NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.

Everpure's data primacy thesis is a bold architectural argument. Across four interviews at Accelerate, its executives made ...

Roese's predictions: stronger AI governance, better data management, agentic AI infrastructure, resilient AI factories, and ...

Dun & Bradstreet has spent over 180 years building a comprehensive commercial database. Its Commercial Graph, covering 642 million businesses and their relationships, corporate hierarchies and risk ...

The SQLite of graph databases. Embedded, Cypher-native, zero infrastructure. SparrowDB is an embedded graph database. It links directly into your process — Rust, Python, Node.js, or Ruby — and gives ...

Burn electricity to train large models, and you get a neural network ontology; burn tokens to train a memory graph, and you get a symbolic network ontology. Combine the two, and you get ...

A nation cannot boast of a thriving security force with thorough aggression against invaders or mercenaries without protecting the lives ...

Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already known about genes, diseases, treatments, molecular pathways and symptoms in ...

The Melbourne-based university has developed a centralised platform on Amazon Web Services to help users more easily find information across its research ecosystem, using multi-modal generative AI.

Bacteria dominate the ecosphere through their varied metabolic pathways. Genomic data now serve as a common start point for studying bacterial metabolism, yet current capacity to predict and compare ...

Graph Neural Networks (GNNs) have gained considerable attention in recent years. Despite the surge in innovative GNN architecture designs, research heavily relies on the same 5-10 benchmark datasets ...