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Recently, Andreas Schierenbeck, CEO of Hitachi Energy, the world's largest transformer manufacturer, stated in an interview with the Financial Times that as large technology companies see a surge in power demand when training artificial intelligence models, governments need to take measures to limit these fluctuations to ensure the stability of the power supply. Image source note: The image is generated by AI, and the image licensing service provider is Midjourney. Schierenbeck said that the power demand fluctuations in AI data centers are extremely severe,

On June 30th, the world's first trillion-parameter large model for the power generation industry, Qinyuan, developed independently by the State Energy Group, was officially released. This innovative large model, with its unique full-stack independent and controllable characteristics, marks an important step forward for the power generation industry into a new era of intelligent decision-making. The Qinyuan large model aims to integrate the diverse scenarios, high complexity, and strong professionalism of the power generation industry, fully utilizing the State Energy Group's globally largest installed capacity and massive data resources. The launch of this model not only creates a new engine for multi-energy coordination and dynamic optimization, but also establishes an electricity

Recently, SoftBank and Intel have jointly developed a new AI-specific memory chip aimed at significantly reducing power consumption to provide more efficient support for Japan's AI infrastructure. According to Nikkei Asia, the goal of their cooperation is to design a new type of stacked DRAM chip. The wiring method of this chip will be different from the popular High Bandwidth Memory (HBM) on the market, expected to reduce power consumption by about 50%. Image source note: The image was generated by AI, and the image rights service provider is Midjourney.

According to a new analysis, the power consumption of artificial intelligence is expected to reach nearly half of the total electricity consumption of global data centers by the end of 2025, meaning AI energy consumption will soon surpass bitcoin mining. The analysis was conducted by Alex de Vries-Gao, a Ph.D. student at the Environmental Institute of Vrije Universiteit Amsterdam. He has previously tracked the power consumption and environmental impact of cryptocurrencies and published related data on his website Digiconomist. Currently, AI has already accounted for a significant portion of data center energy usage.

PJM, the largest electricity grid operator in the United States, recently announced a partnership with Google and its subsidiary Tapestry to leverage artificial intelligence (AI) to transform how it manages its power system. This collaboration is expected to accelerate the integration of new power sources and address challenges such as delays in approving renewable energy projects and risks of power shortages. PJM noted in a press release that the project will mark the first use of AI to manage grid interconnection requests. Tapestry

Accurate power generation forecasting and supply-demand management are crucial for the rapid development of the new energy industry. On March 26, Ant Group released its new energy power time series large model – EnergyTS. This model aims to help companies optimize their business strategies and improve operational efficiency through high-precision data analysis. EnergyTS demonstrates particularly strong performance in photovoltaic scenarios, surpassing Google's TimesFM-V2.0 and Amazon's Chronos-Lar in power generation prediction accuracy.

On March 26th, at the Spring Summit of the New Energy Digital Asset Community in Suzhou, Ant Group officially launched EnergyTS, a time-series model for energy and power. This marks a significant breakthrough for Chinese companies in the field of energy AI. Specifically designed for the new energy sector, EnergyTS demonstrated significantly higher accuracy in photovoltaic power generation prediction compared to leading international general-purpose time-series models such as Google's (TimesFM-V2.0) and Amazon's (Chronos-Large). In T+1 day prediction, the model's mean absolute error is only...

EcoDataCenter, a Swedish sustainable data center company, has received $478 million in funding to expand its operations and build more environmentally friendly data centers.

At the recent 360 Nano AI search event for new energy vehicles, Zhou Hongyi, founder and chairman of 360 Group, shared in-depth insights on the widely-discussed DeepSeek. He highly praised its open-source spirit and its positive role in advancing the industry.

Recently, a study conducted by the non-profit organization Epoch AI revealed the energy consumption of OpenAI's chatbot platform ChatGPT, showing that its energy use is significantly lower than earlier estimates. According to some reports, ChatGPT consumes about 3 watt-hours of power to answer a question; however, Epoch AI's research suggests that this figure has been overstated. The study indicates that when using OpenAI's latest default model GPT-4o, the average energy consumption per query is only...

The $100 billion Stargate project plans to source some of its electricity from solar energy and batteries. According to Bloomberg, the renewable energy facilities for this project will be constructed by SB Energy, a subsidiary of SoftBank, but this is not the only energy source for the project. Stargate is a collaboration between OpenAI, Oracle, and the SoftBank Group aimed at establishing a large number of new data centers to accelerate the rapid development of artificial intelligence applications. Image source note:

Silicon Valley giants were once the most vocal advocates and generous financiers of clean energy investments, but they may now become the biggest villains in the renewable energy revolution. With surging energy demands from artificial intelligence, emissions from large tech companies have spiked, making their lofty decarbonization goals increasingly elusive. Tech giants, including Google, Meta, Microsoft, and OpenAI, are pushing for greater deployment of renewable energy infrastructure and research into new forms of clean energy, but keeping up with the enormous energy demands of AI is a daunting task.

With the surge in demand for artificial intelligence and large-scale data processing, data centers, as the infrastructure for these operations, are having an increasingly negative environmental impact. A recent research report delves into the environmental and regulatory issues associated with AI data centers, highlighting the urgent need for improvements in the current policy framework to address the growing consumption of energy and water resources. Image source note: The image is generated by AI and licensed through the service provider Midjourney. The research report emphasizes significant gaps in the current approaches of the EU and the US in this field, calling for countries to develop more robust regulations.

According to the Globe and Mail, the Canadian federal government is considering introducing incentives of up to CAD 15 billion to encourage major domestic pension funds to invest in AI data centers powered by green energy. This proposal was made during private consultations with pension funds and may be considered as part of the government's fall economic statement. Image source note: Image generated by AI, image authorized by service provider Midjourney. With the rapid development of AI technology, platforms like OpenAI's ChatGPT.

Meta is investing $10 billion to build a large AI data center in Richland Parish, Louisiana. This data center will be the largest of Meta's 20 data centers, with construction expected to begin this month and continue until 2030. It is reported that it will be optimized to support Meta's AI workloads, aiding in the operation of Meta's technologies including Facebook, Messenger, Instagram, WhatsApp, and Threads.