A New Paradigm of AI Collaborative Economy: A Comprehensive Analysis of Sahara AI

Sahara AI aims to create an open, fair, and collaborative artificial intelligence economic ecosystem, allowing more people to easily participate. Through blockchain technology, Sahara ensures that all participants (, including data providers, annotators, and model developers, can receive fair compensation while safeguarding the sovereignty of data and models, as well as the security of AI assets. Additionally, users can freely create, share, and trade related permissions.

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The Current State of AI Stacks

The current AI stack is mainly divided into the following layers:

1. Data collection and annotation: Collect data from various sources and annotate it according to the specific task.

2. Model training and service: Input data into the model, adjust parameters to reduce errors, a process that usually requires a large amount of computing resources.

3. Creation and Deployment of AI Agents: Typically requires the use of specialized tools like TensorFlow, which have high technical requirements.

4. Computing Resources: Model training requires expensive processing power.

Competition is fierce at every level, and relatively effective execution methods have been established. For example, data collection is best done using large public datasets, and then fine-tuned with specialized data; model training should be conducted on dedicated hardware; AI agent development should facilitate the use of plug-and-play resources; and computing resources should be deployed in a distributed manner to accurately reward providers.

Although Web2 companies are working in this direction, they face numerous limitations due to their centralized design. These companies tend to restrict access and isolate different parts of the stack, resulting in a disconnection in security standards, database design, backend integration, and profit strategies, making it difficult to adapt to the transformation of the AI economic model.

Vision of AI Collaborative Economy

The Sahara platform provides one-stop services for the entire AI lifecycle, covering all aspects from data collection and labeling to model training services, as well as the creation and deployment of AI agents, multi-agent communication, AI asset trading, and resource crowdsourcing. By lowering the entry barrier, Sahara AI offers equal opportunities for individuals, enterprises, and communities to shape the future of AI together.

In the Sahara ecosystem, the process of creating, using, and implementing AI assets to achieve user stickiness is recorded on the blockchain, ensuring the immutability and traceability of transactions, protecting ownership and recording the source of assets. This transparent and fair revenue-sharing model ensures that developers and data providers can receive appropriate compensation.

Diversified User Base

Sahara aims to enable users from different backgrounds to easily participate in the AI economy:

1. Experienced AI developers: Can use the Sahara SDK and API to interact with blockchain and AI stack to create authorized and monetizable AI agents.

2. AI Development Beginners: Create and deploy AI assets using no-code/low-code environments with intuitive interfaces and pre-built templates.

3. AI Training Participants: Simply visit the website to complete AI training tasks and receive token rewards.

4. AI Users: Use AI agents through a simple user interface to flexibly purchase access rights or trade AI asset shares.

5. Enterprise users: can create AI agents based on proprietary data, utilizing decentralized systems to reduce costs, and can also purchase high-quality, privacy-protecting datasets generated by Sahara.

Technological Innovation

The Sahara team has developed multiple innovative technologies in the background while simplifying the user experience:

• Sahara Blockchain: Minimizing gas fees, compatible with EVM, achieving secure cross-chain communication.
• AI Native Precompiled Contract ) SAPs (: Optimizing AI task performance and reducing computational overhead.
• Sahara blockchain protocol )SBPs(: Manage AI assets, track contributions, and allocate rewards.
• Data Management: On-chain storage of metadata and proofs, off-chain storage of important datasets and models.
• Collaborative Execution Agreement: Supports joint AI model development and deployment.

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Strong Team Background

Sahara is led by USC professor Sean Ren and UC Berkeley alumnus Tyler Z, with team members from top institutions such as Stanford, Google, and Microsoft. At the same time, they also received advisory support from industry leaders like Motherson Group and Nous Research.

Currently, Sahara AI has been adopted by over 35 leading technology innovation projects and research institutions, including Microsoft, Amazon, and MIT, for services such as data collection/annotation and personalized domain agents.

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Conclusion

Generative AI technology and the market are still in their infancy, with limited coverage of centralized tools. Sahara AI, through modular design and blockchain technology, has become the only company dedicated to building an easily accessible and equitable AI future. This innovative approach is expected to promote the popularization of AI technology and allow more people to participate in the AI economy.