Series 16 – Episode 6 – Generative AI: an industrial use case
Summary
Using advanced algorithms, companies can rapidly create and evaluate multiple design iterations, optimising factors such as cost, materials, and performance. Di Segni explained how it optimises complex processes through large-scale data analysis, facilitating more efficient operations by suggesting improvements. Additionally, Di Segni highlighted supply chain optimisation: “GenAI can simulate various scenarios to anticipate disruptions and recommend adjustments, making enterprises more resilient and adaptable to market shifts.” This predictive capability allows enterprises to better manage supply chains by simulating potential disruptions and suggesting preventive measures, adding a layer of adaptability in volatile markets. SECO has focused on integrating GenAI with Edge computing to drive real-time data processing and decision-making, which is essential for responsive and safe industrial settings. Di Segni envisioned a future where devices powered by GenAI are not just tools but intelligent partners capable of optimising operations and anticipating user needs.