谷歌DeepMind近日在其最新研究中推出了两款创新的基础模型，名为「Hawk」和「Griffin」，这标志着人工智能领域的又一重大进展。在一篇详尽的论文中，DeepMind的研究团队提出了一种名为RG-LRU的新型门控线性循环层，该层旨在改进现有的循环神经网络结构，并替代传统的多查询注意力（MQA）机制。
RG-LRU层的创新之处在于它能够更有效地处理序列数据，提高了模型在理解和处理复杂信息时的效率。基于这一新设计，DeepMind构建了两个独特的模型。首先是Hawk模型，它巧妙地融合了多层感知机（MLP）与RG-LRU循环块，旨在平衡全局和局部的信息处理，从而在各种任务中实现更高效的性能。
而Griffin模型则更进一步，不仅结合了MLP和RG-LRU循环块，还引入了局部注意力机制。这种设计旨在增强模型在处理局部特征时的敏感性，同时保持全局理解能力，有望在需要精细分析和广阔视野的任务中表现出色。
这两款新模型的发布，不仅展示了DeepMind在人工智能研究上的持续领先，也为未来的自然语言处理和序列建模设立了新的标准。这一突破性的研究成果，无疑将对学术界和工业界产生深远影响，推动人工智能技术的边界不断向前。
英语如下：
**News Title:** “Google DeepMind Unveils Innovative Models Hawk and Griffin: Redefining AI Infrastructure and Shaping the Future of Intelligent Technologies”
**Keywords:** Google DeepMind, Hawk Model, Griffin Model
**News Content:** Google DeepMind recently introduced two groundbreaking foundational models, named ‘Hawk’ and ‘Griffin,’ marking another significant advancement in the field of artificial intelligence. In an extensive paper, the DeepMind research team proposed a novel Gated Linear Recurrent Unit with Reinforcement (RG-LRU), designed to enhance existing recurrent neural network architectures and replace conventional Multi-Query Attention (MQA) mechanisms.
The innovation of the RG-LRU layer lies in its more efficient handling of sequential data, enhancing the model’s effectiveness in understanding and processing complex information. Based on this new design, DeepMind has constructed two distinctive models. The first, the Hawk model, skillfully combines Multi-Layer Perceptrons (MLP) with RG-LRU recurrent blocks, aiming to balance global and local information processing for improved performance across various tasks.
Going a step further, the Griffin model not only integrates MLPs and RG-LRU blocks but also introduces a local attention mechanism. This design is intended to enhance the model’s sensitivity to local features while maintaining a global understanding, positioning it for excellence in tasks requiring fine-grained analysis and a broad perspective.
The release of these new models not only underscores DeepMind’s ongoing leadership in AI research but also sets new benchmarks for natural language processing and sequence modeling. This breakthrough research is poised to have a profound impact on both academia and industry, pushing the boundaries of artificial intelligence technology forward.
【来源】https://mp.weixin.qq.com/s/RtAZiEzjRWgqQw3yu3lvcg
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