Data Labeling

Unlock possibilities for your enterprise with LLM distillation. Learn how distilled, task-specific models boost performance and shrink costs.

What is AI data development? AI data development includes any action taken to convert raw information into a format useful to AI.

Snorkel AI has made building production-ready, high-value enterprise AI applications faster and easier than ever. The 2024.R3 update to our Snorkel Flow AI data development platform streamlines data-centric workflows, from easier-than-ever generative AI evaluation to multi-schema annotation.

Discover new NLP features in Snorkel Flow\’s 2024.R3 release, including named entity recognition for PDFs + advanced sequence tagging tools.

“Task Me Anything” empowers data scientists to generate bespoke benchmarks to assess and choose the right multimodal model for their needs.

Introducing Alfred: an open-source tool for combining foundation models with weak supervision for faster development of academic data sets.

High-performing AI systems require more than a well-designed model. They also require properly constructed training and testing data.

We need more labeled data than ever, so we have explored weak supervision for non-categorical applications—with notable results.

AI alignment ensures that AI systems align with human values, ethics, and policies. Here’s a primer on how developers can build safer AI.

The Snorkel Flow label model plays an instrumental role in driving the enterprise value we create. Here’s a peek at how it works.

See a walkthrough of how Snorkel Flow users build applications with production-grade RAG retrieval components.

Snorkel takes a step on the path to enterprise superalignment with new data development workflows for enterprise alignment

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

Unlock advanced LLM customization with Snorkel Flow’s new release! Explore flexible data integrations, secure controls, and multimodal support to fine-tune language models for enterprise use. Discover how to leverage images and diverse data types for AI-driven insights.

Snorkel Flow’s new FM-first workflow for building document intelligence applications will get you from demo to production faster than ever.

We’re excited to announce Snorkel Custom to help enterprises cross the chasm from flashy chatbot demos to real production AI value.

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 will be at Google Cloud Next. The event will feature more than 700 sessions, so we picked five that we think you shouldn’t miss.

Snorkel AI helped a client solve the challenge of social media content filtering quickly and sustainably. Here’s how.

Google and Snorkel AI customized PaLM 2 using domain expertise and data development to improve performance by 38 F1 points in a matter of hours.

We’ve developed new approaches to scale human preferences and align LLM output to enterprise users’ expectations by magnifying SME impact.

QBE Ventures made a strategic investment in Snorkel AI because it provides what Insurers need: scalable and affordable ways to customize AI.

Snorkel CEO Alex Ratner spoke with Douwe Keila, an author of the original paper about retrieval augmented generation (RAG).

New unified prompting UI + RAG features, PDF annotation, Databricks MLflow integration, Snorkel Flow Studio, and datasets load 2x faster!

LLMs have claimed the spotlight since the debut of ChatGPT, but BERT models quietly handle most enterprise production NLP tasks.

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

When done right, advanced classification applications cultivate business value and automation, unlock new business lines, and reduce costs.

A brief guide on how financial institutions could use Google Dialogflow with Snorkel Flow to build better chatbots for retail banking

A proof-of-concept project that combines predictive AI + generative AI to minimize LLM’s risks while keeping their advantages.

Data scientists can fine-tune Llama 2 to adapt it to specific tasks. The Snorkel Flow data development platform makes it easy to do so.