Artificial intelligence (AI) has the ability to enhance human capabilities and increase productivity in any industry, which is a critical component for companies that want to succeed in the competitive mining environment.
As technology continues to advance, AI has become a valuable ally in this mission, and within AI, Transformers’ neural networks stand out.
This technology is the same technology behind systems such as ChatGPT (OpenAI), BARD (Google) and LlAMA (Meta). Transformers neural networks are a type of AI natural language processing model used to solve a variety of sequence analysis problems such as language modeling.
Since their introduction in 2017, they have displaced other technologies, but have never been more popular. Its success relies on the ability to process information in parallel through an attentional mechanism that eliminates the need for repetition.
The hardware these models run on (GPUs) is optimized for parallel computing, which allows the networks to be trained faster and with a larger amount of data. Training efficiency also allows many more different combinations of model hyperparameters to be explored, resulting in solutions that are closer to the global optimum.
However, its applicability goes beyond text processing and provides robust and efficient solutions to multiple areas and challenges, including process optimization, anomaly detection, and customization of services for mining.
The strength of Transformers neural networks lies in their ability to analyze large amounts of data efficiently and accurately. These networks can process and learn from production data in real time to accurately model production processes at mining sites. This leads to the ability to automatically identify patterns and trends, allowing companies to anticipate problems before they occur and optimize their operations to maximize efficiency. Element that becomes key in the mining industry.
In addition, by modeling the relationship between different production processes, scenarios can be simulated to recommend optimized solutions that meet the operational needs of the industry and enable energy savings, time reduction, quality maximization and accident prevention. All this through optimization platforms through genetic algorithms.
Transformers can also automate tasks that previously required a lot of time and resources. For example, the automatic detection of anomalies in production data. These anomalies can indicate equipment malfunctions or irregular behavior in the work environment, and all can lead to major financial losses if not detected and corrected in a timely manner. This automation allows human teams to focus on more strategic tasks. By reducing the time and resources spent on these tasks, companies can save money and increase operational efficiency.
Another important aspect of these neural networks is their ability to constantly adapt and learn. As production data changes and evolves, Transformers can adapt and learn from this new data. This ensures that the solutions they provide are always relevant, up-to-date and personalized, which is crucial in the dynamic world of mining. This gives you a better experience with users and allows you to stand out from the competition in today’s highly competitive environment.