Artificial Intelligence and Machine Learning are picking great pace in the pandemic era largely due to two main reasons. Firstly, organizations are moving into a local village model where everyone can work in satellite dens without losing touch with their colleagues—this is called virtualization of the remote workplace, also referred to as Hybrid working models. Secondly, a majority of the mundane bottom level managerial works have been completely outsourced to robotics and automation that are now called Robotic Process Automation or RPA. These new developments are gathering massive investments around the world, and that’s why I thought it would be best to provide a larger picture around the recent developments that would help you get closer to the industry requirements with the best Artificial Intelligence and machine learning courses.
Here is the list of the top AI ML developments that you should know happened in 2022.
AI in DNA and RNA Research Gets Biggest Funding this Year
It has been a great year for companies invested in bioinformatics and genome research. Top investors such as Microsoft’s M12, Madrona Venture Group, Third Kind Venture Capital, Dynamk Capital, and Empire State Development’s venture capital arm, New York Ventures heavily backed the startup ecosystem involved with building AI ML platforms for the biotechnology industry.
In recent months, we have seen a rampant adoption of AI and machine learning algorithms for highly specific RNA splicing modules that could solve the perennial problems and challenges associated with the understanding of oncology, neurology, muscular dystrophy, genetics, and drug re-engineering. With advanced knowledge of AI ML in healthcare, we can expect to find accurate answers to diseases for which we are yet to get medicines or therapy.
AI in Banking and Digital Payments
The global AI in Fintech market is another major industry where you could potentially find lot of opportunities after completing your Artificial Intelligence and machine learning courses.
Merely going by the recent statistics, the machine learning domain within fintech has expanded to 18% during the last 18 months or so and is expected to be the second largest destination for AI investments, projected to reach $18000 million USD in annual revenue by 2027.
What are the common applications of AI ML in Fintech?
Well, the first application is digital banking where large sized global and national banks are adopting virtual assistants and chat support systems to deliver highly personalized experiences. Secondly, banks are using AI ML tools for solving critical issues in their front-end and back-end operations, including those related to Cloud modernization, and security posturing. Thirdly, the entire document processing operations have been outsourced to automated robotics-based tools that capture images, store data, and analyze them for KYC and other important tasks.
Right from personalized emails to tracking banking transactions, AI ML in Fintech has opened new doors of opportunities for everyone in the value chain of Big Data learning.
IT and Data Center Management
Just like Fintech, the IT industry too has been heavily proliferated by AI ML applications, and the new age concepts like Edge and Fog computing are making a swashbuckling impact on the entire ecosystem. Even startups in IT are adopting tools for automation of their IT migration, Cloud modernization, and Containerization. We are seeing a lot of impetus given to automated programming, data extraction, and mining and similar efforts are going on in the field of DevOps that involves building seamlessly connecting APIs and MSP management. Companies you can work for as an AI engineer in the IT industry are Cisco, Dell, Fujitsu, Huawei, Microsoft, Google, and Micro Focus.
Global Deep Learning Models
CNN, GAN, and RNN have transformed the way we look at digitization processes built specifically on AI Machine Learning platforms. The entire digital transformation concept runs on the three pillars of IT modernization – Cloud, Computing, and Connectivity. It would be a ubiquitous decision for any business development manager to look at AI, ML, and IOT / 5G connectivity as the lifeline of their operations, even as companies pick up new advancements in the fields of neural networking models to augment intelligence and develop cognitive intelligence for strategic decision making in their respective domains.
With barely a few months left in the year 2022, we can expect further inroads in the field of Artificial Intelligence and machine learning trends that would buck down the traditional concepts of IT, banking, education, healthcare management, and marketing through the internet.
So, training with AI ML is a superior professional domain today.