As AI systems evolve from assistants into autonomous collaborators, enterprises will need durable memory, explicit semantics, lineage, governance, and explainability. AllegroGraph and GraphTalker ...

Official Implementation of "ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning". Logical rules are essential for uncovering the logical connections between ...

People love to learn, but we don’t really like it when it’s hard. Luckily, some ways to learn are easier than others.

Abstract: Graphs are naturally used to describe the structures of various real-world systems in biology, society, computer science etc., where subgraphs or motifs as basic blocks play an important ...

Schneider Electric is acquiring Cognite, a provider of Agentic AI solutions, at a hefty 18.2 revenues. Cognite is growing ...

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

Abstract: Possessing a manipulable representation of the world is a requirement for intelligent machines to plan, reason, and act in the world. Endowing computational systems, e.g., deep networks (DNs ...

The training and evaluation scripts assume CUDA is available. The default Qwen2.5-7B configuration uses 4 GPUs for training and tensor parallel size 2 for vLLM evaluation.

General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document ...

Spread the love“`html As high schools continue to diversify, the presence of English Language Learners (ELLs) in classrooms ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?