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Build powerful RAG pipelines with LlamaIndex and Amazon Bedrock

This post was co-written with Jerry Liu from LlamaIndex. Retrieval Augmented Generation (RAG) has emerged as a powerful technique for enhancing the capabilities of large language models (LLMs). By combining the vast knowledge stored in external data sources with the generative power of LLMs, RAG enables you to tackle complex tasks that require both knowledge …

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Deploy Amazon SageMaker pipelines using AWS Controllers for Kubernetes

Kubernetes is a popular orchestration platform for managing containers. Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. DevOps engineers often use Kubernetes to manage and scale ML applications, but before an ML model is available, it must be trained and evaluated and, if the …

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Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024

Today, we are excited to announce that Google is a Leader in The Forrester Wave™: AI/ML Platforms, Q3 2024, tying for the highest score of all vendors evaluated in the Strategy category. At Google Cloud, we are committed to providing you with a unified platform that supports the entire AI lifecycle – from data preparation …

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

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 …

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

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: …

Optimizing Byte-level Representation for End-to-End ASR

In this paper, we propose an algorithm to optimize a byte-level representation for end-to-end (E2E) automatic speech recognition (ASR). Byte-level representation is often used by large scale multilingual ASR systems when the character set of the supported languages is large. The compactness and universality of byte-level representation allow the ASR models to use smaller output …

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Best practices for prompt engineering with Meta Llama 3 for Text-to-SQL use cases

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 …

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GenOps: learning from the world of microservices and traditional DevOps

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 …

Apple Workshop on Privacy-Preserving Machine Learning 2024

At Apple, we believe privacy is a fundamental human right. It’s also one of our core values, influencing both our research and the design of Apple’s products and services. Understanding how people use their devices often helps in improving the user experience. However, accessing the data that provides such insights — for example, what users …