Mapping and Defining Architectures

Data Collection, Transformation, and Processing

Training and Deployment of GAIA

Model Validation and Retraining

Curation

Miners monitor a lot

You might have noticed that to comply with regulations, track parameters in real time, or even maintain production targets, miners use a wide array of equipment and sensors, generating data sometimes in fractions of a second. Seeing significant results and achievements by harnessing the full potential of this already generated data inspired us to develop GAIA. After more than a decade of gathering reliable datasets, developing robust algorithms, and training effective models, we can finally share our results with the mining industry.

FAQ

How can I contact support?

Please reach out to us at suporte@beyondmining.tech.

What will be done with my data? And who can access it?

The information you enter and any related scenarios are stored exclusively in the database linked only to your user account. In other words, neither we nor anyone else can access them—only you can.

What is the difference between GAIA and tools like ChatGPT, Midjourney, and Gemini?

Tools like ChatGPT, Gemini, and Midjourney, which are very popular today, are generative AIs. This means they produce probable—but not unique—responses based on their training data and the user’s input (prompt). The same prompt can generate different responses each time it’s used. In contrast, GAIA is built with algorithms that model processes, identify patterns, and predict outcomes objectively within a margin of error. It employs an engineering-focused, finite-scope approach, meaning the same input parameters will always produce the same result.

What is the Beyond Mining Curation?

The Beyond Mining curation encompasses the selection, organization, validation, and maintenance of information, data, and resources essential to the project. Additionally, it includes the training and deployment of models and solutions. This process involves identifying reliable information sources, gathering data, establishing standards and architectures, implementing best practices, and sourcing other materials and resources vital for development.