Luma AI Unveils Ray3 Modify: Redefining Video Transformation

by THEFUTURE.TEAM

December 18, 2025

Innovative AI Model Transforms Video Editing

Luma AI, the a16z-backed leader in AI video and 3D modeling technology, has introduced its latest innovation, Ray3 Modify. This groundbreaking model allows creators to modify existing footage by using character reference images that faithfully preserve the original performance. By specifying start and end frames, users can seamlessly generate transitional footage, elevating the creative process.

Preserving Authentic Performance

Ray3 Modify addresses a critical challenge in visual production: maintaining the integrity of human performance amidst digital transformation. According to Luma AI, the model ensures that key elements—such as motion, timing, eye line, and emotional delivery—are retained, enabling creative studios to incorporate human actors within AI-modified scenarios. This capability is essential for studios aiming to produce consistent and high-quality brand or creative content.

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Expanding Creative Possibilities

Beyond preserving performance, Ray3 Modify empowers creators by facilitating detailed character transformations. Users may provide a reference image to transform an actor’s appearance, retaining crucial details like costumes, likeness, and identity across the shoot. Additionally, by offering start and end frames, directors can meticulously control transitions and character behavior, ensuring smooth continuity between scenes.

Strategic Industry Implications and Funding Momentum

In a statement, Amit Jain, co-founder and CEO of Luma AI, emphasized that the development of generative video models has historically been challenged by issues of control. “Generative video models are incredibly expressive but also hard to control. Today, we are excited to introduce Ray3 Modify that blends the real-world with the expressivity of AI while giving full control to creatives,” Jain explained. The model is now available via the company’s Dream Machine platform.

This release follows significant market developments, including Luma AI’s recent funding surge. A fresh $900 million funding round, led by Saudi Arabia’s Humain and witnessed by investors such as a16z, Amplify Partners, and Matrix Partners, underscores the high stakes in the AI-driven visual content arena. Furthermore, Luma AI’s strategic plans include building a 2GW AI cluster in Saudi Arabia, reinforcing its commitment to expanding technological capabilities and market reach.

Conclusion

With Ray3 Modify, Luma AI is setting a new benchmark in the integration of AI with video production. By offering unprecedented control over digital transformations without compromising on performance authenticity, the new model positions the company at the forefront of an industry undergoing rapid evolution.

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Cyprus Income Distribution 2024: An In-Depth Breakdown of Economic Classes

by THEFUTURE.TEAM

December 24, 2025

New findings from the Cyprus Statistical Service offer a comprehensive analysis of the nation’s income stratification in 2024. The report, titled Population By Income Class, provides critical insights into the proportions of the population that fall within the middle, upper, and lower income brackets, as well as those at risk of poverty.

Income Distribution Overview

The data for 2024 show that 64.6% of the population falls within the middle income class – a modest increase from 63% in 2011. However, it is noteworthy that the range for this class begins at a comparatively low threshold of €15,501. Meanwhile, 27.8% of the population continues to reside in the lower income bracket (a figure largely unchanged from 27.7% in 2011), with nearly 14.6% of these individuals identified as at risk of poverty. The upper income class accounted for 7.6% of the population, a slight decline from 9.1% in 2011.

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Income Brackets And Their Thresholds

According to the report, the median equivalent disposable national income reached €20,666 in 2024. The upper limit of the lower income class was established at €15,500, and the threshold for poverty risk was set at €12,400. The middle income category spans from €15,501 to €41,332, while any household earning over €41,333 is classified in the upper income class. The median equivalents for each group were reported at €12,271 for the lower, €23,517 for the middle, and €51,316 for the upper income classes.

Methodological Insights And Comparative Findings

Employing the methodology recommended by the Organisation for Economic Co-operation and Development (OECD), the report defines the middle income class as households earning between 75% and 200% of the national median income. In contrast, incomes exceeding 200% of the median classify households as upper income, while those earning below 75% fall into the lower income category.

Detailed Findings Across Income Segments

Upper Income Class: Comprising 73,055 individuals (7.6% of the population), this group had a median equivalent disposable income of €51,136. Notably, the share of individuals in this category has contracted since 2011.
Upper Middle Income Segment: This subgroup includes 112,694 people (11.7% of the population) with a median income of €34,961. Combined with the upper income class, they represent 185,749 individuals.
Middle Income Group: Encompassing 30.3% of the population (approximately 294,624 individuals), this segment reports a median disposable income of €24,975.
Lower Middle And Lower Income Classes: The lower middle income category includes 22.2% of the population (211,768 individuals) with a median income of €17,800, while the lower income class accounts for 27.8% (267,557 individuals) with a median income of €12,271.

Payment Behaviors And Economic Implications

The report also examines how income levels influence repayment behavior for primary residence loans or rental payments. Historically, households in the lower income class have experienced the greatest delays. In 2024, 27.0% of those in the lower income bracket were late on payments—a significant improvement from 34.6% in 2011. For the middle income class, late payments were observed in 9.9% of cases, down from 21.4% in 2011. Among the upper income class, only 3% experienced delays, compared to 9.9% previously.

This detailed analysis underscores shifts in income distribution and repayment behavior across Cyprus, reflecting broader economic trends that are critical for policymakers and investors to consider as they navigate the evolving financial landscape.

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