Why MongoDB thinks better retrieval — not bigger models — is the key to trustworthy enterprise AI

As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can ...

Neel Somani explains why interpretability must evolve faster than model size

When systems lack interpretability, organizations face delays, increased oversight, and reduced trust. Engineers struggle to isolate failure modes. Legal and compliance teams lack the visibility ...

From Text To Tables: Why Structured Data Is AI’s Next $600B Frontier

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

MongoDB combines database and embedding models for simplified AI development

MongoDB said additional partners and offerings are expected to be added to the startup program over time.
Scientific Research PublishingOpinion

Evolution of GIS: Learning from the Past—Looking to the Future ()

Given the current state of practice and visions for the future (including AI), certain practices should be reevaluated. This ...
GitHub

MITRE ATT&CK® Data Model

The ATT&CK Data Model (ADM) provides a type-safe, object-oriented interface for working with MITRE ATT&CK datasets. Built on STIX 2.1 compliance, it uses Zod schemas and TypeScript types to ensure ...
IEEE

Achieving Common Operational Data (COD): A conceptual informational framework using the Unified Incident Command and Decision Support™ (UICDS™) approach

Abstract: Common Operational Data (COD) is the essential building block of emergency information sharing. This paper describes how a Conceptual Interoperability Framework is being operationalized by ...
IEEE

Model-Free Predictive Control Based on Data-Driven for Fast and Accurate Power Allocation in Solid-State DC Transformers

Abstract: Robustness is a crucial issue in model predictive control despite the excellent dynamic performance and effective management of multiple variables that this control strategy provides for ...