SYDNEY, Australia — Appen Ltd., which provides data sets to enterprises and governments for training artificial intelligence, today announced feature updates for its training data system. Developers of robots and autonomous vehicles could benefit from it, said a company representative.
Appen claimed that its AI system is already the most comprehensive one for collecting and labeling images, text, speech, audio, and video. It combines the machine learning-enabled tools Appen acquired with Figure Eight with the Appen Connect self-serve client workspaces.
“AI can’t function and improve without a constant stream of large volumes of high-quality training data, a market that will be worth up to $19 billion — 10% of the overall AI market — by 2025,” said Wilson Pang, chief technology officer of Appen. “To ensure our customers can continue to develop accurate, powerful AI products, and services, we are constantly enhancing our solution with new
features to help them meet their data needs today and into the future.”
The company said customers can oversee its global workforce of more than 1 million multilingual and skilled contractors. Customers can also use a wide range of managed services to ensure delivery of high-quality training data at scale, with the speed and security they require, Appen said.
Appen said its new features focus on text and speech data, enable customers to develop, enhance, and obtain quality training data for their specific AI project or business needs. They include the following updates:
- Machine Learning-Assisted Text Annotation: New text-annotation capabilities locate and classify named-entity mentions in unstructured text into predefined categories to support entity extraction and span labeling use cases. Users can also now use “bring your own model” outputs to accelerate contributor annotations. Machine Learning-Assisted Text Annotation helps natural language processing (NLP) teams scale quality human annotations.
- Machine Learning-Assisted Text Utterance Collection: Conversational AI customers can now use machine learning validators to collect unique and high-quality text utterances in their domains of choice. Text utterance collection jobs allow customers to take advantage of a distributed workforce of fluent annotators to collect text strings based on prompts or scenarios to power conversational agents.
- Enterprise Analytics: Enterprise Analytics provides in-platform reporting on an organization’s usage. For larger enterprises, Enterprise Analytics supports the management of multiple teams across the platform. Organization and team administrators can view in-depth analytics and are then empowered to make data-driven decisions about allocation, resourcing, and ROI.
The platform’s ML-assisted video object tracking also includes dots, lines, and polygons capability. Available for multiple use cases, these feature updates further cement Appen’s unique ability to deliver on the increasing volume, quality, and speed requirements for training data to support the world’s most innovative AI systems.
The Robot Report has launched the Healthcare Robotics Engineering Forum, which will be on Dec. 9-10 in Santa Clara, Calif. The conference and expo focuses on improving the design, development and manufacture of next-generation healthcare robots. Learn more about the Healthcare Robotics Engineering Forum.
Appen said it collects and labels images, text, speech, audio, and video used to build and continuously improve AI systems. With expertise in more than 180 languages, a global crowd of over 1 million skilled contractors, and the industry’s most advanced AI-assisted data annotation platform, Appen said its systems provide the quality, security, and speed required by leaders in technology, automotive, financial services, retail, manufacturing, and governments worldwide. Founded in 1996, Appen has customers and offices around the world.