Tag: ai/ml

Generating image descriptions is a common requirement for applications across many industries. One common use case is tagging images with descriptive metadata to improve discoverability within an organization’s content repositories. Ecommerce platforms also use automatically generated image descriptions to provide customers with additional product details. Descriptive image captions also improve accessibility for users with visual …

Read more “Build a generative AI image description application with Anthropic’s Claude 3.5 Sonnet on Amazon Bedrock and AWS CDK”

Don’t Miss Out on ROI of Conversational AI — Your Secret Weapon for Profitability Contact centers are in crisis. Skyrocketing customer expectations were coupled with relentless cost pressures. It all has created a perfect storm. 71% of consumers expect companies to deliver personalized interactions, and 76% of them get frustrated when it doesn’t happen. Agents are overwhelmed: …

Read more “Don’t Miss Out on ROI of Conversational AI — Your Secret Weapon for Profitability”

With the rapid growth of generative artificial intelligence (AI), many AWS customers are looking to take advantage of publicly available foundation models (FMs) and technologies. This includes Meta Llama 3, Meta’s publicly available large language model (LLM). The partnership between Meta and Amazon signifies collective generative AI innovation, and Meta and Amazon are working together …

Read more “Best practices for prompt engineering with Meta Llama 3 for Text-to-SQL use cases”

Who is supposed to manage generative AI applications? While AI-related ownership often lands with data teams, we’re seeing requirements specific to generative AI applications that have distinct differences from those of a data and AI team, and at times more similarities with a DevOps team. This blog post explores these similarities and differences, and considers …

Read more “GenOps: learning from the world of microservices and traditional DevOps”

This post is co-written with Eliuth Triana, Abhishek Sawarkar, Jiahong Liu, Kshitiz Gupta, JR Morgan and Deepika Padmanabhan from NVIDIA.  At the 2024 NVIDIA GTC conference, we announced support for NVIDIA NIM Inference Microservices in Amazon SageMaker Inference. This integration allows you to deploy industry-leading large language models (LLMs) on SageMaker and optimize their performance and …

Read more “Accelerate Generative AI Inference with NVIDIA NIM Microservices on Amazon SageMaker”

Over the past few months, early users put Imagen 3 on Vertex AI through its paces and shared valuable insights with us. It’s clear that users want an AI model that generates stunning visuals and empowers your practical creative applications. We’ve used their feedback to identify three common themes: Demand for unparalleled quality across diverse …

Read more “A developer’s guide to getting started with Imagen 3 on Vertex AI”

As a customer service leader, you know how important it is to provide the best service when someone interacts with your call center. One bad experience for a customer will have far flung implications. In an ideal world, all your call center agents are perfectly trained, and your customers are always happy with their interactions. …

Read more “Top 10 Benefits of Integrating a Chatbot in Call Center”

By Jiangwei Pan, Gary Tang, Henry Wang, and Justin Basilico Introduction Our mission at Netflix is to entertain the world. Our personalization algorithms play a crucial role in delivering on this mission for all members by recommending the right shows, movies, and games at the right time. This goal extends beyond immediate engagement; we aim to …

Read more “Recommending for Long-Term Member Satisfaction at Netflix”