Flock.io Initiates ‘Elite Trainer Program’ To Attract Top AI Talent For Decentralized AI Training
In Brief
Flock.io has introduced the Elite Trainer Program, inviting machine learning professionals to shape the future of decentralized AI while earning rewards.
Decentralized AI training platform, FLock.io has introduced the Elite Trainer Program, an initiative to recruit top-tier machine learning (ML) professionals as training nodes within its decentralized AI Training Arena.
The program seeks applications from inviting ML engineers, AI developers, and data scientists to participate as trainers, contributing to federated model training on-chain and advancing AI innovation. Participants will receive an exclusive Elite Trainer Wallet, enabling them to train AI models with 200,000 FLOCK tokens provided by the FLock Foundation. Trainers will also receive 50% of the rewards generated from completed training tasks and early access to new features.
The program is particularly interested in applicants who have previously participated in competitions and can showcase achievements such as Kaggle or Numerai Grandmasters, Masters, or other AI challenge/competition winners. Additionally, applicants should provide evidence of their technical expertise, such as high-impact contributions to GitHub AI/ML projects, top rankings on platforms like LeetCode or HackerRank, or academic experience, including publications at leading conferences and journals like NeurIPS, ICML, CVPR, and TAI. While prior Web3 experience is not required, applicants should be familiar with decentralized AI concepts.
Initially, applicants can apply by submitting their email, GitHub, and Kaggle profiles. The FLock team will review these applications and select top-tier ML engineers for the first cohort. If selected, participants will gain exclusive access to AI model training tasks, where they will act as training nodes and receive rewards based on their contributions.
What Is Flock.io?
It is a decentralized platform that aims to make AI training, fine-tuning, and inference more accessible by integrating federated learning with blockchain technology. This approach ensures that data stays local during the training process, improving privacy and security.
Recently, it has introduced its FLock Web3 Agent Model—a specialized large language model (LLM) created to perform complex tasks through precise function calls and on-chain analytics. This model is designed to enhance the efficiency of AI Agent projects and has already been adopted by companies like io.net, OpenGradient, and HashKey Chain.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
