Businesses are constantly evolving, and leaders are challenged every day to meet new requirements and are seeking ways to optimize their operations and gain a competitive edge. One of the key challenges they face is managing the complexity of disparate business systems and workflows, which leads to inefficiencies, data silos, and missed opportunities. Generative AI …
With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing the accuracy and reliability of AI-generated responses. RAG is as a way to incorporate additional data that the large language model (LLM) was not trained on. This can also help reduce generation …
As one of the fastest sports in the world, almost everything is a race in Formula 1® (F1), even the pit stops. F1 drivers need to stop to change tires or make repairs to damage sustained during a race. Each precious tenth of a second the car is in the pit is lost time in …
AWS machine learning supports Scuderia Ferrari HP pit stop analysis Read More »
This post is co-authored by Manuel Lopez Roldan, SiMa.ai, and Jason Westra, AWS Senior Solutions Architect. Are you looking to deploy machine learning (ML) models at the edge? With Amazon SageMaker AI and SiMa.ai’s Palette Edgematic platform, you can efficiently build, train, and deploy optimized ML models at the edge for a variety of use …
Accelerate edge AI development with SiMa.ai Edgematic with a seamless AWS integration Read More »
This post is co-written with Ken Tsui, Edward Tsoi and Mickey Yip from Apoidea Group. The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. These tasks, which require significant human resources, slow down critical operations such as Know Your Customer (KYC) procedures, loan …
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