Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Databricks, a company specializing in data lakehouse technology, announced on Tuesday a new platform designed for the manufacturing industry. Called lakehouse for manufacturing, the platform aims to unify data and artificial intelligence (AI) for various analytics use cases such as predictive maintenance, quality control and supply chain optimization. The platform builds on Databricks' core data lakehouse platform, which leverages Delta Lake, Apache Spark and MLFlow, open-source projects that enable scalable data processing and machine learning (ML) workflows. The platform also integrates with model serving, a service that Databricks introduced last month to simplify the deployment and management of ML models in production.

Don't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution accelerator for adverse drug event detection. The World Health Organization defines pharmacovigilance as "the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine-related problem." While all medicines and vaccines undergo rigorous testing for safety and efficacy in clinical trials, certain side effects may only emerge once these products are used by a larger and more diverse patient population, including people with other concurrent diseases. To support ongoing drug safety, biopharmaceutical manufacturers must report adverse drug events (ADEs) to regulatory agencies, such as the US Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in the EU. Adverse drug reactions or events are medical problems that occur during treatment with a drug or therapy.