Resource library

The Databricks Model Registry integration equips Snorkel Flow users to automatically register custom, use case-specific models.

Snorkel CEO Alex Ratner chatted with Stanford Professor Percy Liang about evaluation in machine learning and in AI generally.

Learn how enterprises can harness the power of LLMs to deliver tangible results today and see real-world examples of the latest in LLM fine-tuning, distillation, and data development.

Honeypots are a classic cyber-deceptive technique that allows a defender to add false information into the system in an effort to deter/delay/distract potential attackers. However, the effectiveness of honeypots is dependent on their design along with the environment into which they are deployed. In this work, we consider the scenario where there is a collection of honeypots along with a…

LLMs have claimed the spotlight since the debut of ChatGPT, but BERT models quietly handle most enterprise production NLP tasks.

In its first six months, Snorkel Foundry collaborated on high-value projects with notable companies and produced impressive results.

When done right, advanced classification applications cultivate business value and automation, unlock new business lines, and reduce costs.

A brief guide on how financial institutions could use Google Dialogflow with Snorkel Flow to build better chatbots for retail banking

Zero-shot inference is a powerful paradigm that enables the use of large pretrained models for downstream classification tasks without further training. However, these models are vulnerable to inherited biases that can impact their performance. The traditional solution is fine-tuning, but this undermines the key advantage of pretrained models, which is their ability to be used out-of-the-box. We propose ROBOSHOT, a…