Xiaohongshu 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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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.
Swedish AI Startup Lovable Eyes $13.2 Billion Valuation After Major Funding Round
As AI-driven coding tools gain traction, Swedish startup Lovable has secured a major funding round. The company aims to raise $3 billion, potentially boosting its valuation to $13.2 billion—double the $6.6 billion recorded last December. Menlo Ventur
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Streamline Report Card Comments with AI ToolsIntroductionAI Tools for Generating Report Card CommentsMagic SchoolAlmanac AIChat GPTUsing Magic School to Generate Report Card CommentsLogging into Magic SchoolSelecting the Report Card Comments ToolCust





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