Category: Announcements

May 2024: This post was reviewed and updated with support for finetuning. Today, we are excited to announce that Meta Llama 3 foundation models are available through Amazon SageMaker JumpStart to deploy, run inference and fine tune. The Llama 3 models are a collection of pre-trained and fine-tuned generative text models. The Llama 3 Instruct fine-tuned […]

We are excited to announce that Slack, a Salesforce company, has collaborated with Amazon SageMaker JumpStart to power Slack AI’s initial search and summarization features and provide safeguards for Slack to use large language models (LLMs) more securely. Slack worked with SageMaker JumpStart to host industry-leading third-party LLMs so that data is not shared with the infrastructure owned by third party model providers. This keeps customer data in Slack at all times and upholds the same security practices and compliance standards that customers expect from Slack itself.

AWS was delighted to present to and connect with over 18,000 in-person and 267,000 virtual attendees at NVIDIA GTC, a global artificial intelligence (AI) conference that took place March 2024 in San Jose, California, returning to a hybrid, in-person experience for the first time since 2019. AWS has had a long-standing collaboration with NVIDIA for […]

With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for Retrieval Augmented Generation (RAG). Access to additional data helps the model generate more relevant, context-specific, and accurate responses without retraining the FMs. In this post, we discuss two new features of Knowledge Bases for […]

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data using a fully managed Retrieval Augmented Generation (RAG) model. For RAG-based applications, the accuracy of the generated responses from FMs […]

Amazon Rekognition makes it easy to add image and video analysis to your applications. It’s based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. It requires no machine learning (ML) expertise to use and we’re continually adding new computer vision […]

Today, Mistral AI is bringing its latest and most capable model, Mistral Large, to Amazon Bedrock, and is committed to making future models accessible to AWS customers. Mistral AI will also use AWS AI-optimized AWS Trainium and AWS Inferentia to build and deploy its future foundation models on Amazon Bedrock, benefitting from the price, performance, scale, and security of AWS. Along with this announcement, starting today, customers can use Amazon Bedrock in the AWS Europe (Paris) Region. At launch, customers will have access to some of the latest models from Amazon, Anthropic, Cohere, and Mistral AI, expanding their options to support various use cases from text understanding to complex reasoning.

This post is co-written with Matt Middleton from Contentful. Today, jointly with Contentful, we are announcing the launch of the AI Content Generator powered by Amazon Bedrock. The AI Content Generator powered by Amazon Bedrock is an app available on the Contentful Marketplace that allows users to create, rewrite, summarize, and translate content using cutting-edge […]

Today, we are excited to announce the capability to fine-tune Code Llama models by Meta using Amazon SageMaker JumpStart. The Code Llama family of large language models (LLMs) is a collection of pre-trained and fine-tuned code generation models ranging in scale from 7 billion to 70 billion parameters. Fine-tuned Code Llama models provide better accuracy […]

Today, we’re excited to announce that the Gemma model is now available for customers using Amazon SageMaker JumpStart. Gemma is a family of language models based on Google’s Gemini models, trained on up to 6 trillion tokens of text. The Gemma family consists of two sizes: a 7 billion parameter model and a 2 billion parameter model. Now, […]