Latest posts
- PonderNet: Learning to Ponder by DeepMind
- Machine Learning Whiteboard (MLW) Open-source Series For our new visitors, we started our machine learning whiteboard (MLW) series earlier this year as an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. In which, we emphasize an informal and open environment to everyone interested… ... - Design Principles for Iteratively Building AI Applications
- Enabling iterative development workflows with Snorkel Flow’s Application Studio. Consider this scenario— we’re AI engineers, and we’re building a social media monitoring application to track the sentiment of Fortune 500 company mentions in the news. ... - Snorkel’s Journey to Data-Centric AI, with Chris Ré - The Future of Data-Centric AI Talk Series Background Snorkel co-founder Chris Ré is an associate professor of Computer Science at Stanford University and an award-winning researcher in data-based theory and machine learning. He has co-founded four companies based on his research in machine learning systems. Chris recently presented at the… ...
- Building a Successful AI Startup - ScienceTalks with Saam Motamedi We at Snorkel AI have received many requests from data scientists and machine learning engineers who aspire to be founders, where do they start and how should they get started on their entrepreneurial journey? We genuinely believe that data scientists and machine learning engineers will build… ...
- Forager: Rapid Data Exploration for Rapid Model Development
- Machine Learning Whiteboard (MLW) Open-source Series We started our machine learning whiteboard (MLW) series earlier this year as 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… ... - Recap: The Future of Data-Centric AI Event
- Main takeaways from The Future of Data-Centric AI Event We recently hosted The Future of Data-Centric AI, where academia, research, and industry experts and practitioners came together to discuss the shift from model-centric AI development to data-centric AI and what lies ahead. This post gives you a quick overview of… ... - Building Malleable Machine Learning (ML) Systems - Defining and Building Malleable ML Systems - Machine Learning Whiteboard (MLW) Open-Source Series As you may know, 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… ...
- Web Virtualization — Optimizing Data-Intensive App Performance
- Frontend Development Best Practices for Working With Lots of Data From Snorkel AI Engineering As a frontend engineer, it's often easy to run into limitations when scaling large applications. At Snorkel AI, we often run into times where our users work with data that scales into the gigabytes when using… ...
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