Scaling Structural AI Through Data Collaboration Without Comprising Confidentiality
- Addressing the data bottleneck in limiting predictive model performance
- Explaining federating learning frameworks and how they enable companies to retain full data and IP control, while contributing to shared model improvements
- Providing an update on dataset diversity, scale and benchmarking strategies; coupled with future plans for the initiative