Ian explains how Tonic started by helping developers create safe, realistic data for testing and development, and how that has expanded into AI model training, de-identification, and synthetic datasets for reinforcement learning.
We discuss structured vs. unstructured data, healthcare and financial services use cases, Tonic Fabricate, Tonic Textual, fine-tuning, RL environments, and why enterprises are becoming more interested in training models on their own data.
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