Appen Launches New LLM Features for Enterprises.

Appen Propels Social Network Growth

Published on
August 21, 2017
Author
Share

Appen Propels Social Network Growth

Social Network Search Improvements Fuel Growth and Improve User Experience

The Situation

A leading social network provider needed to improve its social network search engine functionality. The firm was already working with a third-party vendor to source training data, but the vendor was unable to provide quality data on tight deadlines.

The Solution

The social network firm turned to Appen to develop a pilot with 80 raters. Appen quickly provided:

  • Identification and management of strong raters
  • The ability to meet project demands in terms of raters and evaluations needed

The Results

The pilot was successful and the client’s expectations were exceeded. This led to the company transferring additional vendor projects to Appen. The social and search evaluation projects grew from one project with 80 U.S. Appen raters to almost 1,200 raters on 15 projects in 4 markets. The client now has higher quality data and a proven model for entering new markets.

Related posts

Lorem ipsum dolor sit amet, consectetur adipiscing elit.

What is Human-in-the-Loop Machine Learning?

Human-in-the-loop (HITL) is a branch of artificial intelligence that leverages both human and machine intelligence to create machine learning models. In a traditional
Read more

Deciphering AI from Human Generated Text: The Behavioral Approach

One of the most important elements of building a well-functioning AI model is consistent human feedback. When generative AI models are trained by human annotators, they serve
Read more

Data Quality: The Better the Data, the Better the Model

If your data’s not accurate, your model won’t run...properly, that is. While you may end up with a working model, it won’t function the way it was intended. The quality of
Read more

Machine Vision vs. Computer Vision — What’s the Difference?

Artificial Intelligence is an umbrella term that covers several specific technologies. In this post, we will explore machine vision (MV) vs. computer vision (CV). They both
Read more