7 stories
AI-powered knowledge management systems face a fundamental challenge when businesses need accurate answers rather than plausible ones. Imago Platform Ltd. encountered that problem while developing an application to help customers navigate complicated product warranty policies.
Physical AI needs context about its surroundings to adapt beyond a fixed set of instructions. Munich-based Spranic is building a spatial memory layer that records physical spaces and how they change.
When the founders at Phasis Inc. sought to develop a platform for orienting AI agents, they turned to graphs as a way to obtain a measurement of culture. The company wanted to better understand relations not just between people, but between a person and their values, beliefs and subcultures.
Legacy modernization requires understanding how an application’s code, data and business rules fit together before rebuilding it. BotMan AI uses an AI-powered migration pipeline that maps an application’s dependencies, business logic and data models in a knowledge graph.
AI is helping companies interpret biological data for drug discovery and more personalized care. Healthcare technology company Flahy Inc. is applying that approach to clinical decision support, bringing together information that could affect a person’s next step in prevention or treatment,…
A control plane for distributed AI could help applications decide which tasks to run on a device, at the edge or in the cloud. Seismora Inc. is developing networking technology to coordinate AI workloads across different providers and computing environments, according to Vito Palermo (pictured),…
The knowledge graph can give enterprise AI applications context by connecting data with the business relationships needed to support decisions. Knowledge graphs can connect enterprise data with the meaning AI applications need.
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