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This post is co-authored with Travis Mehlinger and Karthik Raghunathan from Cisco. Webex by Cisco is a leading provider of cloud-based collaboration solutions, including video meetings, calling, messaging, events, polling, asynchronous video, and customer experience solutions like contact center and purpose-built collaboration devices. Webex’s focus on delivering inclusive collaboration experiences fuels their innovation, which uses …

How Cisco accelerated the use of generative AI with Amazon SageMaker Inference Read More »

Seamless access to content and insights is crucial for delivering exceptional customer experiences and driving successful business outcomes. Box, a leading cloud content management platform, serves as a central repository for diverse digital assets and documents in many organizations. An enterprise Box account typically contains a wealth of materials, including documents, presentations, knowledge articles, and …

Discover insights from Box with the Amazon Q Box connector Read More »

This post is co-written with Aishwarya Gupta, Apurva Gawad, and Oliver Cody from Twilio. Today’s leading companies trust Twilio’s Customer Engagement Platform (CEP) to build direct, personalized relationships with their customers everywhere in the world. Twilio enables companies to use communications and data to add intelligence and security to every step of the customer journey, …

How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock Read More »

AI chatbots and virtual assistants have become increasingly popular in recent years thanks the breakthroughs of large language models (LLMs). Trained on a large volume of datasets, these models incorporate memory components in their architectural design, allowing them to understand and comprehend textual context. Most common use cases for chatbot assistants focus on a few …

Improve AI assistant response accuracy using Knowledge Bases for Amazon Bedrock and a reranking model Read More »

Innovations in artificial intelligence (AI) and machine learning (ML) are causing organizations to take a fresh look at the possibilities these technologies can offer. As you aim to bring your proofs of concept to production at an enterprise scale, you may experience challenges aligning with the strict security compliance requirements of their organization. In the …

Automate the machine learning model approval process with Amazon SageMaker Model Registry and Amazon SageMaker Pipelines Read More »

With last month’s blog, I started a series of posts that highlight the key factors that are driving customers to choose Amazon Bedrock. I explored how Bedrock enables customers to build a secure, compliant foundation for generative AI applications. Now I’d like to turn to a slightly more technical, but equally important differentiator for Bedrock—the …

Build custom generative AI applications powered by Amazon Bedrock Read More »

Generative artificial intelligence (AI) models have opened up new possibilities for automating and enhancing software development workflows. Specifically, the emergent capability for generative models to produce code based on natural language prompts has opened many doors to how developers and DevOps professionals approach their work and improve their efficiency. In this post, we provide an …

Use Amazon Bedrock to generate, evaluate, and understand code in your software development pipeline Read More »

Music generation models have emerged as powerful tools that transform natural language text into musical compositions. Originating from advancements in artificial intelligence (AI) and deep learning, these models are designed to understand and translate descriptive text into coherent, aesthetically pleasing music. Their ability to democratize music production allows individuals without formal training to create high-quality …

Inference AudioCraft MusicGen models using Amazon SageMaker Read More »

Google for Startups AI Academy: American Infrastructure provides mentorship, training, and resources to help founders scale solutions and benefit communities.

Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and foundation models (FMs). RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer based on the retrieved information. An end-to-end RAG solution involves several …

Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation Read More »