Artificial Intelligence in Industry: Secil’s example
Ricardo Carvalho addressed the various challenges that A.I. poses in the industrial environment. In addition to Generative A.I., which creates content, much of the A.I. applications in industry use other algorithms, from machine learning to deep learning. According to Secil’s digital director, this is probably the biggest wave of opportunities in the last 20 years since the Internet. However, “implementing these A.I. applications requires overcoming difficulties in the industrial environment. The Semapa Group has industrial facilities with recent equipment, but also some that are 100 years old, such as the Maceira-Liz Factory. The big challenge is finding a way for the existing factory data to be used by A.I. and integrated into a contiguous system, making it much easier to scale from one facility to another.”
Secil currently has several activities integrating Generative and Non-Generative A.I. “An interesting example is what we are doing in the concrete business. We have predictive models from the concrete plant to the arrival at the site to obtain data related to viscosity, which allows us to ensure that the final product is increasingly of better quality”, Ricardo Carvalho mentions.
Finally, Secil’s digital director stressed the need to increase A.I. literacy to reduce the perception of A.I. as a threat and ensure employees feel well prepared to use A.I. tools effectively in the future.