Accelerating domain-specific AI model training with private data
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Publicly available data has fueled AI’s early successes, but the next big leap lies in domain-specific models trained on sensitive, private data. Highly regulated industries like healthcare are unlocking unprecedented accuracy and innovation using specialized datasets while maintaining compliance and privacy.
Join Brad Genereaux, Global Healthcare Lead at NVIDIA, and Adam Kamor, Co-Founder & Head of Engineering of Tonic.ai, for a panel-style webinar exploring private data's transformative potential in AI development.
Using healthcare as an example, we’ll dive into the next generation of AI innovations that redefine what’s possible with sensitive data across industries. Our discussion will include:
- Trends in AI model training in 2025—why domain-specific models are taking over.
- Navigating challenges with sensitive data, from PII to PHI and healthcare-specific datasets.
- Leveraging enterprise data to train SLMs, with practical insights for developing and training advanced, specialized models.
- Real-world use cases—learn how NVIDIA and Tonic.ai address critical challenges in training models on private, sensitive enterprise data.
- Interactive Q&A, to get your most pressing questions answered live.
Learn how to develop AI solutions that integrate industry expertise and an organization’s unique operational knowledge—while maintaining strict data protection—from the industry’s leading voices in data synthesis and secure AI development.
Don’t miss this opportunity to learn how NVIDIA and Tonic.ai enable organizations to securely tap into the new frontier of domain-specific AI without compromising compliance or patient trust.
See you there!