The Challenge seeks to fund projects that develop, fine-tune, or adapt domain-specific AI models to unlock breakthroughs in their respective fields and catalyze significant downstream applications within the next three years. Priority will be given to Respondents developing models targeting complex societal challenges or innovations in one of Massachusetts' priority industry sectors including healthcare, life sciences, financial services, robotics, advanced manufacturing, climate tech, or education. This funding opportunity is designed to support Respondents at various stages across the lifecycle of AI model development, from data acquisition to deployment. Depending on the nature of proposed projects, awardees may be expected to carry out the following activities: 1. Data Collection and Preparation: Collect or generate datasets for model training, ensuring data quality through cleaning, preprocessing, and appropriate structuring. Collaborate with data partners to overcome challenges of data fragmentation and privacy. 2. Training & Fine-Tuning: Train novel foundation models or fine-tune existing open-source models to address specific use-cases. Select appropriate models, train them with domain-specific data, and iteratively optimize performance. Emphasis should be placed on cost-effective model development to achieve robust performance.
