What fundamental infrastructure bottlenecks exist when scaling modern artificial intelligence workloads on legacy cloud providers?
Founder & CEO at Modal
Traditional cloud hyperscalers were architected two decades ago for persistent virtual machines running long-lived monolithic web servers. Modern artificial intelligence applications require instantaneous container provisioning, massive parallel GPU execution, and zero idle overhead. Waiting four minutes for a GPU node to spin up in a legacy cloud environment destroys the user experience for real-time inference. Modern infrastructure must cold-start containers in under a second.
This answer is part of a full interview with Erik Bernhardsson, Founder & CEO at Modal.
Found this insight valuable? Share it with your network to help others learn from Erik Bernhardsson's experience.
Cite This Answer
Use this answer in your research, article, or academic work