Published @SME_MFG — With #AutoML 2.0, firms can leverage the wealth of data at a manufacturer’s disposal, to create ML/AI algorithms in a matter of days,” our CEO Ryohei Fujimaki shared his insights with SME for this article. #manufacturing #MachineLearning #DataScience #ArtificialIntelligence #ML and AI
Manufacturers must manage sensor performance and forecast supply chain issues and inventory. To create an effective AI algorithm for predicting equipment failures, we need to leverage existing sensor data as well as the skills of data scientists. AutoML 2.0 provides a solution to the manual development of AI/ML algorithms. Finding the right AutoML solution can be tricky. Manufacturers should focus on the product’s automation for feature engineering and how it can help them speed up their development lifecycle. Using API-based delivery of ML algorithms developed with AutoML systems makes retraining the algorithm easy but introduces too much latency for intelligent manufacturing operations. Manufacturers can deploy ML models within containers to achieve near real-time response times. Manufacturers rely on sensors to monitor production, but ML models can predict failures. Read the full article SME Manufacturing
