This paper advances empirical demand analysis by integrating multimodal product representations derived from artificial intelligence (AI). Using a detailed dataset of toy cars on \textit{Amazon.com}, we combine text descriptions, images, and tabular covariates to represent each product using transformer-based embedding models. These embeddings capture nuanced attributes, such as quality, branding, and visual characteristics, that traditional methods often struggle to summarize. Moreover, we fine-tune these embeddings for causal inference tasks. We show that the resulting embeddings substantially improve the predictive accuracy of sales ranks and prices and that they lead to more credible causal estimates of price elasticity. Notably, we uncover strong heterogeneity in price elasticity driven by these product-specific features. Our findings illustrate that AI-driven representations can enrich and modernize empirical demand analysis. The insights generated may also prove valuable for applied causal inference more broadly.

The Global 3D Mobile Theatre Market size is forecast to reach $45.6 billion by 2027, growing at a CAGR 7.5% from 2022 to 2027. Increasing penetration of augmented reality and virtual reality for effective 3D content visualization, leveraging digital age technologies such as Artificial Intelligence (AI), Machine Learning (ML) have been impacting the market growth towards 3D mobile theatres. Growing demand for 3D Mobile Theatre as a part of gaining immersive cinematic experience utilizing connected systems such as head-mounted display and headsets are some of the major factors attributing to the market growth. The growing adoption of active matrix organic light emitting diode (AMOLED) in smart gadgets leveraging flexible display technology is enhancing digital reality. Since electroluminescent organic compounds are generally placed on base layers within AMOLED displays, aiding its deployment in 3D mobile theatre applications.

Mobile Robots Market is forecast to reach $54.2 billion by 2026, growing at a CAGR 20.0% from 2021 to 2026. Autonomous Mobile robot is an integration of artificial intelligence with physical robots, and has a locomotive feature, which ensures that they have the capacity to navigate around physically. They are powered by fleet management software and use sensors and other gears to identify and understand their surroundings. Robot technology is experiencing increased acceptance in different commercial and industrial environments. Hospitals, for example, are now using autonomous mobile robots to move supplies and monitor patient health.

The market research report on the Global Deep Learning Market has been formulated through a series of extensive primary and secondary research approaches. The data is further verified and validated by industry experts and professionals. The forecast for 2020-2027 has been covered in the report and offers an extensive historical analysis for the key segments of the Deep Learning market. The well-formulated research report aims to provide the readers with a better understanding of the industry and help them formulate strategic investment plans. The report also evaluates the market dynamics, including drivers, restraints, opportunities, threats, challenges, and other key segments.

With the classified Artificial Intelligence in Supply Chain market research based on various growing regions, this report provides leading players portfolio …

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Global Artificial Intelligence (AI) Market Outlook Market Overview In the era of digitalization and rapidly changing technology, Artificial intelligence technology is one the fastest evolving technology across the globe. Further this technology has vast applications in various sectors like healthcare and manufacturing. Artificial intelligence has potential to lift various industries by reducing the human effort and increasing productivity. The AI technology will transform the functionality of various sectors such as agriculture, Industrial, BFSI, Healthcare among others by providing ease to consumers and the users. Artificial intelligence consists of various technologies such as natural language processing, quarrying, deep learning etc which can be implemented in various applications. AI technologies increase the efficiency of organization and complete tasks efficiently on the back of systematic inputs in the system.