Eurostat Report Signals Modest Contraction In European Services Production

Overview Of Recent Sectoral Trends

New data released by Eurostat showed seasonally adjusted services production declining by 0.3% in both the euro area and the wider European Union during February. The decline followed stronger performance in January, when services production increased 1.0% in the euro area and 0.4% across the EU. Despite the monthly slowdown, annual figures remained positive, with services production rising 1.4% year-on-year in the euro area and 1.3% across the EU.

Sector-Specific Performance

Within the euro area, transportation and storage activities recorded a modest monthly increase of 0.2%, while accommodation and food services declined 0.6% and real estate activities fell 0.4%. Information and communication services experienced the sharpest monthly contraction, dropping 2.0%. At the same time, professional, scientific and technical activities increased 0.5%, while administrative and support services remained broadly stable.

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A similar trend emerged across the EU, although transportation and storage services declined 0.3%. Meanwhile, professional and scientific activities recorded a stronger monthly growth of 1.0%, while administrative and support services posted a slight increase of 0.1%.

Member State Dynamics

Performance varied significantly between member states during the month. Estonia recorded the steepest monthly decline at 16.3%, followed by Luxembourg at 9.5% and Denmark at 3.0%. By contrast, Bulgaria posted the strongest monthly increase at 4.6%, while Hungary and Poland recorded gains of 3.7% and 1.4% respectively.

Year-On-Year Performance And Sectoral Leadership

From an annual perspective, information and communication services remained one of the strongest-performing sectors, increasing 4.0% in the euro area. Professional, scientific and technical activities also recorded solid annual growth, rising 2.3% in the euro area and 3.0% across the EU. Accommodation and food services remained the only major sector to post an annual decline, falling 0.8% in the euro area. At the national level, Hungary led annual growth with an increase of 7.6%, while Bulgaria and Slovenia each recorded growth of 6.3%. Meanwhile, Romania experienced the steepest annual contraction at 5.3%, with Denmark and Lithuania also reporting declines compared with the previous year.

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Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

by THEFUTURE.TEAM

October 13, 2026

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

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According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

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