Continuous Learning technology is a type of real-time Machine Learning that continuously learns from business users and creates explainable AI powered by continuous data streaming. With continuous learning, businesses can adapt to changes in real-time, giving them an advantage over their competitors. In contrast, Batch Learning trains models with past data, which can quickly become outdated when changes occur in the world, requiring retraining of models and valuable resources from IT and data science teams. Continuous/Adaptive Learning ensures algorithms that adapt to changing real-life dynamics, guarantees more accurate models with less effort, and reduces the computational cost of modeling.
At TAZI, we have been providing our customers with robust and Adaptive Machine Learning (ML) solutions since 2016. Continuous/Adaptive Learning has become a hot topic due to the frequency and magnitude of change in business environments, speed of data and the quantity and complexity of Machine Learning models in use. Our product and intellectual property has been aligned with market needs since day one and now, we have a new patent that supports this alignment even further: “Continuously learning, stable and robust online machine learning system”, US Patent No 11,315,030.