YAPAY ZEKA İÇ MİMARLIĞA NE ÖLÇÜDE KATKI SAĞLAYABİLİR? BETİMSEL DOĞRULUK ÜZERİNE KARŞILAŞTIRMALI BİR ANALİZ

Abstract

Bu çalışma, Claude 3.5 Sonnet, Gemini 1.5 Flash ve ChatGPT 4o olmak üzere üç yapay zeka modelinin, yedi temel tasarım kriterine dayalı olarak iç mekân tasarımı çıktıları üretme performansını değerlendirmektedir. Bu kriterler; tasarım stili, renk, aydınlatma, mobilya ve ürün seçimi, iç mekân malzemeleri, mimari özellikler ve mekânsal yerleşimden oluşmaktadır. Değerlendirme süreci, altı farklı mekân tasarımı üzerinden gerçekleştirilmiş ve 15 katılımcı, yapay zeka tarafından üretilen çıktıları 1 ile 5 arasında puanlamıştır. Sonuçlar, Claude 3.5 Sonnet’in birçok kriterde tutarlı puanlar elde etmesi sayesinde genel performans açısından en başarılı model olduğunu ortaya koymaktadır. Bunu, tasarım stili ve renk alanlarında öne çıkan ancak belirli ölçüde değişkenlik gösteren Gemini 1.5 Flash takip etmektedir. ChatGPT 4o ise mobilya ve aydınlatma kategorilerinde güçlü performans sergilemesine karşın, genel tutarsızlıklar nedeniyle daha düşük bir sıralamada yer almıştır. Modeller rekabetçi bir performans göstermelerine rağmen, özellikle mekânsal yerleşim ve iç mekân malzemeleri gibi alanlar tüm modeller için belirli zorluklar teşkil etmiş ve bu bağlamda gelişime açık noktalar ortaya koymuştur. Bu çalışma, yapay zekâ destekli sistemlerin tasarım süreçlerine katkı potansiyelini vurgularken, karmaşık mekânsal ve malzeme odaklı bağlamlarda mevcut sınırlamaların aşılabilmesi adına daha fazla geliştirme ve kapsam genişletme gerekliliğine dikkat çekmektedir.

Keywords

• Yapay zekâ tarafından üretilmiş iç mekân tasarımı
• İç mekan tasarımı
• Betimleme
• Tasarım teknolojisi

How Well Can AI Contribute to Interior Architecture? A Comparative Analysis of Descriptive Accuracy

Abstract

This study evaluates the performance of three AI models—Claude 3.5 Sonnet, Gemini 1.5 Flash, and ChatGPT 4o—in generating interior design outputs based on seven key design criteria: design style, color, lighting, furniture and product, interior materials, architectural features, and spatial layout. The evaluation was conducted across six different space designs, with 15 participants scoring the AI-generated outputs on a scale of 1 to 5. The results indicate that Claude 3.5 Sonnet achieved the highest overall performance due to its consistent scores across multiple criteria, followed closely by Gemini 1.5 Flash, which excelled in design style and color but exhibited slight variability. ChatGPT 4o, while demonstrating strong performance in furniture and lighting, struggled with inconsistencies, leading to its lower overall ranking. Despite their competitive performance, areas such as spatial layout and interior materials presented challenges for all models, highlighting opportunities for improvement. This study underscores the growing potential of AI in supporting design processes while emphasizing the need for further refinement and expansion to address limitations in complex spatial and material contexts.

Keywords

• AI-generated interior design
• Interior design
• Describe
• Design Technology

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