Training the neural networks—the complex AI algorithms—that safely steer autonomous vehicles requires testing them against millions of rare driving anomalies, a process that demands massive cloud computing budgets. How can software engineering departments structure collaborative graduate research labs so students get hands-on experience with these expensive cloud simulation frameworks without causing severe institutional budget deficits?
