The business model behind the predominant AI Large Language Models (LLMs) is going to crash by 2030 or before. It will not be for dystopian reasons, intellectual property rights infringements, or lack ...

data can be defined consistently and delivered reliably. Figure 1: Centralized model for data & analytics management In practice, however, there’s a few big problems with this approach.

As artificial intelligence (AI) usage and sophistication grows, questions about the sustainability of the traditional model ...

The emergence of the hybrid work model has delivered benefits ... and storing vast amounts of information efficiently.

“Edge,” in the context of Ditto’s industry, refers to a distributed computing model that brings data processing and ... rather than having to rely on centralized data centers and cloud ...

As utilities typically have technology assets dispersed across broad geographical areas—often in remote, inhospitable locations—this computing model ... central location for processing. When ...

Edge computing involves processing data closer to where it is generated, at the network's "edge" rather than relying on a centralized server ... a zero-trust security model, granting users ...

Embrace an ‘Uber-like’ data processing model Traditionally, data processing has been transaction ... Uber provides a constructive example: Instead of requesting a car through a central dispatch office ...

A document data model removes that requirement. The Ditto databases running on a company’s edge devices can regularly sync their contents to a centralized data processing environment.