6 Emerging AI and Machine Learning Trends to Watch in 2022

If you want to start a new profession in Artificial Intelligence (AI) or Machine Learning (ML), you need keep up with the latest AI and Machine Learning developments. Nearly everyone has heard of AI and machine learning these days. Even individuals who are unfamiliar with these terminology are exposed to new technology on a daily basis. According to research, AI is embedded into 77 percent of the products we use today. AI is the driving force behind many modern technology conveniences that are now part of our daily lives, from a slew of "smart" devices to Netflix suggestions to Amazon's Alexa and Google Home.
Artificial Intelligence and Machine Learning have a wide range of applications.

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For example, IBM's Chef Watson could make a quintillion different combinations with just four components. In addition, AI-powered virtual nurses like "Molly" and "Angel" are already saving lives and lowering costs, and robots are aiding with a variety of treatments, from less invasive procedures to open-heart surgery.
 


1. The Future of Machine Learning-

• Increasing Use of AI and Machine

Learning-According to reports, 52 percent of businesses have accelerated their plans to include AI in some way. AI adoption will continue to expand as a result of the benefits AI and machine learning provide in business analysis, risk assessment, R&D, and cost savings.
 
Many firms that use AI and Machine Learning, however, do not properly comprehend these technologies. In fact, according to a recent survey, 64% of respondents believe their staff does not fully trust or understand AI.
 
While the advantages of AI and machine learning are becoming more apparent, businesses will need to step up and hire individuals with the necessary abilities to put these technologies into practice. Some have already made significant progress. According to a recent KPMG poll of Global 500 firms, most anticipate expanding their investment in AI-related skills by 50-100 percent over the next three years.
 

• Transparency Trends

in AI-Despite its widespread adoption, AI has trust difficulties. Businesses will seek to use AI systems more confidently as they intend to expand their use of them. After all, no one wants to put their trust in a system they don't comprehend.
 
As a result, in 2021, there will be a stronger push for AI deployment that is transparent and well-defined. While businesses will struggle to grasp how AI models and algorithms work, AI/ML software providers will have to make complex ML solutions more understandable to users.
 
The roles of experts who work in the trenches of programming and algorithm development will become increasingly crucial as transparency becomes a significant conversation in the AI area.
 
 

• Rising Emphasis on Data Security and Regulations-

The future currency is data. In other words, it is the most valuable resource that businesses must safeguard. With AI and machine learning brought into the mix, the amount of data they handle and the risks associated with it will only grow. Today's enterprises, for example, back up and store vast volumes of sensitive personal data, which is expected to become a growing privacy problem in 2022.
 
GDPR and, more recently, the California Consumer Privacy Act — both of which went into force in 2020 — have made privacy violations extremely costly. The Information Commissioner's Office (ICO) fined British Airways and Marriott International nearly $300 million in 2019 for GDPR violations.
 
Companies will need data scientists and analysts on hand to stay compliant and ahead of AI and Machine Learning trends as the need to meet these standards grows.
 

• The Overlap Between AI and IoT-

The distinctions between AI and IoT are becoming increasingly hazy. While each technology has its own merits, when combined, they provide better and more unique options. In fact, we have smart voice assistants like Alexa and Siri because of the convergence of AI and IoT.
 
So, why do these two technologies complement one other so well? IoT can be compared to the digital nervous system and AI to the decision-making brain. IoT systems become more sophisticated thanks to AI's capacity to quickly extract insights from data. According to Gartner, by 2022, more than 80% of enterprise IoT projects will use AI in some form, up from just 10% currently.
 
This AI and Machine Learning revolution provide software developers and embedded engineers with yet another opportunity.
 

• Augmented Intelligence is on the Rise-

The growth of Augmented Intelligence should be a welcome trend for individuals who are concerned about AI destroying their jobs. It brings together the best qualities of humans and technology, allowing businesses to improve their workforce's productivity and performance.
 
Gartner expects that by 2023, 40% of big enterprise infrastructure and operations teams would employ AI-augmented automation, resulting in increased efficiency. To get optimal results, their staff should be skilled in data science and analytics or have the option to upskill on the latest AI and ML technologies.
 

• Hyper Automation-

Hyper automation is another growing AI and Machine Learning technology that is an effective approach to improve customer service and speed up numerous procedures. Machine learning, artificial intelligence (AI), cognitive process automation, and other advanced technologies are all used to fuel hyper-automation. Aside from boosting customer service, hyper-automation can aid in the completion of other critical activities, such as system integration and organization, as well as increasing worker productivity.
 
The Future of AI and Machine Learning-
The New Year has here, and we're excited to see what the future holds for AI and Machine Learning, as well as the advances they will bring. Despite their age, these technologies are still in their infancy. If you're a tech professional trying to keep up with the latest technological advances, now is the time to do so. Our comprehensive AI Courses will teach you everything you need to know about how AI can help you succeed in your profession, as well as keep you up to date on machine learning's future.

Who is the father of machine learning?

Geoffrey Everest Hinton CC FRS
Geoffrey Everest Hinton CC FRS FRSC (born 6 December 1947) is a British-Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks.

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