EU Household Energy Consumption Declines For Third Consecutive Year

Steady Decline In Energy Use

European Union households consumed 9.54 million terajoules of energy in 2024, down 0.2% from 9.57 million terajoules in 2023, according to Eurostat. The decline marks the third consecutive year of lower residential energy consumption, following the 2021 peak of 10.98 million terajoules.

Residential Sector’s Energy Share

Households accounted for 26% of total final energy consumption across the European Union in 2024.

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Fuel Mix And Its Evolution

Natural gas remained the largest source of household energy, representing 29.4% of total consumption. Electricity accounted for 26.9%, while renewables and biofuels made up 22.8%. The figures illustrate the continued role of multiple energy sources in meeting residential demand across the bloc.

Thermal Comfort As A Priority

Space heating remained the largest household energy use category, accounting for 61.5% of total residential consumption. Water heating represented 15.6% of energy use, followed by lighting and electrical appliances at 14.8%. Cooking accounted for 6.4%, while space cooling represented 0.8%.

Year-Over-Year Shifts

Compared with 2023, energy consumption for space heating declined by 1.2%, while energy used for cooking fell by 0.9%. At the same time, energy demand for space cooling increased by 15.3%, and consumption related to lighting and electrical appliances rose by 2.6%. The data point to shifting patterns in household energy use, particularly in categories linked to cooling and electricity consumption.

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Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

by News Editor

August 6, 2026

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

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Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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