Did you know? By 2022, the global ML market is expected to be worth $8.81 billion. It is true that machine learning and AI will drive innovation in various industries in the years to come. Want to know how? Or What will be the future of machine learning and AI? Here are some points that say what’s in store for machine learning as it continues its growth trajectory. It is a good idea to hire AI developers to develop innovative solutions with machine learning. Hiring a top-notch machine learning development company in India can help corporations streamline their operations and stay competitive in the marketplace. https://bit.ly/3zl85FF

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Future of Machine Learning: Ways ML and AI
Will Drive Innovation & Change
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Did you know?? By 2022, the global ML market is expected to be worth $8.81 billion.
It’s not a surprise that Arti몭cial Intelligence (AI) and Machine Learning (ML) are two of the top
buzzwords in today’s technological world. But, how will the two technologies create innovation
and change in the near future?
Do you have the answer?
If not, continue reading to learn why AI and ML are two of the most promising technologies that
will drive innovation and change in the coming years.
Firstly, let’s start with Machine Learning facts & stats for 2021 so that it is easy for us to depict the
future.
Varun Bhagat - December 31, 2021  0
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2. In fact, the top arti몭cial intelligence and machine learning use case in 2021, at 57 percent, is
improving customer experience. Arti몭cial intelligence and ML can help businesses enhance a
variety of processes.

3. So, will it be the same in 2022 & Beyond?
Well, it may not be the same!
But it is also true that machine learning and AI will drive innovation in various industries in the
years to come.
Want to know how? Or What will be the future of machine learning and AI? Here are some points
that say what’s in store for machine learning as it continues its growth trajectory:
How Machine learning and AI Will Drive Innovation in 2022 and Beyond?
Machine learning models help detect patterns to provide insights. However, keeping data private
and protecting it through a secure, federated system will be a top priority.
Using federated learning, individual users can train their machine learning models with their data
without sharing anything with anyone else.
This means that they get to keep control over 100 percent of the sensitive information, so it’s not
leaked or breached.
Furthermore, 73% of businesses in the United States plan to use more arti몭cial intelligence and
machine learning (AI/ML) in cybersecurity tools this year,
1. Increased Commercial Applications For “Federated ML”
“

4. Image Source: Helpnetsecurity
The privacy-preserving capabilities of Federated Learning will provide companies with more
opportunities for innovation.
Before going deep, what is Hyper-Personalization?
Image Source: PGS-Soft
Machine learning will allow retailers to o몭er customers hyper-personalized experiences through
email marketing, online shopping, and more.
For example, by using machine learning in conjunction with product recommendation
algorithms, an eCommerce website can do the following:
Quickly identify new products that might appeal to its users based on past purchases or other
data
Identify the ‘next best o몭er’ for a particular product or service, even if it’s on another website.
Highlight new products that are similar to existing ones based on customer preferences
Besides, ML with AI-based chatbots will let companies communicate with customers more
e몭ciently and e몭ectively. Also, there is no denying the future of machine learning in retail will be
exciting.
According to Markets And Markets, the arti몭cial intelligence market in healthcare is estimated to
increase at a CAGR of 46.2 percent from 2021 to 2027, rising from USD 6.9 billion to USD 67.4
2. Hyper-Personalization Within E-Commerce
“
3. Promising AI Applications Within The Health Sector
“

5. increase at a CAGR of 46.2 percent from 2021 to 2027, rising from USD 6.9 billion to USD 67.4
billion by 2027.
Machine learning and AI can be leveraged for applications such as:
Personalized treatment and care
Big data analytics and insights
Electronic health records (EHRs)
Drug discovery
Imaging diagnostics
Also, there’s a rise in the use of the Internet of Things (IoT) and wearable devices to collect and
analyze health and 몭tness data, which is subsequently used with machine learning algorithms for
healthcare.
Did you know? Sixty-몭ve percent of people aged 25 to 49 use voice-activated gadgets at least
once a day.
4. Better Assisted Search And Discovery On The Web
“

6. As a result, it’s no secret that demand for voice-based searches is increasing day by day. And to
satisfy such consumers’ needs, businesses have to invest more in technology like machine
learning and arti몭cial intelligence (AI) to improve web search and discovery.
For example, Google has upgraded its online shopping experience with ML algorithms that
provide product recommendations based on a user’s past purchases or searches.
And Amazon is using neural networks to add image recognition, scene labeling (e.g., bedroom,
bathroom), and sentiment analysis to its catalog. So, the future of AI and machine learning is
bright, and we can’t wait to see what’s coming up next!
Besides, it is a good idea to hire AI developers to develop innovative solutions with machine
learning.
Today, machine learning still requires humans to de몭ne what an acceptable result should look
like. For instance, a human has to de몭ne the criteria for recognizing objects in images.
But with self-learning systems, this task will become fully automated.
Also, AI services can collect their data and train their machine learning models without human
intervention.
The computing power of quantum systems increases exponentially over conventional computers.
By 2025, the market for quantum computing will have grown to $780 million, and by 2029, it will
have grown to $2.6 billion.
5. Fully Automated Self-Learning System
“
6. Surge in the Quantum Computing Applications
“

7. Image Source: Inside Quantum Technology
Quantum machine learning algorithms will outperform the machine learning algorithms used by
today’s AI services, including ML platforms like Google Cloud Machine Learning Engine and
Amazon Machine Learning.
This is because quantum systems can process massive amounts of data at once, which allows
them to make predictions and conclusions with fewer samples than would be required by today’s
machines.
Software development companies will have the ability to lower the number of lines in a code
required for deep learning networks.
For instance, Google’s TensorFlow project is open source and provides developers with the ability
to decrease the number of lines in a code required for deep learning.
Nowadays, it usually requires approximately 80-90 thousand lines of code to train a deep
learning model instead of millions of lines needed on traditional architectures. With software
development tools like TensorFlow, this task will be simpli몭ed.
Data security and privacy will also rise with increased machine learning and arti몭cial intelligence
solutions.
For instance, if private data like health or 몭nancial records are used with machine learning or AI
solutions, there’s the risk that hackers will exploit these systems to access information for their
gain.
So, to prevent this situation in the future, developers need to ensure that these services provide
authentication and authorization protections in addition to encryption techniques.
Although, there’s a need to strike a balance between protecting data and enabling the use of
machine learning and AI services. Besides, the future of arti몭cial intelligence and machine
learning holds a lot of promises.
Machine learning and AI will bring about an increased level of automation on the factory 몭oor.
7. Fewer Code Lines For Deep Learning Networks
“
8. Data Security And Privacy
“
9. Increased Automation On The Factory Floor
“

8. For instance, driverless vehicles are already being used in mining operations with the advantage
that they can operate without drivers who might otherwise be injured at dangerous work sites.
Moreover, robots equipped with machine learning and AI capabilities will perform a broader
range of tasks without guidance from humans. Also, The automation business is expected to earn
roughly 214 billion dollars in global revenue by the end of 2021.
There is no denying that virtual assistants, like Amazon’s Alexa and Google Home, are becoming
part of our everyday lives.
For instance, voice-based searches are used by roughly 40% of all internet users in the US and a
third of the population. And all indications are that it will gain in popularity, with a 9.7% growth
to 122.7 million users projected by 2021. (Source: Oberlo)
And, virtual assistants are gaining popularity among consumers because they allow customers to
order items or get information without going through additional steps.
This means that users will rely only on voice-based searches and commands. Also, virtual
assistants are the perfect solution for the “just a minute” level of customer service inquiries.
Moreover, chatbots will also create signi몭cant opportunities in terms of marketing and branding
by assisting customers throughout the entire customer journey without human intervention.
Machine learning and arti몭cial intelligence will increase smart machines, for example, those that
can automatically detect operational problems.
10. Improved Customer Experience Through Virtual Assistants/Chatbots
“
11. Rise Of Smart Machines With Active Learning Capability
“

9. In fact, this is already happening as manufacturers are now using machine learning algorithms to
monitor machinery through embedded sensors and identify signs of failure well before it occurs.
And, because active learning capabilities enable these systems to collect and analyze data in real-
time, they can provide a more detailed analysis of problems as soon as possible.
Manufacturers are already using autonomous robots to perform complex tasks associated with
production.
For instance, instead of having humans operate dangerous machinery, manufacturers now allow
robots to perform most tasks.
And, more often than not, these bots can scan barcodes or RFID tags to determine part locations
and requirements on the 몭y.
In addition, autonomous robots are also being used to transport goods from one section of a
manufacturing plant to another without human intervention.
Wrap Up!
These are a few of the most visible ways machine learning and arti몭cial intelligence may a몭ect all
industries. Yet, no doubt, there is still much to learn about how new technologies will impact the
way we do business.
Hiring a top-notch machine learning development company in India can help corporations streamline
their operations and stay competitive in the marketplace.
Categories: Blog • Customer Analytics • Customer Engagement • Editor's Pick • Enterprise Technology
63 views
Varun Bhagat
PixelCrayons
Varun Bhagat is a technology geek and works as a Sr. IT Consultant with
PixelCrayons, a web & software development company in India.He possesses
in-depth knowledge of mobile app development & web development
technologies and helps clients to choose the best platforms as per their needs.
Author Rank: 22
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12. Autonomous Robots That Will Perform Almost All Tasks Associated With
Manufacturing Processes
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