AI & Machine Learning

Worldwide spending on artificial intelligence (AI) systems will reach $35.8 billion in 2019, according to IDC’s latest projections, a whopping 44 per cent increase over the amount spent in 2018. By 2022, that number is expected to more than double to $79.2 billion (all figures USD), equating to a 38 per cent compound annual growth rate

Recent advances in AI have been made possible through access to “Big Data” and cheap computing power. But can it go wrong? Big data is suddenly everywhere. From scarcity and difficulty to find data (and information), we now have a deluge of data. In recent years, the amount of available data has been growing in

In case you’ve been living under a rock, artificial intelligence (AI) is everywhere. It’s infiltrated almost every aspect of our private and professional lives. From healthcare to transportation, AI aims to redefine how information is collected, integrated, and analyzed; ultimately leading to more informed insights and delivering better outcomes. But for all its hype, the

If you’re one of the many who see a dark future where the honest working man is replaced by mindless structures of automated metal, where technology has become so advanced that it is no longer under our control, and where the human race is overpowered by evil robots programmed to take over the world, 1)

Marketing and Sales prioritize AI and machine learning higher than any other department in enterprises today. In-memory analytics and in-database analytics are the most important to Finance, Marketing, and Sales when it comes to scaling their AI and machine learning modeling and development efforts. R&D’s adoption of AI and machine learning is the fastest of

A few months ago, Babson College professor Tom Davenport gave a talk on the state of AI in the enterprise at the annual conference of MIT’s Initiative on the Digital Economy.  His talk was based on two recent US surveys conducted by Deloitte, the first one in 2017 followed by a second in 2018.  Davenport was a co-author of both reports. The 2017 survey was

Legacy code sometimes resembles a sleeping monster that software engineering teams learn to tiptoe around. When enterprises try to modify or upgrade this code, they face a few barriers—one of which is that every small change in the app’s code could have far-reaching, unexpected consequences. With this in mind, everyone’s a little bit afraid of

One of the most cherished dreams — and fears — of today is penetration of Artificial Intelligence in all aspects of our life. Books and movies about wars with robots, artificial masterminds and the forever changed Earth emerge every year to stir our imagination. The reality is far less thrilling: in his famous article Andrew NG, one of the most influential figures in the AI field,

Getty Incumbent organizations—those with long histories—all struggle with the same issue in the digital economy: the conflict between transforming the business and operating the business. How does a company transform its business model midflight, while at the same time competitively operating legacy businesses in order to provide stability and cash flow. As the leading platform

Periodically my colleagues and I raise the topic of machine learning and artificial intelligence in the everyday application of data management and data quality and every day it seems I read something that suggests that if you are not using or considering AI or ML you may be missing out.It is often stated in the

What is AI? Information Age has created a simple guide to AI, machine learning, neural networks, deep learning and random forests. Artificial intelligence or AI, the phrase/acronym gets banded about an awful lot. Unfortunately, a lot of companies that say they use AI don’t. It’s a marketing gimmick — maybe they are even targeting shareholders,