IBM Data Science and AI Elite team members Mehrnoosh Vahdat and Rachael Dottle were just one month into their IBM careers when they received their first assignment last July.
The project jettisoned them into the heart of Africa, where their banking client was looking to surface new business
The IBM Data Science and AI Elite team showed that PostNord can predict non-deliveries of traceable items depending on address, weather condition, sizes and time of delivery. By leveraging AI, it’s possible to reduce non-deliveries by 50 percent annually, beneficial for both customers and PostNord
Imagine a day in the life of Sarah, a hypothetical Chief Data Officer at a major bank in South Africa. There are many expectations on her shoulders. She struggles to deliver business-ready data to fuel her organization and support the decision makers within the bank. It is her job to put in place a
At IBM Cloud Pak for Data, we’ve got a growing ecosystem of technology partners. As an open, Kubernetes-based, data and AI platform, we integrate with an array of tech solutions that enhance what we do to help companies make their data AI-ready. From stepping up data security to empowering
With its electro-light tulip garden, disco ball-adorned trees and no stone-left-unturned music lineup, "Denmark’s Most Beautiful Festival" aims to surpass guests’ expectations on safety, comfort and entertainment, from its uncannily clean bathrooms down to its whimsical camp-in-a-beer-can glamping
In the latest release of IBM Cloud Pak for Data, v2.5 has three key themes: Red Hat integration, new key built-in capabilities like Watson tools and runtimes, and a heavy focus on open source .(https://www.ibmbigdatahub.com/blog/announcing-cloud-pak-for-data-2-5). Open source is widely adopted in
68 percent of surveyed businesses recently responded that they use machine learning (ML) or plan to do so in the next three years. AI technologies rapidly are becoming how businesses distinguish themselves from competitors. But choosing the best way to implement AI isn’t always a straightforward
Artificial intelligence and machine learning (ML) have become very popular recently due to their ability to both optimize processes and provide the deep insights that push enterprises and industries forward. In fact, 68 percent of respondents in a recent 451 Research Report, Accelerating AI with
It’s no surprise: most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of
In part one of the Capitalogix data science story, I focused on their strategic need for a data platform that supports speed, data variety and custom-built algorithms to find advantages for their business. A key success driver: they worked to make life better for the people on the front lines of
With the automated AI and ML advancements, you may find yourself wondering--what are the overall impacts to business? How will all of this technological progress impact the ways we run our business and perform our jobs?