Join the live discussion. Learn how to unlock data-centric AI and make AI development practical in your organization
Working with vast unstructured and unlabeled data is one of the bottlenecks in the machine learning lifecycle. Machine learning models can only get as reliable and accurate as the data being fed to them. With a data-centric approach 1, your data science and MLE teams save valuable time, resources, and effort by focusing on the data itself.At Snorkel AI, we are going all-hands into making data-centric AI the new and better way of rapidly building and deploying AI applications. With state-of-the-art weak supervision and programmatic labeling approaches, Snorkel Flow aims to meet every data need of your organization, multi-class text classification, named entity recognition, and more.We are excited to announce The Future of Data-Centric AI event, set to take place on September 28, 2021, from 9 AM to 3 PM PDT. Join the conversation at a free, one-day virtual event hosted by Snorkel AI. We will bring together some of the best minds in data-centric AI from academia, research, and industry to explore the shift from model-centric practices to a data-centric approach (also referred to as Software 2.0 2) to building and deploying AI applications. Save your seat, and join us to discuss challenges, solutions, and ideas to make AI practical, both now and in the future.Some topics that will be covered are:
- The latest data-centric AI research
- MLOps and data-centric AI
- The future of weak supervision
Confirmed Speakers:
Whether you are just getting started with data-centric AI, are an advanced practitioner, or are just curious about the new way of building AI applications, this event will help you deepen your understanding the approach, and its applications. RSVP today and save your seat.If you’re interested in staying in touch with Snorkel AI, follow us on Twitter, LinkedIn, Facebook, Youtube, or Instagram, and if you’re interested in joining the Snorkel team, we’re hiring! Please apply on our careers page.
1 Core hypothesis on the data-centric approach to building and deploying AI by Alex Ratner
2 The Road to Software 2.0 or Data-Centric AI by Chris Ré
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