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Cyprus Cuts Youth Unemployment To 13.8%, But The EU Gap Persists

Cyprus is making headway in tackling youth unemployment, with the share of young people not in work, education, or training (NEETs) dropping to 13.8% in 2023. Yet, the country still trails behind the EU average, highlighting the need for sustained efforts.

A Targeted Push To Get Young People Back On Track

The Employment Counseling Unit Services for NEETs project, launched in January 2024, has already assisted 400 young people, providing 717 counseling sessions. The initiative aims to register at least 1,200 NEETs, offering personalized support such as CV writing, interview coaching, and job placements.

Labour Minister Yiannis Panayiotou underscored the government’s goal of achieving full employment by 2025, calling job creation a top priority.

A Stronger Job Market And Rising Wages

Beyond youth employment, Cyprus sees broader labour market gains. Unemployment has dropped to 5%, employment rates are nearing 80%—the highest in 15 years—and wages are steadily climbing. Key collective agreements, extended until 2027, signal long-term stability.

The Road To Full Employment

The government is doubling down on its commitment to closing the NEET gap, ensuring young people gain the skills and opportunities needed to thrive. While Cyprus is moving in the right direction, bridging the gap with the EU remains a challenge.

The AI Agent Revolution: Can the Industry Handle the Compute Surge?

As AI agents evolve from simple chatbots into complex, autonomous assistants, the tech industry faces a new challenge: Is there enough computing power to support them? With AI agents poised to become integral in various industries, computational demands are rising rapidly.

A recent Barclays report forecasts that the AI industry can support between 1.5 billion and 22 billion AI agents, potentially revolutionizing white-collar work. However, the increase in AI’s capabilities comes at a cost. AI agents, unlike chatbots, generate significantly more tokens—up to 25 times more per query—requiring far greater computing power.

Tokens, the fundamental units of generative AI, represent fragmented parts of language to simplify processing. This increase in token generation is linked to reasoning models, like OpenAI’s o1 and DeepSeek’s R1, which break tasks into smaller, manageable chunks. As AI agents process more complex tasks, the tokens multiply, driving up the demand for AI chips and computational capacity.

Barclays analysts caution that while the current infrastructure can handle a significant volume of agents, the rise of these “super agents” might outpace available resources, requiring additional chips and servers to meet demand. OpenAI’s ChatGPT Pro, for example, generates around 9.4 million tokens annually per subscriber, highlighting just how computationally expensive these reasoning models can be.

In essence, the tech industry is at a critical juncture. While AI agents show immense potential, their expansion could strain the limits of current computing infrastructure. The question is, can the industry keep up with the demand?

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