Blend360 is a world class marketing, analytics, and technology company that delivers the best results for our clients. Our primary focus is Data Sciences; leveraging data and applied mathematics to solve our clients' business challenges. Blend360 is known for our exceptional people, our get-it-done mentality, and delivering high impact and sustainable results. If you love to solve difficult problems and deliver results; if you like to learn new things and apply innovative, state-of-the-art methodology, join us at Blend360. Summary with focus on communication: Data Scientists at Blend360 work with business leaders to solve our clients' business challenges.

One of the most promising technologies in the past few years is composite AI. Companies will have an unmatched competitive edge now and in the future if they fully leverage the benefits of composite AI. It would be difficult finding an enterprise that isn't utilizing AI in 2022. In recent years, AI has expanded in popularity and accessibility, solidifying its position as a key component in the technological lexicon. Composite AI is something that is not yet immensely popular but is becoming increasingly important for successful AI deployments.

Technology has played a pivotal role in transforming how businesses operate, for the better and for the worse. The development of semiconductors and the computing revolution that followed changed the business landscape dramatically in a few decades. The next transformational change in business will be brought about by artificial intelligence. Artificial Intelligence or AI tries to mimic human intelligence with computing power. Complex statistical operations are applied to huge amounts of data to train computers to learn some aspects of human intelligence.

In an era of accelerated digitalisation, artificial intelligence (AI) and machine learning (ML) have fast become part of the IT infrastructure of many businesses. Consequently, how these technologies are being used to derive meaningful insights from vast quantities of data is maturing rapidly. "Early on, when organisations didn't have access to the computing power and zettabytes of data that they have today, AI was only springing up in pockets," says Vaidya JR, SVP and global head of data and AI at IT transformation specialist Hexaware Technologies, "The approach then was to see what AI could do for a company, without truly identifying a well-defined problem. Data science solutions were just a shot in the dark. "Organisations were struggling to put their data to effective use, which led to limited value generated and ineffectual business results," he adds. "You can crunch any amount of data, and create numerous models; it only adds value if there is a significant impact on the business.

Recently, businesses and organizations alike have been turning to ModelOps to solve business challenges. The framework of ModelOps works in effort to reduce manual work and increase productivity all around. Find out why ModelOps is in-demand and how SAS can help you propel in this growing area. A variation of DevOps, ModelOps is primarily focused on the management of operationalized artificial intelligence and decision models, from machine learning and optimization to linguistic and agent-based models. ModelOps is crucial for predictive analytics and allows quality analytics models to move through development to deployment as quickly as possible.

Organizations across industries are turning to data and analytics to solve business challenges. A survey by New Vantage Partners found that 91 percent of enterprises have invested in AI. However, the same study found that just 26 percent of these firms have AI in widespread production. Organizations are struggling to solve business challenges with AI. They find that building machine learning (ML) applications takes time and requires expensive maintenance and talent that's in short supply.

Content is always king, if you were to ask any seasoned media professional or publishing company. Whether the content is in the form of a movie, music album or digital news article, it has to be compelling to make the consumer want to spend time on it. At the same time, many companies are also realising that great content has to be distributed as widely as possible, and be personalised to the right audiences to capture their attention in today's competitive, on-demand world. To make their content travel as far as possible and gain as many readers or viewers as possible, these companies could do with a helping hand from artificial intelligence (AI). AsiaOne recently partnered AI company Neural Lab to create an automated personalised article recommender based on smart AI algorithms.

The term AI was coined back in 1956, and has come a long way from there, and has become more popular today. Cheers to all the massive amounts of data, advanced algorithms, and improvements in computing capability and storage. The growth of AI and Machine Learning has increased the demand for talented minds to help solve pressing business challenges faster and better. AI job market is booming and is expected to exceed $191 billion by 2024 globally, and AI is expected to create more than 2 million jobs across sectors. With attractive salaries, investing in upskilling oneself in the field, and understanding just the right AI learning path is surely the smart move to make.

This learning path is designed to help you prepare for the Google Certified Professional Machine Learning Engineer exam. Even if you don't plan to take the exam, these course will help you gain a solid understanding of how to implement machine learning on Google Cloud Platform.

My name is Guy Nadivi and I'm the host of Intelligent Automation Radio. Our guest on today's episode is Steven Hall, President of ISG, a leading global technology research and advisory firm that is committed to helping organizations achieve operational excellence and faster growth. Steven is an industry expert on cloud, automation, and outsourcing, with a focus on innovation that drives significant cost savings. He's advised such firms as United Airlines, Symantec,and Motorola. And, with a resume like that, we knew Steven was a thought leader we needed to bring on to the podcast. Today, we're going to tap into his considerable insights, particularly as they pertain to how MSPs can deliver digital transformation more effectively. Steven Hall: Well, thank you, Guy.