Federated Learning (FL) offers a promising approach for collaborative machine learning across distributed devices. However, its adoption is hindered by the complexity of building reliable communication architectures and the need for expertise in both machine learning and network programming. This paper presents a comprehensive solution that simplifies the orchestration of FL tasks while integrating intent-based automation. We develop a user-friendly web application supporting the federated averaging (FedAvg) algorithm, enabling users to configure parameters through an intuitive interface. The backend solution efficiently manages communication between the parameter server and edge nodes. We also implement model compression and scheduling algorithms to optimize FL performance. Furthermore, we explore intent-based automation in FL using a fine-tuned Language Model (LLM) trained on a tailored dataset, allowing users to conduct FL tasks using high-level prompts. We observe that the LLM-based automated solution achieves comparable test accuracy to the standard web-based solution while reducing transferred bytes by up to 64% and CPU time by up to 46% for FL tasks. Also, we leverage the neural architecture search (NAS) and hyperparameter optimization (HPO) using LLM to improve the performance. We observe that by using this approach test accuracy can be improved by 10-20% for the carried out FL tasks.

THINK Surgical, a technology innovator developing orthopedic surgical robots, announced a collaboration with UK based digital health company, Definition Health. The companies will jointly develop a seamless, web-based, connected care solution to enhance the surgical planning experience for surgeons using THINK's robotic technologies for joint replacement surgery. This web-based solution will support all of THINK's robotic products, including new product launches planned for 2023. In addition, this web-based solution will incorporate Definition Health's Total Digital Surgery platform which assists hospitals and surgeons in achieving workflow efficiency, improved perioperative care and virtual follow up for surgical patients. Definition Health's platform is widely deployed in the UK with customers reporting improved profitability for surgical service lines as well as improved patient and provider satisfaction rates.