Snorkel Tackles AI's Most Tedious Task - The New Stack

For all the advances in the development of artificial intelligence algorithms and models, the majority of potential applications never make it to production because of the time and expense of labeling data to train the model. That's a problem Snorkel.ai has set out to automate. "The not-so-hidden secret about AI today is that despite all the technological and tooling enhancements, but 80 to 90%, of the cost, for many use cases, just goes into manually collecting and labeling and curating this data, this training data that the model learns from," said company co-founder and CEO Alex Ratner. Ratner concedes that this is not the first field or even the first decade in which appropriately labeled data has been considered paramount. In a contributed post to TNS last year, Vikram Bahl outlined the challenges of preparing data for machine learning and AI.