Data Lakehouse Drives AI Large Model Advancement: GBase Selected for 'Large Model Vendor Panoramic Map'

Recently, ifenxi, a leading Chinese industry digitalization research and consulting firm, released the "2023 ifenxi: Large Model Vendor Panoramic Report." Taking into account enterprise demands and attention levels, it selected 7 specific markets for in-depth analysis, providing a reference for enterprise vendor selection through demand analysis of each market and interpretation of representative vendors' capabilities. With its deep presence and technical strength in the large model domain, GBase was successfully included in the "Large Model Vendor Panoramic Map" within the Data Lakehouse segment.

ifenxi believes that from a technical architecture perspective, the large model market can be divided into the infrastructure layer, model layer, intermediary layer, and application layer. The infrastructure layer provides the foundational environment for training and inference of large models, including data lakehouse, vector databases, intelligent computing centers, and secure circulation platforms for large models. The model layer includes base large models and fine-tuned large models, encompassing general-purpose large models, industry-specific large models, domain-specific large models, and enterprise large models. The intermediary layer acts as a "bridge" between the model layer and application layer, facilitating rapid deployment of large models in various real-world scenarios, including large model application development tools and LLMOps tools. The application layer refers to large model applications and solutions, such as knowledge base Q&A, intelligent customer service, and conversational analytics.

GBase has always focused on the R&D of core database technologies and market development. With two decades of deep cultivation in the database field, it has built a matrix of database products and solutions that cover the entire data management lifecycle and full technology stack.

The storage foundation for AI large models requires high storage density, high-performance computing, and data security assurance. GBase GCDW, a cloud-native real-time logical data warehouse, supports the data lakehouse architecture. Taking the data lake as its base, it builds data warehouse and AI data management capabilities on top, further safeguarding the efficiency of large model training. In addition, targeting key large model technologies, GBase has introduced GBase Cloud Vector DB, a vector database built on the GBase 8a cluster, for diverse AI-driven application scenarios. It supports classification, deduplication, and cleaning of massive data during the large model training phase, while addressing the security and privacy issues arising from injecting private data into large models.

Moving forward, GBase will drive product innovation guided by AI large model application demands, enrich and improve its product and technology system, continue to deepen core technologies, and deeply integrate with the digital transformation needs of various industries. It will keep advancing the quality and efficiency of digital transformation while empowering deeper data application across industries.