At IBM, we led the humans to the moon and coined the term machine learning 50 years ago. Now we are helping organizations scale the ladder to AI to reap rewards in growth, productivity and efficiency with IBM Watson. This journey to AI mirrors the history of travel. In this blog, I’ll describe how
Today, “doing more with less” is a key principle driving business strategy across many resource-intensive industries. Organisations are looking to get more out of artificial intelligence (AI) and machine learning (ML) than just great insights. They need access to recommendations that help simplify
Before making any major purchase decision, most of us read reviews to learn about the experiences of other users and get an understanding of a product from the perspective of the marketplace. This is especially important for when evaluating options for a major investment like planning software.
IBM anticipated barriers to scaling enterprise AI. We developed a platform to help clients operationalize AI faster while infusing trust and transparency with IBM Cloud Private for Data and the add-on Watson OpenScale.
India’s current patient to physician ratio prevents thousands from receiving individualized care needed. iKure has developed a network of facilities with an integrated EMR system that brings care to rural communities in India, Vietnam, and Africa at an affordable and convenient way.
Today's manufacturing organizations operate in a dynamic environment characterized by increased complexity and uncertainty. The financial performance of manufacturers hinges on their ability to rapidly adapt to constantly-changing conditions, from demand fluctuations to delivery challenges while
Prescriptive analytics offers healthcare decision makers the opportunity to influence optimal future outcomes. Based on decision optimization technology, these capabilities allow users to not just recommend the best course of action for patients or providers, they also enable comparison of multiple
Every company has its own set of problems that it attempts to solve. In our case, we needed a more efficient and accurate way to identify the relationships between businesses on which we maintain data.