European Commission Defends Entry/Exit System Amid Airport Delay Concerns

The European Commission has rejected claims that the new digital Entry/Exit System, or EES, is to blame for the long delays reported at some European airports, arguing instead that the real problem lies in long-standing weaknesses in airport infrastructure and staffing.

Brussels Points To Structural Weaknesses, Not The New Border System

Responding to questions from journalists, Markus Lammert, the Commission’s spokesman for home affairs, said the EES is operating smoothly across the vast majority of European Union border crossing points.

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According to the Commission, the bottlenecks seen at certain airports are largely tied to pre-existing structural constraints, including insufficient staffing, limited infrastructure, a shortage of space for the new equipment and the overall capacity of the facilities themselves.

Wide Rollout Across Europe

The Commission says the system is already active at roughly 1,500 crossing points across 29 countries, with nearly 110 million entries and exits recorded so far — the equivalent of more than two million crossings per week. Lammert also stressed that the EES applies to third-country nationals, not European Union citizens.

For reference, the Commission has also published information on the system here: European Commission Entry/Exit System.

Years Of Preparation, Yet Uneven Readiness

Brussels said the gradual deployment of the system began only after all member states had confirmed they were ready to launch it. The relevant legislation, the Commission noted, has been in force for around a decade, giving national authorities ample time to prepare.

At the same time, the Commission is increasing its support for member states, while Frontex says it is ready to deploy additional personnel at airports facing elevated pressure. Frontex, the EU’s border and coast guard agency, can be found here: Frontex.

Security Gains Remain The Core Argument

Despite the operational difficulties, the Commission insists the EES delivers a significant security benefit. According to Brussels, the system has already helped identify around 1,000 individuals considered a potential risk, preventing them from entering the European Union.

In the Commission’s view, the debate is not whether digital border control is needed, but whether airports and national authorities have invested enough in the physical and human infrastructure required to support it at scale.

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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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