SensOre (ASX:S3N), both a mineral explorer and a developer of artificial intelligence-powered geological interpretation software, has found early stage evidence of gold mineralisation at a target it was led to by its software algorithms.
The company let loose its proprietary machine learning program on a range of local data for the Yilgarn Craton area in which the Balagundi project is placed. SensOre teams up with privately held Gold Road Resources on-site.
The big takeaway?: SensOre has found gold mineralisation in aircore drilling exactly where its AI software thought gold would be located.
While the software has not led to a fresh discovery of bonanza grade gold, the successful discovery of shallow trace gold does support SesOre’s overall thesis on its own technology.
Investor information provider Undervalued Equity calls high-grade gold projects anything with over five grams of gold per tonne in ore (5g/t). Many Australian projects boasting grades of 4g/t are also widely accepted as high grade.
Low-mid grades typically capture concentrations of around 2g/t.
With that in mind, SensOre reports:
09m @ 0.81g/t gold from surface, including:
04m @ 1.19g/t gold from 2m
24m @ 0.48g/t gold from 13m, including:
04m @ 2.03g/t gold from 13m
The drillhole turning up today’s results was sunk near a previous strike target which reported the below results. It is undisclosed to what extent SensOre’s AI software hinged on that previous drillhole in targeting a fresh area.
Previous results include:
34m @ 0.54g/t gold from 96m, including:
01m @ 05.4g/t gold from 96m
16m @ 0.80g/t gold from 114m, including:
02m @ 03.6g/t gold from 114m
While these grades may not inspire the imagination, it’s worth noting Balagundi has historically pushed out some 4,000oz of gold.
The bigger thing to note here could very well be the evolving fortitude of SensOre’s AI tech development capacity, as opposed to the gold hits in question.
Shareholders are also still waiting for over 15km of assay results to come back from SensOre across various projects. Sector-wide delays in assay laboratories continue to taunt Australian investors.
“The results in the central corridor, where the AI target was identified, supports deeper targets predicted from the modelling,” SensOre CEO Richard Taylor said.
“Conventional target testing using gravity, geochemistry, drilling, and mapping has been augmented with machine learning, including the application of SensOre’s new SimClust workflow.”
Get the latest news and insights direct to your inbox