AI Navigating the AI Fog of War This blog grapples with the AI “fog of war”, exploring future challenges Geolytix may face. Blair reflects on key themes from the recent Geographic Data Service partner conference.
Awards GEOLYTIX Named a Finalist in The 2024 A.I. Awards International Cloud Artificial Intelligence Awards Program Announces its Finalists. Geolytix are a finalist in the A.I. Implementation of the Year.
Awards GEOLYTIX Shortlisted in The 2024 A.I. Awards International Cloud Artificial Intelligence Awards Program Announces its Shortlist. Geolytix are amongst them and are up for three categories.
GeoData Interaction Surfaces explained: Why Context is Everything Christoph Mülligann, Chief Innovator at Geolytix, takes us behind the curtain of developing Interaction Surfaces and gives us his unique take on making sense of mobile data.
GeoData Interaction Surfaces: Illustrate The Complexity Of The City Our new MAPP tool, Interaction Surfaces, lets you interrogate complex pedestrian interactions in urban areas and start to see the wood for the trees.
Awards GEOLYTIX MAPP wins Innovation of the Year at the British Data Awards 2024 We are thrilled to win Innovation of the Year for GEOLYTIX MAPP and the British Data Awards 2024.
Our Team Geolytix Model Innovation Day Geolytix recently held a Model Innovation Day, an internal event to challenge our Data Scientists. Who was the model modeller at the end of the day?
Team Thoughts Featured Machine Learning within Location Planning Machine Learning is not new. We have used it in Location Planning for years, but new advancements mean now we can do more. Danny shares more about the Geolytix ML journey.
GeoData Machine Learning with spatial Big Data: How Uber helped us get there. Sometimes we look for answers outside our cosy little GIS bubble. In this case we applied well-established information retrieval techniques to truly understand hyperlocal movement patterns in mobility data.
GeoData Inferring Traffic Counts from Network Centrality We were recently asked by a client to incorporate an element of traffic and road utilisation into the modelling of their network blueprint as they investigate opportunities to locate drive-thrus.
