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Cyprus Economy: Strong Growth Ahead Despite Structural Challenges

Cyprus is poised to sustain strong economic growth in the coming years, according to a recent report from the Canadian rating agency Morningstar DBRS. The agency also predicts a steady decline in unemployment, which is expected to bolster the nation’s fiscal performance.

Despite these positive projections, the report highlights persistent hurdles facing the Cypriot economy. As a small, service-driven market, Cyprus remains highly susceptible to external shocks. Additionally, while strides have been made to reduce non-performing loans (NPLs), their levels still exceed the Eurozone average. Challenges in labour market productivity further restrict the nation’s economic potential.

On a brighter note, progress in addressing NPLs has been significant. Data from the Central Bank of Cyprus show that NPL ratios in approved credit institutions dropped to 6.8% in August 2024, a dramatic reduction from 43.7% at the end of 2017. This improvement represents an €18.9 billion decrease in absolute terms.

Morningstar DBRS anticipates this downward trajectory to persist but acknowledges that eliminating the remaining NPLs will require time. By mid-2024, credit acquisition companies managed exposures of approximately €21 billion, with 94% classified as non-performing.

The report also notes delays faced by KEDIPES, the state-owned asset management company. Challenges such as foreclosure moratoriums, the COVID-19 pandemic, and geopolitical tensions have pushed the company’s operational deadline to 2030.

Housing prices, meanwhile, have shown sustained growth. As of Q2 2024, property prices in Cyprus rose by an annual rate of 8.0%, with house prices increasing by 6.2% and apartment prices surging by 12.0%. Most of the real estate collateral tied to NPLs consists of residential properties, with Nicosia and Limassol identified as the most stable markets on the island.

While structural vulnerabilities persist, Morningstar DBRS’s analysis underscores Cyprus’ resilience and ability to adapt. Continued efforts to address NPLs, coupled with a robust housing market and improved employment metrics, suggest the nation is on a steady path toward economic stability and growth.

Meta Unveils 816 Billion-Parameter AI Model For Mac, But It Requires 1TB Of RAM

Meta has introduced what it describes as the most capable open-weight AI model available in the United States, making a strategic bet on Apple’s Mac ecosystem. The release reflects the company’s ambition to strengthen its position in open AI while bringing advanced models into professional development and creative workflows.

A Powerful Model With High Hardware Requirements

Called Muse Spark Open, the model has 816 billion parameters and a context window of 1 million tokens. Meta said benchmark results published on Thursday show it outperforming other widely used open-weight systems across key evaluations.

Natively multimodal, Muse Spark Open is designed for complex coding and agentic tasks, extending beyond conventional chatbot use. However, local deployment requires substantial computing power. According to Engadget, the model needs at least 1TB of RAM, with the best performance expected on a Mac Studio equipped with Apple’s M5 Ultra chip. These requirements may limit local use to developers and organisations with access to high-end hardware.

Built For Real-World Development

Meta has paired Muse Spark Open with Muse Code, its AI coding terminal, and tested it across agentic workflows. In one project, the model helped develop a Mastodon client, handling bug fixes, new features and the build process.

The company also deployed the model in DaVinci Resolve, the professional video-editing platform, where it reviewed and cropped footage. These examples demonstrate Meta’s aim to position open-weight AI as a tool for practical production work, from software development to creative tasks, rather than just research demonstrations.

The Strategic Case For Open-Weight AI

Open-weight models give developers and organisations greater flexibility to customise AI, integrate it into internal tools and build specialised workflows. Depending on deployment, they can also reduce costs and provide more control over infrastructure than relying entirely on proprietary services.

However, access to model weights does not eliminate the cost of running advanced AI. Muse Spark Open’s reported memory requirements could make API access a more practical option for many developers than local deployment.

Expanding Access Beyond Mac Hardware

Meta is making Muse Spark Open available through multiple API platforms, allowing developers to use the model without running it on their own machines. This broadens access beyond users with high-end Mac hardware while retaining the option of local deployment for those able to support it.

The release combines Meta’s push to strengthen its position in the open-weight AI ecosystem with a focus on professional users. Wider adoption will depend on the model’s performance, practical usefulness and the resources required to run it.

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