• 강사 : 황의종 교수 (KAIST 전기및전자공학부)
• 일시 : 2020. 6. 25 (목) 17:00~18:30

Software 2.0 is a fundamental shift in software engineering due to the success of Artificial Intelligence (machine learning) using Big data. Previous software development involved implementing specific features and testing the code. In machine learning, data is on par with code, and models are the new software. Developing a model involves data collection, analysis and validation, followed by model training, analysis, validation, and serving. Several companies have developed solutions to make such end-to-end machine learning easy for everyone. For example, Google and DataBricks are developing and opensourcing TensorFlow Extended (TFX) and MLflow, respectively. This talk focuses on data management research challenges that occur in Software 2.0 and their current solutions.