Flock.io Partners with Alibaba Cloud to Transform AI Development
Flock.io, a groundbreaking decentralized AI training platform, has announced an exciting new partnership with Alibaba Cloud, the digital backbone of Alibaba Group. This collaboration aims to combine federated learning and blockchain technology to reshape the AI development landscape.
Central to this collaboration is the incorporation of Alibaba Cloud's Large Language Model (LLM), Qwen, and its cloud technologies. Flock.io can then create sophisticated AI models for domain-specific and general use, opening up its potential to cater to different industries and applications.
Flock.io is committed to enabling secure, privacy-preserving AI model training without centralizing data. This partnership aligns with that goal, as both companies focus on empowering communities to collaboratively create, train, and own AI models while ensuring privacy and security at all stages of development.
The collaboration will also emphasize joint research initiatives. Flock.io and Alibaba Cloud plan to leverage their combined technical expertise to explore new AI applications and use cases, spanning both centralized and decentralized AI sectors.
A Game-Changer for AI Models
The partnership will see Flock.io utilizing Qwen, an advanced open-source LLM developed by Alibaba Cloud, to push the boundaries of AI development. Qwen is already widely adopted, with over 290,000 enterprises across industries such as automotive, manufacturing, finance, gaming, healthcare, and robotics.
Accessible via Alibaba Cloud’s Model Studio, Qwen offers businesses and developers an easy entry point to access advanced AI capabilities. Its widespread adoption signifies its potential to transform multiple sectors and generate real-world impact.
Decentralized AI and Blockchain in Traditional Sectors
Beyond model construction, this collaboration is a significant milestone for decentralized AI and blockchain technology in traditional AI sectors. According to Sun, this partnership will enable these technologies to achieve product-market fit, marking a key step toward the future of AI development.
