- OBM, Inc. introduces a pioneering energy curtailment solution for AI computing, extending its Foreman platform.
- The new product offers pause-less energy management, allowing continuous AI operations without disruptions during grid balancing.
- Foreman has previously curtailed over 2.5 million megawatt hours, demonstrating its effectiveness in energy optimization.
- The solution addresses the escalating energy demands of AI models, such as ChatGPT, which require significant power and strain power grids.
- During curtailment events, OBM’s technology can redirect over 80% of the AI load back to the grid.
- The new offering provides rapid bidirectional energy adjustments, enhancing grid frequency regulation.
- OBM’s solution aims to reduce energy costs for hyperscalers and support sustainable AI training practices.
Main AI News:
Energy management leader OBM, Inc. has announced the launch of a pioneering solution designed to mitigate energy loads associated with artificial intelligence (AI) computing, responding dynamically to grid conditions. This innovative product, an extension of OBM’s Foreman platform—which manages large-scale energy and operational loads—represents the industry’s first pause-less energy curtailment software. It ensures continuous AI operations without interruptions during grid balancing events.
OBM’s Foreman software has previously curtailed over 2.5 million megawatt hours, equating to the energy needs of an average U.S. home for 250,000 years. Leveraging Foreman’s robust capabilities, OBM’s new offering addresses the critical need within the AI sector: managing energy consumption without disrupting ongoing model training or inference processes.
The energy demands of AI computing are escalating rapidly. For instance, AI models like ChatGPT consume power equivalent to approximately 180,000 U.S. households daily, with individual queries requiring up to ten times more electricity than a Google search. This surge in energy consumption places substantial strain on power grids, creating a pressing need for sustainable solutions. OBM’s new product meets this demand by allowing automatic load reductions while maintaining AI processing operations.
During curtailment events, OBM’s technology can redirect over 80% of the AI load back to the grid. With AI’s increasing energy appetite, OBM’s solution emerges as a significant grid-balancing asset, rivaling the cryptocurrency mining sector for its rapid load adjustments and minimal user impact. Foreman’s bidirectional capability to adjust AI workload energy demands within a second offers unprecedented flexibility for grid frequency regulation.
“OBM remains committed to enhancing energy flexibility for large loads and sectors previously considered rigid,” stated Daniel Lawrence, CEO of OBM. “Our new solution addresses the substantial energy demands of AI computing, advancing industry capabilities and supporting our customers.“
Rooted in its extensive experience managing large-scale Bitcoin mining, OBM continues to drive energy agility with Foreman, which has already saved clients over $66 million through efficient energy management.
Jeremy Ellis, Director of Power Strategies at OBM, remarked, “We are thrilled to introduce this first-to-market AI computing energy curtailment software, which will not only lower energy costs for hyperscalers but also promote a sustainable future for AI training that minimizes stress on energy grids.“
Conclusion:
OBM’s launch of its innovative AI energy management solution represents a significant advancement in addressing the growing energy demands of artificial intelligence. By offering pause-less curtailment and real-time load adjustments, OBM not only enhances operational efficiency for AI computing but also supports grid stability and sustainability. This development positions OBM as a key player in the energy management market, particularly as AI’s energy consumption continues to escalate. The ability to minimize disruptions while optimizing energy usage will likely drive increased adoption among hyperscalers and contribute to more sustainable practices in the industry.
