Comet Lithium Collaborates With VRIFY To Reveal New Exploration Targets Using Machine Learning Technology

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ROUYN-NORANDA, QC, March 4, 2024 /CNW/ - Comet Lithium Corporation (TSXV: CLIC) (FSE: 8QY) ("Comet Lithium" or the "Corporation") is pleased to announce that it is collaborating with VRIFY Technology Inc. ("VRIFY") to, among other things, generate targets from a proprietary machine learning algorithm. The algorithm will be trained using previously disclosed data along with other publicly available information related to the Comet Lithium properties. It will generate multiple scenarios, which will be continually refined as new data becomes available or is published in the public domain. The VRIFY machine learning tool will provide an additional layer of information to enhance Comet Lithium's exploration database and exploration programs.

Vincent Metcalfe, the Executive Chair and CEO of Comet Lithium, commented, "We are thrilled to announce our collaboration with VRIFY, which will leverage machine learning algorithms to actively identify new exploration targets within Comet Lithium's portfolio of properties. This innovative approach will significantly enhance the prospectivity of our properties by adding new targets to our exploration pipeline."

The initial phase of VRIFY's collaboration is focusing on Comet Lithium's 100%-owned Liberty lithium property, and the initial targets generated to date by VRIFY will be presented by Comet Lithium and VRIFY on Monday, March 4, 2024, at 1:00 p.m. (eastern time) at the PDAC Convention in Toronto, Canada. The presentation will be held at VRIFY's lounge (Booth 3321) on the Investors Exchange Floor at the Metro Toronto Convention Centre, located at 255 Front Street West, Toronto, Ontario M5V 2W6. It is expected that the algorithm will generate additional targets on Comet Lithium's properties, including on its Liberty property, as additional work is completed on such properties and data of neighbouring properties also becomes publicly available.

VRIFY Artificial Intelligence System

VRIFY's artificial intelligence ("AI") targeting system uses a combination of deep learning and computer vision architectures to train predictive models with data from various exploration features like drillholes, rock geochemistry, and mineral occurrences. The approach leverages complex data relationships to predict mineral exploration targets, streamlining the process of identifying viable mineral deposits. The automation of target generation will allow the trained model to be updated quickly with new data from ongoing exploration work. By using locally trained models, VRIFY will be able to deliver prediction accuracy metrics and feature importance maps, giving true insight into exploration vectors.