open-source AI

At Huawei Connect 2025, Huawei detailed its plan to open-source its AI software stack by year-end, including CANN, the Mind series, and OpenPangu models. This move aims to address developer challenges and foster collaboration. CANN will offer open interfaces for its compiler, while the Mind series development environment commits to full open-source. Huawei also plans to open-source its UB OS Component for flexible OS integration and prioritize compatibility with PyTorch and vLLM. The success hinges on initial release quality, community support, and clear governance.

Apertus, an open-source AI model from Swiss institutions including EPFL, ETH Zurich, and CSCS, challenges proprietary AI by offering full transparency in its design, training data, and development. Available in 8-billion and 70-billion parameter versions, it supports over 1,000 languages, including Swiss German and Romansh, and is released under a permissive license. Developed with a focus on ethical compliance and utilizing only public data, Apertus aims to democratize access to AI and serve as a foundation for research and diverse applications across sectors like healthcare and education.

The U.S. is launching “Project ATOM,” a strategic initiative to regain leadership in open-source AI amid growing competition from China, particularly Alibaba’s Qwen models. This U.S.-based non-profit AI lab will develop freely accessible AI models, supported by over 10,000 GPUs. Backed by industry leaders, the project addresses concerns about the U.S.’s lagging open-source contributions, highlighted by the dominance of Chinese-developed open-source LLMs. Project initiator Lambert emphasizes the need for coordination and funding, warning of potential U.S. decline in global AI influence if the initiative fails.

Nvidia CEO Jensen Huang emphasized the importance of U.S.-China collaboration for safe and rapid AI advancement at a recent event. He lauded China’s open-source approach as beneficial for global scrutiny and security. Huang highlighted the vastness and dynamism of the Chinese AI market, estimating that China hosts around 50% of the world’s AI researchers, making it crucial for American companies. This was Huang’s third visit to China this year, underscoring Nvidia’s commitment to the region.

Google launched the AI Edge Gallery, an app enabling on-device AI on smartphones. Sourced from Hugging Face, it allows users to run AI models offline with features like image-based question answering and text manipulation via a “Prompt Lab.” Performance varies based on device hardware and model size. The app is an experimental Alpha version, open-source under Apache 2.0, and encourages user feedback.

The Linux Foundation and Meta highlight open-source AI’s (OSAI) pivotal role in driving innovation and enterprise adoption, with 94% of surveyed organizations using AI tools—89% leveraging open-source solutions. Cost efficiency fuels adoption: two-thirds of enterprises report lower deployment expenses versus proprietary systems, while omitting OSAI could triple corporate costs. OSAI enables over 50% operational cost reductions and sector-specific gains, including $290B in manufacturing and $260B in healthcare. Meta’s PyTorch exemplifies decentralized innovation, shifting governance to a nonprofit model and spurring external collaboration. The study projects 20% wage premiums for AI-skilled workers, positioning OSAI as critical infrastructure for economic resilience and competitive diversity across industries.