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

Abstract: Nowadays, data is being generated, collected, and analyzed at an unprecedented scale, data integration is the problem of combining data from heterogeneous, autonomous data sources, and ...

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

GraphRAG explains why AI is shifting from isolated text to connected knowledge, and what that means for AI search ...

The cloud-based agentic AI platform aims to help human researchers overcome resource constraints and complex data challenges ...

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

The recent US-Iran war has given the world one of the clearest glimpses yet of this transformation. The US used AI services, ...

The speakers discuss Netflix’s architecture for surviving extreme traffic spikes. They explain the mechanics of prioritized ...

Backstage solved the portal problem, not the platform problem. A portal organizes catalogs, documentation, and templates. A ...

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