Core Insights - Google DeepMind CEO Hassabis predicts that Artificial General Intelligence (AGI) will be achieved by 2030, but emphasizes the need for 1-2 more breakthroughs akin to the Transformer and AlphaGo before this can happen [11][4][16]. Group 1: AGI Predictions and Challenges - Hassabis stresses the importance of scaling existing AI systems, which he believes will be critical components of the eventual AGI [3]. - He acknowledges that the path to AGI will not be smooth, citing risks associated with malicious use of AI and potential catastrophic consequences [13]. - The timeline for achieving AGI is estimated to be within 5 to 10 years, with a high bar set for what constitutes a "general" AI system, requiring comprehensive human-like cognitive abilities [16][18]. Group 2: Titans Architecture - Google introduced the Titans architecture at the NeurIPS 2025 conference, which is positioned as the strongest successor to the Transformer [6][21]. - Titans combines the rapid response of Recurrent Neural Networks (RNN) with the powerful performance of Transformers, achieving high recall and accuracy even with 2 million tokens of context [7][8]. - The architecture allows for dynamic updates of core memory during operation, enhancing the model's ability to process long contexts efficiently [22][43]. Group 3: MIRAS Framework - The MIRAS framework is introduced as a theoretical blueprint that underpins the Titans architecture, focusing on memory architecture, attentional bias, retention gates, and memory algorithms [36][39]. - This framework aims to balance the integration of new information with the retention of existing knowledge, addressing the limitations of traditional models [39][40]. Group 4: Performance Metrics - Titans has demonstrated superior performance in long-context reasoning tasks, outperforming all baseline models, including GPT-4, on the BABILong benchmark [43]. - The architecture is designed to effectively scale beyond 2 million tokens, showcasing its advanced capabilities in handling extensive data [43]. Group 5: Future Implications - The advancements in Titans and the potential for Gemini 4 to utilize this architecture suggest a significant leap in AI capabilities, possibly accelerating the arrival of AGI [45][48]. - The integration of multi-modal capabilities and the emergence of "meta-cognition" in Gemini indicate a promising direction for future AI developments [48].