Brightstar Resources has reported a 305.4m gold intercept grading 1.82g/t from 351.9m depth in hole TMHRCD26020 at the Two Mile Hill–Shillington deposit, Sandstone project, Western Australia, indicating a mineralised intrusion roughly three times wider than previous models. The intercept is unconstrained at depth, suggesting continuity beyond the current 657.3m end-of-hole and potential for a large-tonnage, bulk underground target rather than narrow-vein stoping. For resource modellers and mine planners, the result may justify revising intrusion geometry, tonnage estimates and potential underground development scenarios.

Artificial intelligence is being rolled out across mines for tasks such as mill optimisation, predictive maintenance and fleet dispatch, but its success still hinges on experienced operators, metallurgists and geotechs defining constraints and validating outputs. Vendors are pairing machine-learning models with domain-specific tools – for example, digital twins of crushers and grinding circuits, or AI-assisted short-interval control in fleet management systems – to capture tacit knowledge from senior crews. The message for sites is to treat AI as an augmentation layer on existing control, planning and reconciliation workflows, not a plug‑and‑play replacement for human judgement.

Vulcan Energy’s Lionheart lithium project in Germany’s Upper Rhine Valley is advancing as a geothermal brine operation backed by more than $3 billion in international funding to support Europe’s energy and critical raw material resilience. The project targets lithium extraction from deep geothermal reservoirs, pairing baseload renewable power generation with direct lithium recovery to supply European battery and automotive supply chains. For geotechnical and process engineers, the scheme centres on managing high-temperature brine production wells, reinjection strategies, and closed-loop fluid handling to minimise surface footprint and chemical consumption.