Labelbox 40M Capital Group 79MWiggersVentureBeat is a San Francisco, California-based startup that provides a training data platform for machine learning applications. It combines a suite of tools to annotate, validate, and analyze data. As a result, enterprises can train AI models with high-quality labeled training data.
The company’s product includes a web service, API, and software that can be customized to fit specific use cases. A few of its customers include Airbus, Lytx, Genius Sports, and Keeptruckin. With this funding, the startup plans to double its workforce to 200 by the end of this year.
Labelbox 40M Capital Group 79MWiggersVentureBeat new round of funding comes from a number of heavy-hitting investors. For instance, Labelbox is backed by Sequoia Capital, B Capital Group, Databricks Ventures, First Round Capital, and Snowpoint Ventures. Other investors include Kleiner Perkins, Andreessen Horowitz, M Capital Group, Gradient Ventures, ARK Invest, and GV (formerly Google Ventures).
Long-Term Vision of the Company
Labelbox 40M Capital Group 79MWiggersVentureBeat is working with SoftBank, which is a major investor in the company. Masayoshi Son, the CEO of SoftBank, has a strong interest in the long-term vision of the company. In addition to his focus on the business, he’s also an observer on the board.
Estimated Valuation of $1 Billion
Labelbox is one of the leaders in the field of artificial intelligence. As of January 2021, the company had an estimated valuation of $1 billion. They also plan to use the capital to increase their workforce and expand their solution offerings.
Labelbox’s technology is built to reduce human effort by 80% and reduce costs associated with data annotation. As a result, the company has a net retention rate of 150%. However, they were tight-lipped about their revenue.
Labelbox is a leading training data platform for enterprise machine learning applications. In this industry, data preparation and also labeling take up over 80% of the time of an AI project. Moreover, the company’s technology is five times more cost-effective than internal efforts. By using Labelbox, businesses can train AI models with high-quality labeled data. Currently, their customers are spread across industries such as insurance, transportation, healthcare, and also financial services.
Most Valuable Asset
Labelbox’s training data is considered the most valuable asset in supervised learning solutions. According to Grand View Research, the global data collection and also labeling market will grow 25% annually through 2028.
What Is Labelbox?
Labelbox is a San Francisco-based software company that provides an enterprise-grade training data platform for machine learning teams. It offers a range of customizable annotation tools, from visual segmentation to image labeling and text annotation. These are available for free or for a fee. Some companies like Bristol Meyer Squibb, Warner Brothers and Bayer use Labelbox.
Labelbox aims to simplify the process of creating and also managing AI/ML training data. Their tools enable teams to collaborate and build better products. They offer various features, including collaboration, customization, quality review and safety monitoring. In addition, it supports different types of datasets, from text, images, geospatial imagery, video, and audio.
Most ML Teams
With more advanced computer vision and also deep learning techniques, the performance of data annotation has improved. However, most ML teams still struggle to measure the efficiency of their pre-labeling process. This is why Labelbox is an invaluable tool for accelerating the labeling process. The team has developed a suite of APIs that allows users to access, manage and also analyze their data.
A number of labels can be added to text strings, paragraphs, conversations and more. The interface is also flexible enough to support NER tagging in documents and also Image Bounding Boxes. The team has built an easy-to-use interface for non-technical users.
Labelbox’s GraphQL API is query-based, with strong tooling and specificity. Data can be exported in JSON format. The GraphQL API has a hierarchical architecture and strongly typed schema. Users can access a variety of ontologies, including the MIT open source ontology, as well as custom ones.
Labelbox’s Workforce Management System
Labelbox’s workforce management system is an important part of the platform. It includes a quality review step, which enables users to test and improve their training data. There is also a benchmark step that enables users to measure the productivity of their labeling workflows.
The platform can be used by any type of organization, including large companies and also organizations with diverse teams. Labelbox has a free version for small teams, which gives users access to its core tools and functions. For more complex use cases, there is a paid version.
Hundreds of teams are using Labelbox to create high-quality training data. It is a valuable resource for any organization looking to improve the quality of its data. For small to large organizations, the labeling process is simplified. Through the platform’s collaborative capabilities, users can build faster, more accurate models.
Labelbox can be useful in a variety of applications, from debugging segmentation models to improving customer personalization. The platform also provides a variety of analytics and error detection.