~/OPEN SOURCE /crowdfunding-and-crowdcomputing-for-open-source-ai-models

Crowdfunding and Crowdcomputing for Open-Source AI Models

A Reddit discussion has proposed using crowdfunding and crowdcomputing platforms to finance the training of large open-source language models like Qwen. The proposal suggests that both individual users and companies could contribute financially to reach milestones for training larger model sizes. Training state-of-the-art AI models requires massive financial resources and computational power, which are currently dominated by tech giants. Crowdfunding could democratize AI development by allowing the community to directly fund and own open-source alternatives. While the idea is appealing, training large models requires coordinated high-bandwidth clusters, making decentralized crowdcomputing technically challenging compared to centralized cloud providers. Additionally, managing trust, fund allocation, and licensing for crowdfunded models presents significant organizational hurdles.

## BACKGROUND

Qwen is a family of large language models developed by Alibaba Cloud, offering open-weight models under licenses like Apache 2.0. Currently, decentralized compute networks like OctaSpace, Targon, and Gonka AI are attempting to optimize GPU power for AI training as alternatives to centralized clouds. However, training large models from scratch still heavily relies on centralized infrastructure due to communication bottlenecks between nodes.

## REFERENCES

## KEYWORDS

#Open Source AI#Crowdfunding#Language Models#Decentralized Compute

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Crowdfunding and Crowdcomputing for Open-Source AI Models | Daily News