Scaling Law没死，Gemini核心大佬爆料，谷歌已有颠覆性密钥

Core Insights - Google DeepMind's Gemini pre-training head, Sebastian Borgeaud, predicts significant innovations in long context processing efficiency and context length expansion within the next year [2][4][16] - The recent discussions among key figures at Google, including Jeff Dean, Oriol Vinyals, and Noam Shazeer, indicate a consensus on the evolving nature of AI models and the importance of system architecture over mere model size [26][30][32] Group 1: Innovations in AI - Major advancements are expected in long context capabilities, transforming models into comprehensive digital workspaces capable of handling extensive data and complex tasks [16] - Recent discoveries in attention mechanisms may lead to substantial improvements in model understanding and efficiency, indicating that there is still significant room for enhancement in this area [18] - The return of retrieval-based learning, where models dynamically access external knowledge rather than relying solely on memorized data, is seen as a promising direction for future AI development [19] Group 2: Shift in AI Development Paradigms - The industry is transitioning from a "data abundance" mindset to a "data limited" approach, necessitating more efficient use of available data and a focus on sophisticated system engineering [12][30] - The emphasis is shifting from merely achieving high performance to ensuring models are cost-effective and reliable for long-term deployment [22][30] - The concept of "slow thinking" is introduced, highlighting the need for models to engage in continuous self-assessment and correction rather than just rapid output generation [30] Group 3: System vs. Model - The term "system" is frequently used to describe Gemini, emphasizing its role as a long-term, iterative infrastructure rather than a one-time model achievement [31][32] - The focus on stability, scalability, and the ability to recover from errors is prioritized over immediate performance metrics, indicating a strategic shift in how AI systems are developed and evaluated [32][34] - Google aims to create a sustainable and evolving intelligent system rather than a fleeting product, reflecting a commitment to long-term innovation in AI [34]