icoe
Joined 9 years ago
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219
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Member since
Sep 22
Recent submissions
Comment · 1 year ago
Tonic.ai acquired Fabricate (built by the founder of Mockaroo) to augment its synthetic data platform. Fabicate has an LLM first approach to synthetic data, letting users create realistic, relational data from schemas, SQL, or natural language. Tonic is a synthetic data company focused on supplying data for SDLC workflows and model training.
Comment · 2 years ago
Thanks. When we talk to customers who are getting started with generative AI, we usually hear the two biggest concerns are how to avoid embarrassing data leaks and how to move quickly. We sincerely hope this makes a dent in both for everyone.
Comment · 2 years ago
Fair question, but you have to consider the realistic alternatives. For most of our customers inaction isn't an option. The combination of NER models + synthesis LLMs actually handles these types of cases fairly well. I put your comment into our web app and this was the output:
How do you handle proprietary data being leaked? Sure you can easily detect and redact names and phone numbers and addresses, but without significant context it seems difficult to detect whether "17 spices - mix with 2lbs of white flour ... half teaspoon of salt, 1 tablespoon of thyme [...]" is just a normal public recipe or a trade secret kept closely guarded for 75 years.
Comment · 2 years ago
Not to be glib, but this why we built Tonic Textual (www.tonic.ai/textual). It’s both very challenging and very important to protect data in training workflows. We designed Textual to make it easy to both redact sensitive data and replace it with contextually relevant synthetic data.
Comment · 6 years ago
Tonic AI | www.tonic.ai | Full-Stock/Front End Developers
We're seeking a talented developers capable of building out features from top to bottom for our data synthesis platform. At Tonic, you'll have the opportunity to help build out a product that is core infrastructure for organizations to use, analyze, and build upon their data while exploring new privacy and data techniques such as differential privacy, synthesizing new data, and creating small and effective subsets of production datasets. In addition, as an early member of our engineering team you'll have many opportunities to forge our best practices, technical decisions, and create areas of ownership for yourself.