Based on interviews with dozens of deep learning teams, we've created a criteria for measuring the growth stages toward AI production at scale. In this guide:
What are scaling AI teams doing for scheduling and orchestration? How do they optimize compute and memory resources?
Data and compute readiness - how much compute do I need, how do I connect the data and the rest of the infrastructure?
Early stages of exploration and team building - what are teams focused on at the outset of an AI project?
