A new contrastive learning framework called VMCL improves knowledge graph embedding for unseen entities and shows smooth, predictable gains as model capacity scales up.

The initial surge of excitement and apprehension surrounding ChatGPT is waning. The problem is, where does that leave the enterprise? Is this a passing trend that can safely be ignored or a powerful ...

Knowledge graphs were the hottest thing in AI architecture a year ago. But today, most teams have quietly shelved them for ...

Ever since large language models (LLMs) exploded onto the scene, executives have felt the urgency to apply them enterprise-wide. Successful use cases such as expedited insurance claims, enhanced ...

A new framework combining a 120,000-entity knowledge graph with contrastive learning outperforms traditional and graph-based ...

AI, natural language processing and semantic search applications are a driving force behind emerging data management operations. Data teams can use knowledge graphs in conjunction with these tools to ...

A single conversation with an AI, continued from my smartphone, lasted for 10 days and about 490,000 tokens. During that time ...

Over the past year or so, I feel that the Japanese used by generative AI has become quite natural.What I am particularly concerned about is the "teniwoha" (Japanese particles).Who does what to whom?