We offer practical AI solutions for scientific discovery by using advanced computational techniques. We integrate large language models (LLMs) and simulations to enhance hypothesis generation, experimental design, and data analysis. This helps to address challenges in physical sciences by developing a comprehensive framework to effectively simulate observational feedback and integrate it with theoretical models. Our innovative approaches in scientific discovery include methods such as Chain-of-Thoughts prompting, FunSearch, Eureka, Neural Architecture Search (NAS), symbolic regression, and population-based molecule design to advance scientific inquiry. We have also developed the Scientific Generative Agent (SGA) Framework, which integrates LLMs and simulations to offer a unified method for physical science, demonstrating superior performance in identifying accurate solutions across tasks. Our SGA framework has outperformed other methods, achieving significant loss reduction in constitutive law discovery and molecular design. It consistently delivers lower loss values across various tasks, highlighting its effectiveness in identifying novel scientific solutions. Implementing AI in your company involves identifying automation opportunities, defining measurable impacts on business outcomes, choosing tools that align with your needs, and implementing AI gradually. A practical AI solution to consider is the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. For more information, you can get a free consultation from our AI Lab in Telegram @itinai or follow us on Twitter @itinaicom.
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