How AI is improving simulations with smarter sampling techniques

Imagine you’re tasked with sending a team of football players onto a field to assess the condition of the grass (a likely task for them, of course). If you pick their positions randomly, they might cluster together in some areas while completely neglecting others. But if you give them a strategy, like spreading out uniformly across the field, you might get a far more accurate picture of the grass condition.Now, imagine needing to spread out not just in two dimensions, but across tens or even hundreds. That’s the challenge MIT…

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