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This invention describes a computer method for managing tasks where you can't know how much work they'll take until you start them. As a task progresses, the system calculates how much work is left and compares that to the cost of using a computer resource. If the remaining work is high compared to the resource cost, the system prioritizes that task over others to ensure efficient use of computing power.
Why it matters: Filed before widespread adoption of advanced machine learning for real-time workload prediction and highly elastic cloud infrastructure. Modern AI could more accurately predict residual complexity and optimize resource allocation in dynamic serverless environments, making this approach more effective today.
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