This eBook shows how product and R&D teams use NobleAI’s VIP Platform to accelerate chemical and material innovation. You’ll see how structured R&D data becomes predictive Science-Based AI models, how these models guide formulation, design, and test acceleration, and how teams rapidly explore product possibilities that would be too slow or costly to evaluate in the lab. The guide walks through data upload, model building, forward prediction, inverse design, and iterative improvement, giving you a clear picture of what it’s like to run AI-accelerated product development.
Readers will learn:
- How the VIP Platform builds science-informed ML models from your R&D data.
- Why SBAI improves prediction accuracy even with limited datasets.
- How to upload, curate, and manage data for model training.
- How scientists use forward prediction to estimate performance of new formulas.
- How inverse design predicts optimal ingredient combinations for target performance.
- How iterative re-training and active learning accelerate product optimization.
- How VIP visualizations help compare predictions, identify top candidates, and speed experimental decisions.
Frequently Asked Question
This eBook shows how product and R&D teams use NobleAI’s VIP Platform to accelerate chemical and material innovation. You’ll see how structured R&D data becomes predictive Science-Based AI models, how these models guide formulation, design, and test acceleration, and how teams rapidly explore product possibilities that would be too slow or costly to evaluate in the lab. The guide walks through data upload, model building, forward prediction, inverse design, and iterative improvement, giving you a clear picture of what it’s like to run AI-accelerated product development.
Readers will learn:
- How the VIP Platform builds science-informed ML models from your R&D data.
- Why SBAI improves prediction accuracy even with limited datasets.
- How to upload, curate, and manage data for model training.
- How scientists use forward prediction to estimate performance of new formulas.
- How inverse design predicts optimal ingredient combinations for target performance.
- How iterative re-training and active learning accelerate product optimization.
- How VIP visualizations help compare predictions, identify top candidates, and speed experimental decisions.
