Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
0 ego_state 4×1 [x, y, θ, v] — scooter position, heading, speed 1 obs_state 4×1 [x, y, vx, vy] — obstacle position and velocity ...
Doctors fear that their knowledge is being “harvested” and could be “sold to the highest bidder” by AI developers, with the ultimate aim of replacing human professionals, representatives at the BMA’s ...
Roese's predictions: stronger AI governance, better data management, agentic AI infrastructure, resilient AI factories, and sovereign AI strategies.
Abstract: Graph cut algorithms are popular in optimization tasks related to min-cut and max-flow problems. However, modern FPGA graph cut algorithm accelerators still need performance and memory ...
Abstract: Triangle classification is essential in graph analysis, such as for effectively detecting communities, evaluating clusters, and quantifying connection density. While traditional algorithms ...
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