IBM Watson Studio enables organizations to develop models and simplify and scale AI across any cloud while simultaneously automating the AI lifecycle. What do end users say about it? Here are a few quotes from among 94 reviews of Watson Studio on Gartner Peer Insights, a free peer review and
As coined by British mathematician Clive Humby, "data is the new oil." Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL
The integrity and trustworthiness of data or any other master entity is enforced via data quality rules. Customers no longer want to rely on hand crafted rules that can number in the thousands, which in turn also need a lot of maintenance.
Riding on the machine learning (ML) wave, customers can
Many financial firms are increasing their use of AI models because they can represent the real world more accurately, and they can deliver better projections than traditional, rule-based models. But some AI models can add complexity and risk.
You can minimize that risk and also streamline the
Innovation and adaptability are more vital than ever. Our ability to discover new insights, examine patterns and build hypotheses continuously helps us adjust and improve our response to rapidly changing conditions. The Innovator’s DNA by Jeff Dyer, et.al describes five discovery skills which are
IBM Watson OpenScale helps organizations detect and correct AI model bias and drift, explain AI outcomes, monitor model accuracy, analyze payloads, and more. There are algorithms available in open source that provide some of these capabilities. Some of these open source algorithms have originated
It’s been said that data is the most valuable resource on the planet. But most companies aren’t getting the maximum value out of their data. If you look at the top three things that are really needed in the marketplace, it's really been around defining a data strategy, filling the skill shortage
This unified end-to-end platform, Cloud Pak for Data, delivers these data and AI capabilities as container-based microservices that help to power new and existing enterprise applications to run on cloud or on-premises. The platform makes it easy to implement data-driven processes and operations and
Last year, more than 100,000 developers from 156 nations built 2,500+ applications in Call for Code 2018, an IBM initiative to create meaningful change through technology. This year, it's your turn. Join Call for Code 2019 and you’ll have the opportunity to create sustainable software solutions
With THINK 2019 just around the corner, 12 through 15 February, there’s no better time to discover the variety of hybrid data management solutions and strategies, along with how each can help uncover actionable insights.
Machine learning has joined artificial intelligence (AI) as the hottest technology topics of 2018. We asked our expert influencers to share their thoughts on the state of the industry: where it's going, and how and why companies should be adopting machine learning and AI.
Big Data and Analytics Hub spoke with IBM Distinguished Engineer John Thomas (@johnjaithomas) about some of the importance of tuning information architecture to make algorithms meet enterprise needs, as well as how machine learning can most effectively be applied in hybrid scenarios in 2018.