Knowledge graph startup Diffbot Technologies Corp., which maintains one of the largest online knowledge indexes, is looking to tackle the problem of hallucinations in artificial intelligence chatbots ...
Data models and query languages are admittedly somewhat dry topics for people who are not in the inner circle of connoisseurs. Although graph data models and query languages are no exception to that ...
Daniel D. Gutierrez, Editor-in-Chief & Resident Data Scientist, insideAI News, is a practicing data scientist who’s been working with data long before the field came in vogue. He is especially excited ...
Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Recommendations can be the guiding light for organizations seeking to increase customer engagement, satisfaction, and retainment—all culminating in greater revenue for the enterprise. Great ...
Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...
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