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The report says that it uses machine learning to predict peak demand and to recommend start-up and ramp-down times. Comparing weather-normalized use with the software off and on, the evaluators found that the building used 4.2% less electricity and 5.0% less gas. In three simulated demand response events, demand fell by 8% on average. Continuous demand management produced no measurable reduction. Hot calls from occupants rose 154% and cold calls 50%, and staff switched the software off on the last day. 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