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Analytics
Kristi Boyd 0
Trustworthy AI: 3 reasons we need it now

Who is responsible for ensuring that new AI technologies are fair and ethical? Does that responsibility land on AI developers? On innovators? On CEOs? Or is the responsibility more widespread? At SAS, we believe that it is everyone’s duty to innovate responsibly with AI. We believe that adhering to trustworthy

Analytics
Vrushali Sawant 0
The ethics of responsible innovation: Why transparency is key

In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how

Analytics | Innovation
Jessica Curtis 0
5 key questions to guide your connected factory strategy

Consumer goods manufacturers have faced significant challenges over the past few years due to rapidly changing demand and supply disruptions in their end-to-end supply chain. As a result, manufacturers have realized the need to strengthen their resilience and have prioritized assessing their manufacturing capacity to maximize output and automation. To

Analytics
Cheryl Cass 0
How UNC Wilmington data science students are using SAS to drive business results for Lightcast

Students in the master's program in data science at the University of North Carolina Wilmington (UNCW) drove real-world results using SAS® Viya® for the labor market analytics company Lightcast. The project gave students practical analytical tools to solve a business challenge – invaluable career preparation. At the same time, Lightcast gained business insights

Advanced Analytics | Analytics | Artificial Intelligence | Data Visualization | Machine Learning
Falko Schulz 0
Analyzing demographics and patterns-of-life using SAS Visual Analytics

The IEEE Visual Analytics Science and Technology (VAST) Challenge provides a great opportunity to validate our software against real-world scenarios using complex data sets. Not only do we learn from these projects, but we also send feedback to our development teams to further improve product capabilities for customers.

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