The Artificial Intelligence Group involves careers that integrate AI models into applications, making sure they work well within larger systems. They handle the deployment and scalability of AI solutions. Their role involves working with different teams to develop and maintain AI applications, ensuring they perform reliably in real-world situations. Generative AI, as an example application of AI engineers, involves developing algorithms and systems that can autonomously create new content, such as realistic images, videos, or even entire virtual worlds, based on learned patterns and data.

The Data Science group involves careers that analyze data to find useful insights and help make better decisions. They build models to predict outcomes and ensure data is clean and ready for use. They also communicate their findings clearly to stakeholders through reports and visualizations. In healthcare, data science is used to analyze patient data for predictive analytics, improving diagnosis accuracy, and personalizing treatment plans.

The Machine Learning Group involves careers that create and improve models that learn from data. They turn research models into practical tools, making sure they are efficient and can handle large amounts of data. Their work involves a lot of programming, tuning models, and setting up systems for training and deploying these models. In architecture, machine learning is used to optimize building designs by predicting structural performance, energy efficiency, and material usage based on vast amounts of design and environmental data.