Studio Lab is currently available in public preview. The service is based on open-source JupyterLab and provides free access to AWS compute resources. To begin, a user creates an account (separate from an AWS account) and selects whether they need a CPU or GPU instance for their project. The service offers 12 hours of CPU or four hours of GPU per user session, with an unlimited number of user sessions available. Users get a minimum of 15 GB of persistent storage per project. When a session expires, Studio Lab will take a snapshot of the environment, so users can pick up right where they left off. AWS is using SageMaker Studio Lab to launch the AWS Disaster Response Hackathon, which aims to inspire ideas for using machine learning to tackle challenges related to natural disaster preparedness and response. The hackathon runs through February 7, 2022, and it’s offering a total of $54,000 in prizes. AWS is also attempting to set the Guinness World Record for the “largest machine learning competition.” Meanwhile, AWS is also launching a new $10 million scholarship to help students pursue careers in machine learning and AI. The AWS Artificial Intelligence and Machine Learning Scholarship (AWS AI & ML Scholarship) program is designed to serve high school and college students who are underserved and underrepresented in the field. The program uses AWS DeepRacer and the new AWS DeepRacer Student League to teach students foundational machine learning concepts.
