AWS Machine Learning Blog

Large language models (LLMs) enable remarkably human-like conversations, allowing builders to create novel applications. LLMs find use in chatbots for customer service, virtual assistants, content generation, and much more. However, the implementation of LLMs without proper caution can lead to the dissemination of misinformation, manipulation of individuals, and the generation of undesirable outputs such as […]

In this blog post, we will share some of capabilities to help you get quick and easy visibility into Amazon Bedrock workloads in context of your broader application. We will use the contextual conversational assistant example in the Amazon Bedrock GitHub repository to provide examples of how you can customize these views to further enhance visibility, tailored to your use case. Specifically, we will describe how you can use the new automatic dashboard in Amazon CloudWatch to get a single pane of glass visibility into the usage and performance of Amazon Bedrock models and gain end-to-end visibility by customizing dashboards with widgets that provide visibility and insights into components and operations such as Retrieval Augmented Generation in your application.

This post is a continuation of Creating Natural Conversations with Amazon Lex QnAIntent and Amazon Bedrock Knowledge Base. In summary, we explored new capabilities available through Amazon Lex QnAIntent, powered by Amazon Bedrock, that enable you to harness natural language understanding and your own knowledge repositories to provide real-time, conversational experiences. In many cases, Amazon […]

This post is co-written with Jhanvi Shriram and Ketaki Shriram from Krikey. Krikey AI is revolutionizing the world of 3D animation with their innovative platform that allows anyone to generate high-quality 3D animations using just text or video inputs, without needing any prior animation experience. At the core of Krikey AI’s offering is their powerful […]

Amazon SageMaker JumpStart is a machine learning (ML) hub offering pre-trained models and pre-built solutions. It provides access to hundreds of foundation models (FMs). A private hub is a feature in SageMaker JumpStart that allows an organization to share their models and notebooks so as to centralize model artifacts, facilitate discoverability, and increase the reuse […]

eSentire is an industry-leading provider of Managed Detection & Response (MDR) services protecting users, data, and applications of over 2,000 organizations globally across more than 35 industries. These security services help their customers anticipate, withstand, and recover from sophisticated cyber threats, prevent disruption from malicious attacks, and improve their security posture. In 2023, eSentire was […]

This is a guest post co-written with Ori Nakar from Imperva. Imperva Cloud WAF protects hundreds of thousands of websites against cyber threats and blocks billions of security events every day. Counters and insights based on security events are calculated daily and used by users from multiple departments. Millions of counters are added daily, together […]

Customer service organizations today face an immense opportunity. As customer expectations grow, brands have a chance to creatively apply new innovations to transform the customer experience. Although meeting rising customer demands poses challenges, the latest breakthroughs in conversational artificial intelligence (AI) empowers companies to meet these expectations. Customers today expect timely responses to their questions […]

In this post, we show you how to evaluate the performance, trustworthiness, and potential biases of your RAG pipelines and applications on Amazon Bedrock. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

In this post, we present a solution for configuring SageMaker notebook instances to connect to Amazon Bedrock and other AWS services with the use of AWS PrivateLink and Amazon Elastic Compute Cloud (Amazon EC2) security groups.