Hello dear community,
Following a series of content and feature releases in the past few weeks I wanted to recap everything available for teams building AI-enabled applications.
The new Amazon SageMaker integration enables CircleCI users to orchestrate model deployment to SageMaker and to track and manage their deployments through The Releases section of the CircleCI platform.
- Find more information in our documentation
- Check the Amazon Sagemaker orb page
- Check out our tutorial for a step-by-step guide
- Fork our sample repository to get started quickly.
You can now trigger your CI pipeline on every model or dataset update thanks to our new Inbound Webhooks. Check our changelog
- Blog post - Empower Your MLOps Journey: A Case Study of Image Detection. A tutorial to run you through triggering updates from Hugging Face assets.
NB: Inbound webhooks are currently only available to users authenticated through our GitHub App integration.
- Leverage the power of Scaleway’s Dedicated AI and GPU compute
Blog post - CircleCI Runner on top of Scaleway’s Dedicated AI and GPU compute
- Linux CUDA images includes AI/ML-specific software
- New NVIDIA Tesla GPU available on our Scale plan
Learn how to evaluate LLM-powered apps in your CI pipeline
- Blog post - Build and evaluate LLM-powered apps with LangChain and CircleCI
- Blog post - Deploy and re-evaluate LLM-powered apps with Langsmith and CircleCI
Want to learn more?
- Ebook - AI adoption Guide
- Blog post - CI for Machine Learning
- Blog post - CD for Machine Learning
- Blog post - Automating and scaling machine learning workflows with CI/CD
- Blog post - Risks and rewards of generative AI for software development
- Video - How to overcome the challenges of ML model development
Our product team is actively looking for engineers building AI-enabled applications to discuss our next roadmap choices. If you are interested in taking part in the future of CircleCI, please book a 30-minute slot with our AI team.
To better building,