SAS's Ann Kuo walks you through how SAS Tech Support developed an email classifier to clean up spam and misaddressed emails using SAS Viya's NLP-based text classifier
SAS's Ann Kuo walks you through how SAS Tech Support developed an email classifier to clean up spam and misaddressed emails using SAS Viya's NLP-based text classifier
SAS' Sophia Rowland breaks down the roles of each team member in a long-term machine learning project and how they can better combine their efforts to increase efficiency and efficacy
AI is increasingly prevalent in our daily lives, and this trend is unlikely to change anytime soon. This comes with risks, but by understanding these risks, we can build AI systems that mitigate them.
SAS' Mary Osborne, Ali Dixon Ricke, and Franklin Manchester break down what insurers still need to learn about generative AI.
As populations around the world the U.S. continue to grow, both condensing in urban areas and sprawling in more rural areas, the importance of a functioning distribution network for utilities grows proportionally. The complexity and interconnected nature of say, the electric distribution network, is already staggering; one can hardly imagine
We often hear about cyberattacks, hackers, ransomware, and other nefarious deeds in the news, but not all data breaches are caused by third parties.
As part of this year's IEEE Visual Analytics Science and Technology (VAST) Challenge, a group of SAS data scientists puit SAS Viya and related machine learning tools to the ultimate test - to identify individuals in a complex fishing network. Excitedly, the team received the Honorable Mention Award for Breadth of Investigation!
What sets the SAS Model Card apart from previous model cards is the use of descriptive visuals, to make model cards accessible to all personas involved in the analytics process, including data scientists, data engineers, MLOPs engineers, managers, executives, risk managers, business analytics, end-users, and any other stakeholder with access to the SAS Viya environment.
When using LLMs, managing toxicity, bias, and bad actors is critical for trustworthy outcomes. Let’s explore what organizations should be thinking about when addressing these important areas.
A recent article came out with an updated list of necessary components for MLOps and LLMOps. And while this list may seem long, reading through the capabilities and components, I realized that SAS Viya already covers most of the required functionality. Organizations can have a hodgepodge of tools that they