Resource library

The human ability to solve complex manipulation tasks is based on a flexible generalizable understanding of intuitive physics mostly learned through curiosity-driven self-play during infancy. We aim to replicate such interactive learning in artificial agents to achieve the same flexibility and generalizability when solving complex manipulation tasks. For that purpose, we introduce a general framework for learning intuitive physics through…

Machine Learning Whiteboard (MLW) Open-source Series Earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine learning.In this episode, our Co-founder and Head of Technology. Braden Hancock…

In this episode of Science Talks, Frederic Sala – an assistant professor of Computer Science at the University of Wisconsin Madison and a research scientist at Snorkel discusses his path into machine learning, the central thesis that ties together his multidisciplinary research, his thoughts on the future of weak supervision, as well as his decision to go into academia.

This paper presents a rigorous approach for using a set of arbitrarily correlated weak supervision sources in order to solve a multiclass classification task when only a very small set of labeled data is available

Impractical ML assumptions are made every day in research, which limit its adoption. In the real world, these assumptions do not hold up. Learn more about how to avoid making these assumptions about AI application development.

In this episode of Science Talks, Explosion AI’s Ines Montani sat down with Snorkel AI’s Braden Hancock to discuss her path into machine learning, key design decisions behind the popular spaCy library for industrial-strength NLP, the importance of bringing together different stakeholders in the ML development process, and more.This episode is part of the #ScienceTalks video series hosted by the Snorkel AI team. You…

This work showcases the Reference-based Weak Supervision (RWS), a fully automatic large-scale data pipeline that harvests high-quality weakly- supervised answer sentences from Web data, only requiring a question-reference pair as input.

This paper introduces a benchmark platform, WRENCH, for thorough and standardized evaluation of WS approaches.

Over the past year, we’ve worked hard to deliver Snorkel Flow, the first AI platform to provide all the power of machine learning without the pains of hand-labeling. Snorkel Flow lets you label data programmatically, train models flexibly, improve performance iteratively, and deploy AI applications quickly. We are incredibly proud of the value that our customers, including two of the…