First Open-Source Labeling & Annotation and Visualization Project at the Linux Foundation AI & DATA
Since the launch of BasicAI’s ‘Xtreme1’ on GitHub, hundreds of AI enthusiasts, students, engineers, and experts in the autonomous driving industry have contributed and rated the repository’s page. Even more, experts have joined the Xtreme1 community. More companies & individual developers are realizing how an open-source culture can drive more benefits than subscription-restricted AI models and data.
Today, BasicAI announced its donation of Xtreme1 to the Linux Foundation (LF), a consortium that provides a neutral, trusted hub for developers and organizations to code, manage, and scale open-technology projects and ecosystems.
Xtreme1 is the world’s first open-source multi-sensory training data platform and the first ML Data Ops Software in the Linux AI & Data Ecosystem.
Linux Foundation Landscape: AI & Data Projects
Linux Foundation hosts a plethora of top-notch projects in modern technology such as deep learning repository, ‘PyTorch,’ incubated by Meta AI; ‘Delta Lake,’ by Databricks (parent company of Spark);’ AresDB,’ by Uber; ‘Milvus,’ by Zilliz; and ‘Doccarray,’ by Jina AI.
About LF AI & DATA Foundation
LF AI & DATA Foundation is a specialized Linux Foundation organization founded under the Linux parent company in March 2018. LF AI & DATA’s mission as described by Ibrahim Haddad, Executive Director of LF AI & DATA Foundation, is to “build and support an open artificial intelligence (AI) and data community, and drive open source innovation in the AI and data domains by enabling collaboration and the creation of new opportunities for all the members of the community” (LF AI & DATA).
Alex S. Liu, CTO at BasicAI, says, “BasicAI is committed to bringing more MLOps features to maintain and grow the community of Xtreme1”.
Alex S.Liu, CTO at BasicAI
Xtreme1 accelerates the modeling process with advanced AI-powered tools, thousands of project-distilled ontologies, and a wide variety of data curation features. Xtreme1’s tools make cultivating datasets faster than ever before by maximizing data labeling and processing