Exclusive: Synthefy raises $6.5M for its number-crunching models trained on numerical data instead of words

SiliconANGLE · 1 week ago · 38

Synthefy raised $6.5 million in seed funding to develop foundation models trained on numerical data rather than text, aiming to do for numbers what large language models did for words. The company's open-source model Nori, with 30 million parameters, outperforms Google's 1.6-billion parameter TabFM model on numerical tasks. Enterprises can now tackle fraud detection, dynamic pricing, and forecasting problems in minutes rather than weeks by using pre-trained models that don't require custom training for each new dataset.