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The Shift in European Working Hours: What’s Behind the Decline?

Over the last decade, workers across Europe have seen a gradual reduction in weekly working hours. On average, the EU has experienced a drop of one hour per week, amplifying to more than an hour in nearly half of its 34 nations.

Where Do Europeans Work the Longest?

According to recent data, countries in Southern and Eastern Europe endure the longest workweeks. Turkey leads at 43.1 hours, followed by Serbia and Bosnia. In contrast, nations like the Netherlands exhibit significantly shorter working weeks, highlighting strong labor protections.

Decadal Shifts in Working Times

From 2014 to 2024, only four countries witnessed an uptick in working hours, with Serbia marking a rise of 1.7 hours. Meanwhile, Iceland and Turkey underwent the steepest declines, exceeding three hours.

Why Are Working Hours Declining?

Declines are closely tied to increased part-time work and greater female workforce participation, with many opting for flexible hours. A study mentioned by the ECB attributes this decline to technological advancements and voluntary part-time employment. Seeking a balance between life and work reflects increased income levels and a diminishing drive to clock in longer hours.

These dynamic factors reshape Europe’s labor markets, marking a cultural and economic shift.

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

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.

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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