Practical AI Solutions for Scientific Discovery
Leveraging Advanced Computational Techniques
Integrating large language models (LLMs) and simulations to enhance hypothesis generation, experimental design, and data analysis.
Addressing Challenges in Physical Sciences
Developing a comprehensive and adaptable framework to effectively simulate observational feedback and integrate it with theoretical models.
Innovative Approaches in Scientific Discovery
Utilizing methods such as Chain-of-Thoughts prompting, FunSearch, Eureka, Neural Architecture Search (NAS), symbolic regression, and population-based molecule design to advance scientific inquiry.
Scientific Generative Agent (SGA) Framework
Integrating LLMs and simulations to transcend specific domains and offer a unified method for physical science, demonstrating superior performance in identifying accurate solutions across tasks.
Research Results and Impact
SGA outperformed other methods, achieving significant loss reduction in constitutive law discovery and molecular design. The framework consistently delivered lower loss values across various tasks, highlighting its effectiveness in identifying novel scientific solutions.
Evolve Your Company with AI
Identify Automation Opportunities
Locate key customer interaction points that can benefit from AI.
Define KPIs
Ensure your AI endeavors have measurable impacts on business outcomes.
Select an AI Solution
Choose tools that align with your needs and provide customization.
Implement Gradually
Start with a pilot, gather data, and expand AI usage judiciously.
Spotlight on a Practical AI Solution
Consider the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
