding, designing, measuring,
and controlling workflows and processing around the Industry.
Hyperautomation relies heavily on artificial intelligence (AI) and
machine learning (along with other technologies like robotic process automation
tools). Hyperautomation successful initiatives cannot rely on static bundled
applications. The automated business processes should be able to adjust to
changing conditions and respond quickly to unexpected situations.
That's where AI, machine learning, and deep learning come into play. By
incorporating these algorithms and models, as well as the automated system's
data, the automated system will be able to evolve over time and respond to
changing business processes and requirements.
Use of AI for Cyber Security Applications
If we see today, Artificial intelligence and machine learning are
rapidly being used in cybersecurity applications for both corporate systems and
home security. Cybersecurity system developers are constantly working to update
their technology to keep up with continuously changing threats such as malware,
ransomware, DDS attacks, and more. Artificial intelligence (AI) and machine
learning technologies can be used to better classify risks, even versions of
previous threats.
AI-powered cybersecurity tools can also collect the data from a company's
own transactional processes, communication networks, digital activity, and
websites, as well as data from public sources, and use AI algorithms to
recognize trends and recognize the threatening activity, such as detecting
unusual IP addresses and possible data breaches.
According to IHS Markit, AI in home security systems is currently
limited to systems that are integrated with a user's video cameras and intruder
alarm systems that are integrated with a voice assistant. However, according to
IHS, AI will be used to build smart homes in which the device learns about the
occupants' preferences and choices, improving its ability to detect intruders.
The Intersection of IoT & AI/ML
The Internet of Things has been a hot topic in recent years, with market
research firm Transforma Insights predicting that by 2030, the global IoT
market will have grown to 24.1 billion devices, producing $1.5 trillion in
revenue. AI/ML is being deeply entangled with IoT. Artificial intelligence
(AI), machine learning (ML), and deep learning (DL) are already being used to
make IoT devices and services smarter and more secure. However, the benefits
flow both ways given that Artificial Intelligence and machine learning need
vast amounts of data to function properly, which is exactly what networks of
IoT sensors and devices provide.
For example, IBM's China Research Lab has developed Green Horizons. This
project aims are to reduce pollution levels to breathable levels. This can be
accomplished by the use of an IoT network in which sensors collect emissions
from cars, pollen levels, airflow direction, temperature, traffic levels, and
other data, and then use machine learning algorithms to determine the best way
to minimize these emissions. The convergence of machine learning and the Internet
of Things can also be seen in the field of smart vehicles, where self-driving
cars must be extremely precise and all of their components must interact in
milliseconds on the road.
By 2022, Gartner predicts that more than 80% of enterprise IoT projects
will use AI and Machine Learning in some way. This is much more than the 10% of
projects that are actually using it.
AI Engineering
Everyone has heard of software engineering, but now AI Engineering is
gaining popularity as a career! This is a significant advancement since the
industry's application of AI and Machine Learning has been haphazard and ad
hoc, without any regulations of best practices. As a result, Gartner predicts
that only 53% of AI and ML ventures will make it from prototype to full production
in a business, while the remaining 47% is likely to fail.
A disciplined AI Engineering strategy for a company ensures that a
machine-learning algorithm provides great efficiency, reliability, and
scalability, ensuring a return on the investment in AI. This involves a strong
emphasis on DataOps, ModelOps, DevOps, and so on, with artificial intelligence
projects being a part of a company's overall DevOps plan rather than ad hoc
activity in a few projects.
Conversational AI
Automated messaging and speech-based applications depend on
conversational AI technology. It can be used to interact like a person by
acknowledging speech and text, understanding a customer's meaning, deciphering
various languages, and responding in a human-like manner. Chatbots and smart
assistants like Amazon Echo and Google Home are examples of conversational AI
devices.
Developers, on the other hand, must discuss a number of improvement
areas. Speech recognition and automatic text recognition are two challenges
that require a high level of natural language processing expertise. These
limitations can be overcome in a variety of ways, one of which is to
classify/segment various words (For example, allowing casual words to be used
to place an order in a restaurant app).
The Rise of Augmented Intelligence
For those who are still worried about AI cannibalizing their jobs, The
rise of augmented intelligence can be pleasing development for them. It
combines the best qualities of humans and technology, allowing businesses to
improve the efficiency and performance of their workers.
According to Gartner, 40% of infrastructure and operations teams in
large organizations would use AI-assisted automation by 2023, resulting in
improved productivity. Of course, in order to achieve optimal efficiency, their
employees should be trained in data science and analytics or updated on new AI
and ML technologies.
Conclusion
In this year 2021, These technological trends will play a major role in the development and this will bring new innovations and opportunities.
Apart from this if you want to start your career in Machine Learning and want to do a
course then join “Nearlearn”. Nearlearn is the Foremost Machine LearningTraining Institute in Bangalore and also the best Artificial IntelligenceTraining Institute. They provide both online training and classroom training
facilities. After completion, of course, they help you to get placement in
various companies.
For more information contact
us:
Visit: www.nearlearn.com
No comments:
Post a Comment