In this wave of AIGC, the most significant underlying evolution lies in AI's leap in "understanding" and "applying" natural language, where data diversity and complexity pose immense challenges across industries. Sage AI, the world's first AI and big data-driven Web 3.0 creation platform, boasts an extensive computational power network that provides continuous computational force. Its vast big data offers numerous training models for valuable data, creating a secure, trustworthy, and fair foundational value network with blockchain technology. Sage AI overcomes reliance on extensive manual parameter tuning by adopting a big data pre-training plus a small data fine-tuning approach. It achieves significant breakthroughs in handwriting, voice, image recognition, and language understanding. The content generated is increasingly accurate and natural, not only of higher quality but also more efficient.
Sage AI provides an intelligent engine built around the core of Data+AI, designed explicitly for processing symbolic data graphs and vectors. It evolves the traditional database "storage & compute" architecture into a "memory & reasoning" architecture. This innovative architecture helps build a unified data layer for the computational power network, efficiently managing and integrating multimodal data with large models, offering users more comprehensive and profound data insights.
Focusing on AI's three key elements - data, computational power, and models - Sage AI deploys privatized large models. Optimizing algorithms and architecture significantly enhances computational power utilization efficiency, supporting higher concurrency with limited initial computational resources and providing users with a stable and reliable large model environment.
Sage AI's intelligent engine employs advanced inference algorithms and model optimization techniques to improve the inference efficiency and accuracy of large models. Additionally, Sage AI is dedicated to researching and developing explainable AI technologies, aiding enterprises in understanding and interpreting the reasoning process of large models, thereby enhancing the credibility and interpretability of intelligent decisions.
This intelligent engine and infrastructure offer comprehensive support to users, helping them tackle challenges related to data, computational power, and models and accelerating business intelligence innovation.
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