HomeXiaohongshu Open-Sources Training Engine, RelaX AI Circle Adds Another Major Player
On April 15, the Xiaohongshu AI platform team made a notable move in the tech community by quietly open-sourcing a reinforcement learning training engine for large models, named Relax.
Relax is built specifically for multimodal and agentic scenarios, meaning it goes beyond text to handle inputs like images, audio, video, and more — all unified and flexibly integrated. This design aligns with the prevailing AI trend, where multimodal and agent capabilities are widely seen as the next major frontier.
Technically, Relax introduces two core mechanisms: modal-aware parallelism and end-to-end asynchronous pipelining. The former intelligently allocates computing resources based on the characteristics of each modality, while the latter minimizes waiting and idle time during training through an asynchronous pipeline. Together, they boost the efficiency and scalability of multimodal training — offering practical engineering value for AI teams handling large-scale workloads.
Notably, the open-source move itself is significant. Xiaohongshu is not traditionally an AI infrastructure company. By voluntarily releasing its internal training engine, the company showcases its deep expertise in AI engineering and extends an olive branch to the developer community — leveraging technical contributions to build ecosystem influence. This is a path more tech companies are taking in the AI era.
In the AI arms race, Xiaohongshu's move came as a surprise.
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![RaymondRoberts]()
小红书这波开源操作有点东西，Relax引擎专门针对多模态和Agent场景，看来大厂都在卷底层基建了，期待后续效果！🤖
On April 15, the Xiaohongshu AI platform team made a notable move in the tech community by quietly open-sourcing a reinforcement learning training engine for large models, named Relax.
Relax is built specifically for multimodal and agentic scenarios, meaning it goes beyond text to handle inputs like images, audio, video, and more — all unified and flexibly integrated. This design aligns with the prevailing AI trend, where multimodal and agent capabilities are widely seen as the next major frontier.
Technically, Relax introduces two core mechanisms: modal-aware parallelism and end-to-end asynchronous pipelining. The former intelligently allocates computing resources based on the characteristics of each modality, while the latter minimizes waiting and idle time during training through an asynchronous pipeline. Together, they boost the efficiency and scalability of multimodal training — offering practical engineering value for AI teams handling large-scale workloads.
Notably, the open-source move itself is significant. Xiaohongshu is not traditionally an AI infrastructure company. By voluntarily releasing its internal training engine, the company showcases its deep expertise in AI engineering and extends an olive branch to the developer community — leveraging technical contributions to build ecosystem influence. This is a path more tech companies are taking in the AI era.
In the AI arms race, Xiaohongshu's move came as a surprise.
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Ando Launches Team Messaging App Bridging Human and AI Collaboration
In 2025, as Sara Du assisted companies in developing MCP servers, a recurring question emerged: how could teams leverage AI agents directly within Slack? The path was obstructed by significant technical barriers, including the complexity of message s
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小红书这波开源操作有点东西，Relax引擎专门针对多模态和Agent场景，看来大厂都在卷底层基建了，期待后续效果！🤖
