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Generative AI is revolutionizing virtual try-ons and product visualization in retail. This technology creates ultra-realistic images for fashion, interior design, and product showcases, enhancing the online shopping experience. By generating diverse product visuals, enabling inclusive sizing, and improving “complete the look” features, generative AI helps retailers boost engagement and sales while reducing returns.
Elevate your e-commerce strategy with Conversational AI. Explore technical advancements and practical use cases in our comprehensive whitepaper.
Discover how the power of deep learning algorithms, computer vision techniques, and AI-powered search and recommendations enabled our client to overcome the challenges of navigating a vast product catalog with 3M+ designs.
Discover how brands can leverage Generative AI to transform the way they produce content and visualize products.
The use of question answering (QA) systems is becoming more prevalent in various domains, including customer Q&A and reviews for products such as photo and video cameras. These systems can help users find information more efficiently and provide direct answers to their questions. Building and adapting QA systems to specific domains can be challenging, but techniques such as knowledge distillation and pre-training on unlabeled data can improve the performance of these systems. Additionally, optimizing the models for production, such as using GPUs for inference and applying pruning techniques, can help accelerate the models and make them more suitable for real-time applications.
Grid Dynamics Labs has developed a voice assistant called “Flower Genie” for Amazon Alexa and Google Home platforms, allowing customers to select and order flower bouquets using voice-based interactions. The article discusses the process of building the conversational AI system for ordering flowers and the challenges faced in conversation design, data collection, natural language processing, testing, and certification.
