siderable cost. Over the years, the size and price of these models have skyrocketed, with models like GPT-2 and PaLM serving as prime examples. The increasing complexity and expense associ- ated with these models underline the evolving landscape of AI and its ongoing pursuit of groundbreaking advancements. Large language models are getting bigger and more expensive. GPT-2, released in 2019, considered by many to be the first large language model, had 1.5 billion parameters and cost an estimated $50,000 USD to train. PaLM, one of the flagship large language models launched in 2022, had 540 billion parameters and cost an estimated $8 million USD—PaLM was around 360 times larger than GPT-2 and cost 160 times more. It’s not just PaLM: Across the board, large language and multimodal models are becoming larger and pricier. AI Applications AI operates through algorithms and computational models that mimic human intelligence. AI has a wide range of applications across industries: a. Healthcare: AI can assist in disease diagnosis, personalized treat- ment planning, drug discovery, and medical imaging analysis. b. Finance: AI is used for fraud detection, risk assessment, algo- rithmic trading, and customer service automation. c. Retail: AIenables personalized product recommendations, de- mand forecasting, inventory management, and chatbot-based customer support. d. Transportation: AI is employed in autonomous vehicles, route optimization, traffic management, and predictive maintenance. e. Education: AI can enhance personalized learning experiences, in- telligent tutoring systems, and educational content generation. SPAIN-US CHAMBER MARKET REPORT 55