SAS Viya can allow users and organizations to more easily interface with the LLM application, build better prompts and evaluate systematically which of these prompts leads to the best responses to ensure the best outcomes.
The National Institute of Standards and Technology (NIST) has released a set of standards and best practices within their AI Risk Management Framework for building responsible AI systems. NIST sits under the U.S. Department of Commerce and their mission is to promote innovation and industrial competitiveness. NIST offers a portfolio
SAS Model Manager and the sasctl packages aim to create a seamless ModelOps and MLOps process for Python and R models. Python and R models are not second-class citizens within SAS Model Manager. SAS, Python, and R models can be easily managed using our no-code/low-code interface. This is an interface that can be extended to support a variety of use cases.
How did we get to a place where a conversational chatbot can quickly create a personalized letter? Join us as we explore some of the key innovations over the past 50 years that help inform us about how to respond and what the future might hold.
I will show you how to deploy multi-stage deep learning (DL) models in SAS Event Stream Processing (ESP) and leverage ESP on Edge via Docker containers to identify events of interest.
Using such features and Natural Language Processing capabilities like text parsing and information extraction in SAS Visual Text Analytics (VTA) helps us uncover emerging trends and unlock the value of unstructured text data.
Using SAS Viya in combination with open-source capabilities, we were able to develop an automated solution for logo detection that does not require any manual data labeling.
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.
Let's create a Multi-stage Computer Vision model to detect objects on high-resolution imagery taken from an aerial view. The goal is to locate a dog and determine if he is wearing a scarf or not and what color the scarf is.
If you are an Enterprise Miner user, do not miss the opportunity to try out Model Studio in SAS Viya. I am sure you will love it!
