generative

Personalization has become a cornerstone of delivering tangible benefits to businesses and their customers. Generative AI and large language models (LLMs) offer new possibilities, although some businesses might hesitate due to concerns about consistency and adherence to company guidelines. This post presents an automated personalization solution that balances the innovativeContinue Reading

The post is co-written with Michael Shaul and Sasha Korman from NetApp. Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training. This data is used to enrich the generativeContinue Reading

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and confidently build, train, and deploy ML models into a production-ready hosted environment. SageMaker provides a broad selection of ML infrastructure and model deployment options to help meet your ML inference needs.Continue Reading

As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. In what we consider “Act 1” of the generative AI story, we saw previously unimaginable amounts of data and compute create models thatContinue Reading

This post was co-written with Mickey Alon from Vidmob. Generative artificial intelligence (AI) can be vital for marketing because it enables the creation of personalized content and optimizes ad targeting with predictive analytics. Specifically, such data analysis can result in predicting trends and public sentiment while also personalizing customer journeys,Continue Reading