Welcome to the Beyond Digital Transformation Podcast - A platform for results driven mining professionals. This short soundbite is part of the Connectivity and Communication Stream Kick Off where Charles Nyabeze provides his mining ecosystem observations of AI & Machine Learning as it relates to the underground mining enviornment.
Neha Singh:
when we talk about mining underground mining operations, where's AI and machine learning, fitting into the journey.
Charles Nyabeze:
my comment on that would be like, look, mining is a complex system, and not only is there a complex system, but this is a system with so many other subsystems and, a long time ago I had a one mining see or say that, running a mining operation is like playing multi-level chess, where there's so much happening all over the place. and that it's very difficult for any one person. Do you not look a long time ago the shift boss could maybe have all the answers because there wasn't the complexity that was there, but nowadays, it's so complex and so many moving parts, so many moving pieces of equipment. So many fans turn on and off, so many inventories in motion. There's so much information, right? So I think, the advent of AI and machine learning is going to allow us to be able to zoom faster to the decision point, right? Because of all this variables that are coming together. So I think the need for AI and machine learning is actually going to accelerate the speed at which you make the decisions that we should without wasting our time looking at all the Non essential information because as it is right now, you know what, it's very difficult for the human brain to distinguish which information is relevant, not relevant when you're getting all the same information coming at in real time. So I think that's where it's coming from. And also the other piece too, is that, I think what's happening with mining is that, we actually missing out on getting the insights that are necessary to truly optimize operations, simply because we haven't been looking at the data and we haven't been crushing, crunching it properly. And I think some of the things that our AVEVA is doing as Martin and I were talking, a little bit earlier last week, just talking about how, the fact that the information is brought to it. And what it needs to be activated It can't just sit there and collect dust the data can not collect dust, but it needs to be activated so that the insights can be drawn out of it. So that's one thing that I'm observing, from some of the ecosystem