Snorkel GenFlow

Snorkel GenFlow offers programmatic curation, annotation, and management of instruction datasets for generative AI use cases.

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Programmatic curation and annotation for safer, reliable, generative AI

In this new era of generative Foundation Models, it's instruction-tuning that crafts the much-sought-after conversational AI experience. This nuanced process is crucial for fine-tuning a foundation model to match your business's tone and style, regardless of the base model you start with. This makes the quality of the training data your top priority, as it directly impacts the performance and capabilities of your AI models. Ultimately, if you let poor data in, you're up against an inescapable truth - "garbage in, garbage out."

Snorkel GenFlow is here to help teams accelerate generative AI adoption within the enterprise. Through a close partnership centered around achieving your business goals, Snorkel GenFlow offers principled, systematic, and programmatic approaches to model fine-tuning to ensure efficiency, scalability, and repeatability. With GenFlow, we provide a powerful solution that allows you to optimize your instruction-tuning process and achieve exceptional results.

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Mastering GenAI: the importance of high-quality data

The key to the superior performance of generative models like ChatGPT is the quality of the “instruction and response” data they are trained on. However, creating and curating these datasets remains a largely ad hoc, manual, and costly process. These data-centric operations are often relegated to second-tier status in the core AI development process, have lengthy review cycles, and are less than ideal for teams working with private, expertise-intensive data.

Sampling

Obtain the optimal mix of prompts and/or responses for the benchmarks and tasks crucial to your deployment setting.

Filtering

Leverage model-driven approaches to filter for high-quality data, the cornerstone of top-tier AI.

Annotation

Combine programmatic and human-driven resources to create high-quality responses, facilitated by algorithmically-driven routing, review, and modeling techniques.

Making generative AI data operations first-class and programmatic

The data-centric operations “behind the curtain”

Discover errors through guided analysis

At Snorkel, we are on a mission to revolutionize the way data-centric operations in AI are treated. We aim to make these operations first-class and programmatic with our newest offering: Snorkel GenFlow.

In GenFlow, we support not just the annotation of prompt/response pairs, but also the critical steps of sampling, selection, and filtering. The end product is a more iterative, high-quality, and speedy programmatic approach to generating the critical data required for instructing and aligning generative models with techniques like Reinforcement Learning from Human Feedback (RLHF) and more.

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Use Cases

Chat

Enhance chatbot interactions with Snorkel GenFlow by streamlining the creation and management of high-quality instruction datasets.

Q&A

Utilize a combination of programmatic and human-driven resources to curate high-quality Q&A data, effectively improving the model's ability to provide accurate and insightful answers.

Summarization

Efficiently curate and manage datasets for creating AI models that summarize articles, blog posts, books, and documents with precision on your infrastructure.

Stay up to date on the latest research

Pioneering AI research is part of our DNA—that’s why in addition to keeping up with the latest research, we also regularly publish. Here are a few of the recent papers in this area relevant to the data-centric side of building high-performing generative AI models:

Instructeval

Towards Holistic Evaluation of Instruction-Tuned Large Language Model

DataComp

In search of the next generation of multimodal datasets

DoReMi

Optimizing Data Mixtures Speeds Up Language Model Pretraining

Set a new pace for AI

Snorkel AI customers have unlocked the promise of AI for the enterprise. See how they’ve shipped high-quality, adaptable applications—across NLP and more—to production faster with Snorkel Flow.