Guides

How to build defect detection models to improve predictive maintenance

In this guide, we’ll walk through an end-to-end tutorial on how your team can leverage Labelbox’s platform to build a powerful task-specific model to improve defect detection on pipes.

How to build damage classification models with aerial imagery to improve claims automation

Learn how your team can leverage Labelbox’s platform to build a task-specific model to improve building damage detection.

What is Model Distillation?

AI models are increasingly getting bigger with the increase in training data and the number of parameters. For instance, the latest Open AI’s GPT-4 model is estimated to have about 1.76 trillion parameters and terabytes of training corpus. Whether training large language models (LLMs) or neural networks, the main goal remains: to train using as much data as possible.  While training from diverse data and increasing the number of parameters produces powerful models, real-world application become

How to Implement Reinforcement Learning from AI Feedback (RLAIF)

The AI revolution is an unstoppable wave, with unique and more capable solutions being rolled out almost every month. These rapid developments, especially around large language models (LLMs), have been made possible by aligning models with human preferences. Reinforcement Learning from AI Feedback (RLAIF) is one of the ways of ensuring such alignments. User feedback has been incorporated into emerging AI models to improve their quality and usefulness. As a result, we have seen more capable model

How to Implement Reinforcement Learning from Human Feedback (RLHF)

The Artificial Intelligence (AI) revolution has been brought to reality with the development of systems and solutions that align with human values and preferences. Reinforcement Learning from Human Feedback (RLHF) is one such example of a system that has transformed model training and improved the accuracy and applicability of AI applications.  Implementing RLHF presents a promising avenue for enhancing AI systems with human guidance. RLHF has been used to develop impressive, human-like convers

How to automatically ingest data from Databricks into Labelbox

Learn how you can leverage Labelbox’s Databricks pipeline creator to automatically ingest data from your Databricks domain into Labelbox for data exploration, curation, labeling, and much more.

How to generate data for model comparison and RLHF

Learn how to generate human preference data for model comparison or RLHF (reinforcement learning with human feedback) with the new LLM human preference editor.

Detecting swimming pools with GPT4 Visual

Explore how Model Foundry enables teams to efficiently compare and select the right foundation model to kickstart LLM development, decreasing costs and accelerating time-to-value.

How to analyze customer reviews and improve customer care with NLP

Learn how to leverage Labelbox's data-centric AI platform to redefine customer care with AI and create solutions tailored to unique customer care challenges.

How to build a content moderation model to detect disinformation

Learn how to leverage Labelbox’s data-centric AI platform to build a model for content moderation for trust & safety applications.