This post is co-written with Ameet Deshpande and Vatsal Saglani from Qyrus.
As businesses embrace accelerated development cycles to stay competitive, maintaining rigorous quality standards can pose a significant challenge. Traditional testing methods, which occur late in the development cycle,...
This post is a joint collaboration between Salesforce and AWS and is being cross-published on both the Salesforce Engineering Blog and the AWS Machine Learning Blog.
The Salesforce AI Model Serving team is working to push the boundaries of natural...
As organizations scale their Amazon Elastic Kubernetes Service (Amazon EKS) deployments, platform administrators face increasing challenges in efficiently managing multi-tenant clusters. Tasks such as investigating pod failures, addressing resource constraints, and resolving misconfiguration can consume significant time and effort....
Keeping an up-to-date asset inventory with real devices deployed in the field can be a challenging and time-consuming task. Many electricity providers use manufacturer’s labels as key information to link their physical assets within asset inventory systems. Computer vision...
Businesses are increasingly seeking domain-adapted and specialized foundation models (FMs) to meet specific needs in areas such as document summarization, industry-specific adaptations, and technical code generation and advisory. The increased usage of generative AI models has offered tailored experiences...
Organizations are constantly seeking ways to harness the power of advanced large language models (LLMs) to enable a wide range of applications such as text generation, summarizationquestion answering, and many others. As these models grow more powerful and capable,...
