Category: HAQM SageMaker JumpStart

Today, we are excited to announce that the Llama 3.3 70B from Meta is available in HAQM SageMaker JumpStart. Llama 3.3 70B marks an exciting advancement in large language model (LLM) development, offering comparable performance to larger Llama versions with fewer computational resources. In this post, we explore how to deploy this model efficiently on HAQM SageMaker AI, using advanced SageMaker AI features for optimal performance and cost management.

In this post, we explore Clearwater Analytics’ foray into generative AI, how they’ve architected their solution with HAQM SageMaker, and dive deep into how Clearwater Analytics is using LLMs to take advantage of more than 18 years of experience within the investment management domain while optimizing model cost and performance.

Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through HAQM SageMaker JumpStart. You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. In this post, we walk through how to discover, deploy, and use the Pixtral 12B model for a variety of real-world vision use cases.

Today, we are excited to announce that Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407 large language models from Mistral AI that excel at text generation, are available for customers through HAQM SageMaker JumpStart. In this post, we walk through how to discover, deploy and use the Mistral-NeMo-Instruct-2407 and Mistral-NeMo-Base-2407 models for a variety of real-world use cases.

In this post, we show how to build a RAG application on HAQM SageMaker JumpStart using Facebook AI Similarity Search (FAISS).

In this post, we explore how to deploy AI models from SageMaker JumpStart and use them with HAQM Bedrock’s powerful features. Users can combine SageMaker JumpStart’s model hosting with Bedrock’s security and monitoring tools. We demonstrate this using the Gemma 2 9B Instruct model as an example, showing how to deploy it and use Bedrock’s advanced capabilities.

In this post, we demonstrate Embodied AI Chess with HAQM Bedrock, bringing a new dimension to traditional chess through generative AI capabilities. Our setup features a smart chess board that can detect moves in real time, paired with two robotic arms executing those moves. Each arm is controlled by different FMs—base or custom. This physical implementation allows you to observe and experiment with how different generative AI models approach complex gaming strategies in real-world chess matches.

We’re excited to announce the availability of Meta Llama 3.1 8B and 70B inference support on AWS Trainium and AWS Inferentia instances in HAQM SageMaker JumpStart. Trainium and Inferentia, enabled by the AWS Neuron software development kit (SDK), offer high performance and lower the cost of deploying Meta Llama 3.1 by up to 50%. In this post, we demonstrate how to deploy Meta Llama 3.1 on Trainium and Inferentia instances in SageMaker JumpStart.

Today, we are excited to announce that John Snow Labs’ Medical LLM – Small and Medical LLM – Medium large language models (LLMs) are now available on HAQM SageMaker Jumpstart. For medical doctors, this tool provides a rapid understanding of a patient’s medical journey, aiding in timely and informed decision-making from extensive documentation. This summarization capability not only boosts efficiency but also makes sure that no critical details are overlooked, thereby supporting optimal patient care and enhancing healthcare outcomes.

The Cohere Embed multimodal embeddings model is now generally available on HAQM SageMaker JumpStart. This model is the newest Cohere Embed 3 model, which is now multimodal and capable of generating embeddings from both text and images, enabling enterprises to unlock real value from their vast amounts of data that exist in image form. In this post, we discuss the benefits and capabilities of this new model with some examples.