Businesses that adapt to the latest technologies are likely to see their operations become more efficient, customer satisfaction and retention improved, and revenue increased. Moreover, it gives that business a competitive edge, improving the overall brand reputation and how its customers perceive the company's value. The best way to achieve this is to overhaul your business with a digital transformation. Digital transformation replaces traditional business processes with improved digital technologies to enhance, advance, or make operations more efficient. Why is digital transformation important?

ElectrifAi, one of the world's leading companies in practical artificial intelligence (AI) and pre-built machine learning (ML) models, today announced that it has achieved Amazon Web Services (AWS) Machine Learning Competency status in the new Applied Artificial Intelligence (Applied AI) category. This designation recognizes that ElectrifAi has demonstrated deep experience and expertise in building or integrating practical ML solutions on AWS. AWS Partners recognized as part of the AWS Machine Learning Competency expansion help customers take advantage of intelligent solutions to drive business optimization, customer revenue growth and cost reduction. This is done by creating, automating, and managing end-to-end ML workflows with machine intelligence. The AI and ML driven applications are maturing rapidly and creating new demands on enterprises.

A regular message in this column is that artificial intelligence (AI) won't spread widely until it's easier to use than the requirement to have programmers who can work at the model level. That challenge won't be solved instantly, and it's slowly changing. While technical knowledge is still too often required, there are ways in which development time can be shortened. One way that's been happening has been is the increased availability of pre-built models. A few years back, a tech CEO loved to talk about the "Cambrian Explosion" of deep learning models, as if a lot of models meant real progress in the business world.

A regular message in this column is that artificial intelligence (AI) won't spread widely until it's easier to use than the requirement to have programmers who can work at the model level. That challenge won't be solved instantly, and it's slowly changing. While technical knowledge is still too often required, there are ways in which development time can be shortened. One way that's been happening has been is the increased availability of pre-built models. A few years back, a tech CEO loved to talk about the "Cambrian Explosion" of deep learning models, as if a lot of models meant real progress in the business world.

For true success, data scientists must be bilingual to effectively accomplish their work. This means being equally versed in technological jargon as well as being able to communicate with business stakeholders. When we look at where data science fails, it's usually in communications. Data science is a relatively new field, first coined in 2001 by William Cleveland to "enlarge the major areas of technical work of the field of statistics." Today, the demand for data scientists is astronomical, because company data can offer tremendous value in edging out competitors--if properly utilized.

Jim McGowan, is the head of product at ElectrifAi, they specialize in extracting massive amounts of disparate data, transforming chaotic structured and unstructured data into actionable business insights. What is it that attracted you to the world of machine learning and AI? I first encountered Machine Learning while earning a doctorate for work in cognitive science. AI systems largely consisted of distilling an expert's experience down to a flow chart. This seemed intuitively to work, but the systems quickly grew too complex and weren't living up to their promise.

Edward Scott is the founder and CEO of ElectrifAi, a company that leverages Artificial Intelligence and Machine Learning via their suite of products to drive profit improvement, increased performance, and risk reduction. As part of this discussion, we shared how their partnership with Microsoft, their use of Azure, and the Azure Marketplace have empowered them to scale and grow their business. Facebook: AvrohomGottheil Twitter: @avrohomg Instagram: @avrohomg INTERVIEW HIGHLIGHTS: [00:48] Artificial Intelligence is very prevalent nowadays, especially in HealthCare, and providers are converting their data to digital format to leverage the benefits of the latest innovations in technology. What are the challenges health care providers face when trying to go digital? Ed: You can access our solution set via one of the following links: electrifai.imageai

Debra Fahey will be joining the company as Senior Vice President, Global Head of Delivery & Operations, and Michael Fox will be joining as Senior Vice President of Product Management. Together, these leaders bring over 40 years of experience in the fields of technology, business analytics, innovation strategy, and software development to ElectrifAi's growing team of skilled professionals. "I am proud to welcome Debra and Michael as the newest additions to ElectrifAi's deep executive leadership team," said CEO, Edward Scott. "Their wealth of knowledge and invaluable experience in the fields of delivery, operations, and product management will be vital in their new roles advancing ElectrifAi's industry-leading Ai and ML products. I am confident Ms. Fahey and Mr. Fox will add value to our expanding global leadership team and continue to strengthen our expertise within the Ai and ML technology, innovation, and delivery of solutions."

ElectrifAi, a global leader in Artificial Intelligence (AI) and Machine Learning (ML), today announced the launch of a new and improved open source platform and the appointment of industry veteran Edward Scott as ElectrifAi CEO. This comes alongside a comprehensive corporate rebrand for ElectrifAi, changing its name from Opera Solutions and launching a new website. In an industry-first move, ElectrifAi has re-architected its technology platform around an open source, Spark-unified computational engine that allows large-scale distributed data processing and machine learning, with embedded Zeppelin notebook capability. Now, ElectrifAi's data scientists – as well as those of its customers – can code and access data in any programming language. The incorporation of Docker Containers and Kubernetes enables ElectrifAi to build and deploy hybrid cloud enterprise solutions at scale, seeing results in weeks rather than months, thus increasing enterprise time to value dramatically.