Product

Real World ML Evaluations: Evaluating Facebook's Search Quality

Real World ML Evaluations: Evaluating Facebook's Search Quality

New Data Labeling Tools for Training Chatbots and Conversational Assistants

New Data Labeling Tools for Training Chatbots and Conversational Assistants

Andrew Mauboussin

Andrew Mauboussin

How to Pick the Best Data Labeling Platform

How to Pick the Best Data Labeling Platform

Is Elon right? We labeled 500 Twitter users to measure the amount of Spam

Is Elon right? We labeled 500 Twitter users to measure the amount of Spam

ML School: Neural Networks

ML School: Neural Networks

Learn about neural networks, a foundational element of machine learning.

Manifold: Using Neural Embeddings to Explore the Shape of Your Data

Manifold: Using Neural Embeddings to Explore the Shape of Your Data

We're excited to share Surge Manifold, a visual tool to help you explore your datasets and understand outliers in your data.

Supercharge your NLP with Surge AI’s NER labeling tool

Supercharge your NLP with Surge AI’s NER labeling tool

We’re excited to release the newest feature in our NLP labeling suite: a self-serve, multi-user tool for labeling named entity recognition...

The AI Bottleneck: High-Quality, Human-Powered Data

The AI Bottleneck: High-Quality, Human-Powered Data

AI has blown past our wildest dreams; in practice, Siri can’t even tell us the weather. The problem? Creating high-quality datasets to train and measure our models is still incredibly difficult. We should be able to gather 20,000 labels for training a Reddit classifier in a single day, but instead, we wait 3 months and get back a training set full of spam.