👉 Transfers computing is a paradigm that enables the seamless movement of computational resources, such as models, data, and algorithms, between different computing environments or platforms. This approach allows for more efficient utilization of resources by leveraging the strengths of various infrastructures, such as cloud services, edge devices, and specialized hardware like GPUs or TPUs. In a transfers computing setup, a model trained on one system can be transferred to another, either for inference (making predictions) or for further training, without the need to retrain from scratch. This not only accelerates the development and deployment of AI applications but also optimizes costs by allowing organizations to use resources where they are most effective, leading to better performance and scalability.
