Michael Polanyi, a philosopher, famously distilled tacit knowledge thus: “We can know more than we can tell.” How can AI ...

FlureeDB acts as a secure context layer fit for autonomous systems: pull from many data sources wherever they live, answer structured queries fast and efficiently, carry citations and lineage on every ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the ...

To ensure the safety of industrial systems and reduce downtimes, fault diagnosis must be accurate and timely. A graph neural network-based method introduced in this paper is referred to as the ...

Meta has been one of the most interesting companies of the generative AI era — initially gaining a loyal and huge following of users for the release of its mostly open source Llama family of large ...

Obsidian Note Taking reshapes how information is captured, connected, and rediscovered by turning simple Markdown files into a dynamic, interconnected system. Instead of isolating notes in folders, ...

Timely and accurate decision-making is critical during gas tunnel emergencies, yet relevant knowledge is typically fragmented across unstructured reports, manuals, and case records, hindering rapid ...

This article was originally published by WatersTechnology. Since 2023, Bloomberg has unveiled its internal LLM, BloombergGPT, and added an array of AI-powered tools to the terminal. As banks and asset ...

Abstract: Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational ...

As AI systems move from single assistants to fleets of collaborating agents, graphs are emerging as the best representation for us to harness them. But graphs are simply a way to represent data and ...