Many different solutions can overcome hardware and software limitations. Some can be achieved within the organization, such as by allocating internal staff with more experience to evaluate and refine the particular model. Another example may be in the training data sets themselves—they may need proper cleaning and preparation to limit their impact on resources. In other situations, using external resources, such as a cloud-based infrastructure platform, can let teams scale more easily with greater flexibility to handle compute demands.