Synthetic Data

Fine-tuning specialized LLMs demands a lot of time and cost We developed Bonito to make this process faster, cheaper, and easier.

The manufacturing industry has experienced a massive influx of data. Snorkel AI and AWS Sage Maker can make that data actionable.

A customer wanted an llm system for complex contract question answering tasks. We helped them build it—beating the baseline by 64 points.

Snorkel AI CEO Alex Ratner explains his view on the importance of AI in data development and illustrates his position with two case studies.

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

The Snorkel AI team will present 18 research papers and talks at the 2023 Neural Information Processing Systems (NeurIPS) conference from December 10-16. The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. Snorkel AI is proud of its roots in the research community and endeavors to remain at the forefront

Distillation techniques allow enterprises to access the full predictive power of large language models at a tiny fraction of their cost.

Sessions at the Future of Data-Centric AI covered LLMs, gen AI, and more. All recordings are now publicly available. See them here!

Recent developments in AI tools have made email surveillance for banks better than ever. See how foundation models and Snorkel Flow can help.

NVIDIA’s Nyla Worker presented “Leveraging Synthetic Data to Train Perception Models Using NVIDIA Omniverse Replicator” in 2022.

Google experts Abhishek Ratna and Robert Crowe discuss practical paths to data-centricity in applied AI at The Future of Data-Centric AI ’22.

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023 free virtual conference.

Jay Alammar, director and engineering fellow at Cohere, presents strategies to enhance the value of Generative AI.

Jan Neumann, Vice President of Machine Learning for Comcast Applied AI and Discovery, describes Comcast’s data-centric AI approach to speech.

30+ sessions by 40+ speakers in 2 action-packed days Last year we organized The Future of Data-Centric AI conference to explore the shift from model-centric to data-centric AI. Speakers included researchers and industry experts such as Andrew Ng (Landing AI), Anima Anandkumar (NVIDIA), Chris Re (Stanford AI Lab), Michael DAndrea (Genentech), Skip McCormick (BNY Mellon), Imen Grida Ben Yahia (Orange)

The future of data-centric AI talk series Background Anima Anandkumar holds dual positions in academia and industry. She is a Bren professor at Caltech and the director of machine learning research at NVIDIA. Anima also has a long list of accomplishments ranging from the Alfred P. Sloan scholarship to the prestigious NSF career award and many more. She recently joined

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 in learning about machine learning. So, if you are interested

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 Future of Data-Centric AI virtual event in September, where he