1. Collect Drill Hole Data
Data is collected by physically drilling 100m into the ground, and then removing each rod
2. Analyze Core Samples
Samples are taken at multiple depths of each rod which are sent offsite to a chemical lab to get assayed. The assays on the core samples measure the mineral grade.
3. Collect Blasthole + Mill Data
Stratum's model learns from higher density data, such as production data, to model lower density data, such as drillholes.
4. AI Resource Model Construction
The Stratum AI model learns geological patterns from all historical data to construct more accurate mine resource model
Model identifies high grade lode previously undetected by kriging
AI more accurately determines boundaries of main mineralization
AI extrapolates from several known samples the direction of a vein
Daniel is a machine learning engineer from the University of Toronto. He has worked with data science teams at pre-seed to late stage startups in industries such as pharmaceuticals, marketing, and agriculture. Daniel's inspiration is to do his part to make sure the mining industry is not left behind in the upcoming AI revolution.
Farzi is a quantum computing hardware and machine learning engineer from the University of Waterloo. Her undergraduate work in materials sciences, nanofabrication, and quantum electrodynamics informed her direction towards quantum computing, and later, with her acquired machine learning skillset, quantum machine learning. Her career inspiration is to design elegant solutions to tough problems - this has allowed her to work in fields like tissue engineering, telecom, and photonics.
Ilia is a statistician and deep learning researcher from the University of Waterloo. His research focuses on improving machine learning performance through the analysis and optimization of data. He has consulted more than two dozen companies, ranging from pre-seed startups to large defense contractors, helping them leverage their data for better outcomes. His latest research on enabling machine learning from small data has been described by MIT Technology Review, Digital Trends, and other major outlets as a technology that could help democratize AI.
David is a highly experienced geologist with over 35yrs of mineral exploration experience, primarily focused on the discovery of world-class Cu &/or Au deposits in Australia, SW Pacific, East & SE Asia, Europe and North America. He also has familiarity exploring for base metal (VMS, sed-hosted Cu, SEDEX Zn-Pb) and Ni-sulfide / PGM deposits. David has held a number of senior technical and management roles for Billiton, BHP Billiton, Phelps Dodge and Freeport-McMoRan, primarily focused on generating and evaluating exploration opportunities. He is a graduate from the Royal School of Mines, Imperial College, London.