Joe Ferrara, PhD

Staff AI Scientist

About the author

Joe Ferrara is a Staff AI Scientist at Tonic.ai, where he uses the latest developments in artificial intelligence to improve named entity recognition and synthetic data generation in Tonic Textual. He holds a Ph.D. in Mathematics from the University of California, Santa Cruz, and a B.A. in Mathematics from the University of California, Berkeley. Prior to his role at Tonic.ai, Joe served as a Data Scientist at ICW Group, where he gained experience applying traditional data science techniques in the context of the insurance industry. His background in theoretical mathematics research gives him a unique perspective on his work in artificial intelligence and machine learning.

Latest insights from Joe Ferrara, PhD

The challenges of preparing unstructured data for Generative AI

Technical deep dive

How to create de-identified embeddings with Tonic Textual & Pinecone

Technical deep dive

RAG evaluation series: validating the RAG performance of Amazon Titan vs Cohere using Amazon Bedrock

Technical deep dive

Introducing Tonic Validate: a platform for streamlining RAG application development

Product updates

What is retrieval augmented generation? The benefits of implementing RAG in using LLMs

AI model training

Understanding named entity recognition (NER) models

AI model training

Safeguarding data privacy while using LLMs

Data privacy in AI

Build better and faster with high-fidelity synthetic data today.

Unblock data access, turbocharge development, and respect data privacy as a human right.
Accelerate development with high-quality, privacy-respecting synthetic test data from Tonic.ai.Boost development speed and maintain data privacy with Tonic.ai's synthetic data solutions, ensuring secure and efficient test environments.