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Advanced Analytics | Analytics
Jennifer Olson 0
3 ways AI and advanced analytics help manage the energy crisis in manufacturing

The need to use less energy is becoming critical to manufacturers worldwide. The transition to a clean energy economy drives new developments in the energy sector. Manufacturers must find ways to reduce energy use to stave off growing internal production costs and remain competitive. Let’s discuss why the global energy

Analytics | Artificial Intelligence | Data for Good
Vrushali Sawant 0
Inclusivity: A guiding principle for responsible innovation

AI – just like humans – can carry biases. Unchecked bias can perpetuate power imbalances and marginalize vulnerable communities. Recognizing the potential for bias is one of the first steps toward responsible innovation. Doing so allows users to include diverse needs and perspectives in building inclusive and robust products. Through

Advanced Analytics | Analytics | Artificial Intelligence
Albert Qian 0
How SAS and Microsoft are using the power of partners to protect data in the cloud

Humanity collectively creates 2.5 quintillion bytes of data daily, presenting incredible opportunities for organizations—especially those who collect it in the cloud. Cloud-based data offers excellent insights for organizations, including a meaningful look at customer needs and operational improvements. However, these benefits come with risks, especially regarding security. According to IBM

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 tips for choosing a statistical computing environment

When you think about life-saving technology, does a statistical computing environment come to mind? Statistical computing environments (SCE) are critical in accelerating scientific discoveries by enabling researchers to manage, process and analyze data efficiently and compliantly, maintaining the utmost regulatory integrity. As life sciences research generates increasingly large and diverse

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 | Data for Good | Innovation
Jerry Williams 0
AI and sustainability: Balancing innovation with environmental impact

Artificial Intelligence (AI) can drive environmental innovation (EI) in sustainability and reduction of carbon emissions. However, the use of AI itself also comes with environmental costs. The high computational requirements of AI-based systems lead to significant energy consumption, contributing to greenhouse gas emissions. The energy consumption of AI systems can

Analytics | Artificial Intelligence | Data for Good | Internet of Things
Emily Johnson 0
Protecting the planet: 7 ways analytics supports sustainability

Analytics are vital to a safer future. As a renowned sustainability leader, SAS is committed to making a positive impact on our customers, employees, and the planet. Climate change is more important than ever, and the explosion of big data is essential to navigating this crisis. Learn how analytics is

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

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