Haitong Securities International·2025-12-08 06:12Investment Rating - The report does not explicitly provide an investment rating for the Titans architecture or related companies in the AI technology sector. Core Insights - Google has reintroduced its Titans architecture at NeurIPS 2025, which is seen as a significant evolution post-Transformer, addressing limitations in ultra-long context processing, long-term memory, and cross-document reasoning [1][11]. - Titans can handle contexts of up to 2 million tokens and introduces test-time learning, allowing models to continuously accumulate knowledge during inference [1][12]. - The architecture combines a memory-enhanced design with recursive and attention mechanisms, significantly improving the processing of long sequences and reducing computational costs compared to traditional Transformers [2][3][12]. Summary by Sections Event Overview - Google emphasized the Titans architecture and the MIRAS theoretical framework at NeurIPS 2025, positioning it as a major advancement in AI architecture [1][11]. Technical Innovations - Titans features a Neural Memory module that allows for dynamic memory writing and retrieval during inference, enhancing long-term memory capabilities [2][12]. - The architecture employs a hybrid design of recursive updates and attention mechanisms, enabling efficient processing of long sequences while maintaining essential global interactions [2][12]. - MIRAS provides guidelines for memory management, allowing Titans to effectively handle ultra-long documents and complex reasoning tasks [2][12]. Comparative Analysis - Titans' dynamic memory during inference is a key improvement over Transformers, which face significant computational challenges with long sequences due to their O(N²) complexity [3][13]. - While Titans excels in long-context understanding and multi-document reasoning, Transformers remain more efficient for short-context tasks and real-time applications [4][14][16].