Meta 的 AIRA₃ 在 Kaggle 夺金并实现 27% 延迟下降
While the Kaggle competition demonstrated AIRA₃’s capabilities in a specific domain, the system itself can generalize across distinct domains: changing only th
Meta 的自主 AI 研究系统 AIRA₃ 在 NVIDIA 举办的 Kaggle 竞赛中，从约 4000 支队伍中排名第 8 夺得金牌，任务是用相同信息微调 30B Nemotron 模型以提升推理能力。该系统仅更换任务说明即可跨领域泛化：内部基准上生产 GPU kernel 延迟降低 27%，并在另一场 Kaggle 竞赛中把 4000 年前的阿卡德语泥板翻译成英文，达到金牌水平。AIRA₃ 不依赖中央控制器，而是让多个长期运行的智能体通过共享论坛和文件系统异步协作、累积知识。
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While the Kaggle competition demonstrated AIRA₃’s capabilities in a specific domain, the system itself can generalize across distinct domains: changing only the task specification. In an internal benchmark, AIRA₃ achieved a 27% latency reduction on production GPU kernels, and gold-level performance in another Kaggle competition translating 4,000-year-old Akkadian clay tablets into English.
We're early, and hard problems are still ahead of us. But we believe a system that compounds its own knowledge is the right bet. As we continue to develop and scale, we’re excited about its potential to accelerate AI research and unlock recursive self-improvement.