Weights & Biases on Amazon Web Services

Accelerate AI development on AWS with the Weights & Biases AI developer platform. Seamlessly monitor, fine-tune, and deploy models while building cutting-edge GenAI applications powered by the leading frontier models hosted on AWS. Combine AWS’s robust infrastructure with Weights & Biases’ powerful platform to drive large-scale innovation and stay ahead of the curve.

The world’s leading AI teams trust Weights & Biases

The tools provided by the Weights & Biases platform enhances the ability for enterprises of all sizes and industries to leverage AI. Whether enterprises are leveraging AWS’ AI focused infrastructure, developing and fine-tuning models on Amazon SageMaker, or leveraging Generative AI via Amazon Bedrock, Weights & Biases has helped customers deliver high impact applications powered by AI.

Jagjit Dhaliwal

Sr. Manager, Generative AI & AI/ML Partners, AWS

Accelerate GenAI development with Weights & Biases on AWS

W&B Weave integrates directly with Amazon Bedrock, AWS’ native GenAI platform. Enterprises leveraging Amazon Bedrock with the leading foundational models such as Claude, Mistral, Cohere Command, Jamba, can seamlessly use W&B Weave to trace, evaluate, and productionize their GenAI powered applications.

Why Weights & Biases on AWS

Cutting-edge GenAI

Evaluate the performance of different foundational models provided by Amazon Bedrock with W&B Weave. Or simply use W&B Models and Amazon SageMaker together to fine-tune state-of-the-art LLMs like Llama3, Mistral, and Jamba.

Simplified AI workflows

W&B Models integrate with Amazon EKS and SageMaker’s managed training infrastructure to allow ML developers easy access to the accelerated compute required to develop AI models.

Centralized system of record

Create a centralized system of record for all workflows developing and leveraging AI. Weights & Biases integrates and tracks all development on both AWS infrastructure, SageMaker, and Bedrock to create a single pane of glass.

AI security and compliance

Implement robust security measures using AWS security services and granular access controls. Weights & Biases natively supports AWS IAM, KMS, and PrivateLink and implements AWS’ security and governance best practices.

Features

Deep AWS integration

Deploy W&B on AWS infrastructure to benefit from data isolation, private connectivity, and native integrations with Amazon SageMaker, Amazon EKS, Amazon Bedrock, Amazon S3, and other AWS services. Streamline your ML workflows within the AWS ecosystem.

LLM evaluations

W&B Weave integrates with Amazon Bedrock to accelerate the development of LLM-powered applications. Check out this tutorial to learn how to leverage W&B Weave with Amazon Bedrock.

AWS-optimized performance

Leverage AWS’ purpose-built ML infrastructure to train with W&B Models and deploy models faster. Scale your experiments effortlessly with auto-scaling clusters and AWS-optimized resource allocation.

Centralized model and dataset management

Version and manage your models and datasets seamlessly with W&B Registry and Amazon S3. Ensure reproducibility and traceability throughout the model lifecycle while leveraging AWS’ scalable storage solutions.

Comprehensive experiment tracking

Automatically log hyperparameters, metrics, and artifacts for all your Amazon SageMaker runs in W&B Models. Visualize and compare experiments to make data-driven decisions, all within your AWS environment.

Collaborative workspaces

Foster teamwork with shared workspaces, experiment commenting, and reports in W&B Models. Integrate with AWS collaboration tools to enhance team productivity and knowledge sharing.

Advanced LLM fine-tuning

Fine-tune open-source LLMs like CodeLLaMA using W&B Models features, including logging, hyperparameter tuning, and visualization tools, fully integrated with Amazon SageMaker’s powerful capabilities.

Governance framework

Implement robust governance with fine-grained access controls, audit trails, and seamless integration with AWS security services and identity management services such as IAM, KMS, and PrivateLink.

Square accelerates the development and evaluation of new LLM candidates to power the Square Assistant, bringing conversational AI to businesses of all sizes.

Canva optimizes MLOps using Weights & Biases, leveraging the Model Registry to seamlessly transition from experimentation to deployment. This empowers Canva’s ML team to enhance user experiences for over 150 million monthly active users through advanced AI capabilities in design and publishing.

Leonardo.ai leverages AWS and Weights & Biases to scale their GenAI platform, enabling creators to produce high-quality, customizable art assets for various industries. This collaboration accelerates the development and deployment of cutting-edge AI models, democratizing access to advanced GenAI tools.

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Automate Model Deployment to SageMaker Endpoints with Weights & Biases

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Generative AI Spotlight Series: Quickly build production-ready LLM-powered applications