The Elements of Innovation Discovered
The Elements of Innovation Discovered
StartUs Insights ranks tech savvy firms impacting the sector Metal Tech News – September 2, 2020
AI and machine learning can assist in the compilation, organization, and analysis of large datasets to predict and generate mineral exploration targets.
StartUs Insights' global startup heat map highlights five emerging companies developing artificial intelligence solutions for mining exploration and illustrates the geographic distribution of all 88 companies analyzed.
StartUs Insights, a global data science company that specializes in technology startup companies, recently named its top five artificial intelligence mineral exploration startups.
AI and machine learning are showing the potential to improve the success of utilizing increasingly large and complex datasets needed to identify economically viable sources of ore that are become scarcer and deeper in the earth.
Mineral exploration involves the collection, processing, and interpretation of large amounts of geological, geochemical, and geophysical information.
Advancements in aerial imaging, including drones, assists mineral prospecting and drill targeting but adds another layer of data for mineral exploration companies to process and consider.
AI and machine learning drive innovation with analytical algorithms that can assist in the compilation, organization, and analysis of these large datasets to predict and generate mineral exploration targets. Thus, improving the traditionally low success rate of mineral exploration.
Analyzing 88 mineral exploration AI startups, Austria-based StartUs listed Minerva Intelligence, OreFox, Datarock, Earth AI, and Aganitha Cognitive Solutions as companies developing the best solutions in this field.
Canadian startup Minerva Intelligence's TERRA Mining AI, offers mineral exploration companies a suite of software and cognitive AI applications designed to organize mineral exploration data, streamline document management, and identify new targets.
By combining AI, geological models, and exploratory data, Minerva's TERRA AI platform allows mineral explorers to standardize their mining and exploration data. This enables them to find, share and use that data for more sophisticated analytics by either a human or through machine learning and reasoning. As a result, TERRA reduces operating costs and improves returns on investment for mining exploration companies.
Much like Minerva, Australian startup OreFox uses machine learning to assist in the speed and success of mineral exploration by better leveraging the available data.
OreFox offers two AI systems, Prospector and Hunter, for mining exploration.
Prospector AI is a data-driven system that specializes in greenfield exploration where data is limited. Using deep learning algorithms, Prospector AI uses a supervised deep learning algorithm that compares data from areas yet to be explored against the data of known economic mineral deposits.
Hunter AI is a hybrid system that utilizes both deep learning and machine learning to further refine targets generated from the Prospector AI.
The output of these combined systems is a prospectivity map and spatial dataset which highlight the target exploration areas.
Australian startup Datarock utilizes computer vision and deep learning algorithms to assist in mining exploration.
Datarock says the massive amount of information available from core photos, one of the cheapest and most routinely collected datasets within mineral exploration and mining, is not currently being utilized to its full potential.
Datarock Core, the startup's cloud-based image analysis platform, extracts several important types of geological and geotechnical information from core imagery.
After uploading images and metadata to a Datarock web portal, the startup's deep learning processes the images and generates models that can be further analyzed to extract geological and geotechnical features of interest.
Australian startup Earth AI develops AI-based mineral exploration technologies that include mineral targeting, drone geophysics, and autonomous drilling.
The company says its Earth AI vastly increase mineral deposit targeting by training the AI with proprietary global mineral exploration datasets; and its drone magnetic surveys can be carried out 10 times faster and at the fraction of the cost of similar surveys carried out with conventional manned flights.
Earth AI is also pioneering low-impact drilling hardware systems as well as automated drill sensing and control technologies that are expected to reduce environmental impact, eliminate operator errors, and streamline operations.
As a result of automation, the geologists will spend less time collecting the geological data and more time interpreting the results.
Indian startup Aganitha Cognitive Solutions creates AI-based mining exploration models by combining geological, geographical, and geophysical data. Moreover, machine learning enables the startup to generate mineral deposit leads and enables them to identify potential hot spots for exploration.
StartUs Insights delved into its more than 1.1 million startups and emerging companies to build its list of 88 mineral exploration AI startups used to create its list of top five.
While these companies came out on top of StartUs Insights list of artificial intelligence mineral exploration startups, the Austria-based data science firm said any of the other 83 companies analyzed in this field could meet mineral exploration AI needs.
"While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence so you can achieve your goals faster," wrote StartUs Insights.
"Depending on your specific criteria, the top picks might look entirely different," the data company added. "To identify the most relevant solutions based on your specific criteria, get in touch."
With more than 16 years of covering mining, Shane is renowned for his insights and and in-depth analysis of mining, mineral exploration and technology metals.
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