Since our last update, we have been diligently working toward achieving our Q3 milestones as part of Phase 2 in Livepeer's AI journey. With most of our objectives now completed (a detailed retrospective is on the way), we are in the final stages of delivering the remaining items and reviewing outstanding pull requests. As we complete these final pieces, we are confident that the AI network has reached a strong, stable foundation for builders and end-users alike.

In recognition of this progress, the AI subnet has officially been renamed to the Livepeer AI Network 🎉, marking its transition from alpha to beta. We’re also excited to announce that the LLM SPE (led by the Livepool team) and Livepeer Studio teams have joined forces with us, Livepeer Cloud, and the broader community 🤝. Their expertise in distributed systems and commitment to open-source development, as demonstrated in their work on the transcoding network, will play a pivotal role in further shaping the AI roadmap and driving even greater innovation. Expect to see exciting new developments as we collaborate with our community to advance our mission of democratizing AI and building a globally accessible, open AI video infrastructure 🚀.

Here’s a quick recap of the key accomplishments since the last update:

Segment-Anything-2 Pipeline Release

We successfully launched the new Segment-Anything-2 pipeline and, in the process, enhanced our container workflow to enable seamless, permissionless pipeline integration through custom containers in the future. Since its release, this pipeline has generated over $10K in fees and processed more than 400K requests in just one week, as highlighted on the Livepeer AI Dune Dashboard—showcasing the immense potential of the AI Network 🚀! A big shoutout to the Livepeer Ecosystem team for their crucial role in driving demand by collaborating with startups to make this pipeline a success.

LoRA Integration

In partnership with Marco Stronk, we’ve introduced LoRA support, allowing users to apply fine-tuned models to any Text-to-Image or Image-to-Image requests. This unlocks a new realm of creative possibilities (see banner image). With our automatic LoRA loading mechanism, orchestrators can now seamlessly handle thousands of LoRAs without manual configuration ⚡.

Client SDK Release

We’re thrilled to announce the release of Python, TypeScript, and Golang SDKs, streamlining the developer experience and making it easier than ever to interact with the Livepeer network 🛠️. Developed in collaboration with the Livepeer Studio team, these SDKs are crafted to provide a smooth, modern interface that aligns with industry best practices.

New Gateway improvements

We have introduced a new -maxPricePerCapability flag, allowing gateways to set the maximum price at the capability level, providing more precise control over spending. Additionally, the new -DiscoveryTimeout flag has been implemented to extend the discovery timeout when searching for orchestrators, enabling the use of a larger pool of resources for AI jobs.

Improved Error Handling & Documentation

We’ve completely overhauled error handling on the AI subnet. Instead of vague internal server errors, users now receive clear, descriptive messages that make troubleshooting easier and more transparent. Additionally, we’ve revamped our documentation to include the new SDKs and improved pipeline parameter descriptions, further streamlining the developer experience.

Additional Improvements and Bug Fixes

Model and Security Enhancements

- Added support for Black Forest Labs Flux.

- Added SG161222/Realistic_Vision_V6.0_B1_noVAE T2I support.

- Implemented the -enforceMaxPrice flag, now enabled by default, to prevent gateways from accepting prices above the set maximum.

Bug Fixes

- Fixed a runtime error that occurred when AI orchestrators failed to set a price.

- Corrected duration calculations for A2T with certain MP3 files.

- Ensured T2I/I2I pricing now accounts for the number of images.