The Future of AI Collaborative Economy: Sahara AI's Vision and Technology

Sahara AI is committed to creating a more open, fair, and collaborative artificial intelligence economic ecosystem. Through blockchain technology, Sahara ensures that data contributors, annotators, model developers, and other participants can receive fair compensation while safeguarding the sovereignty of data and models, as well as the security and tradability of AI assets.

The Current State and Challenges of AI Stacks

The current AI technology stack mainly includes the following aspects:

1. Data Collection and Annotation
2. Model Training and Deployment
3. Creation and Application of AI Agents
4. Provision of Computing Resources

Although there is intense competition at every level, certain methods have proven to be more effective. For example, using large public datasets for initial training and then fine-tuning with specialized datasets; training models on dedicated hardware; providing developers with plug-and-play resources to build AI agents; and utilizing distributed computing resources to accurately reward providers.

However, existing Web2 companies face serious limitations in promoting these directions due to their centralized design. They tend to restrict access and isolate various parts of the technology stack, leading to different security standards, database designs, backend integrations, and profit strategies. This design is difficult to adapt to the shifting AI economic model.

Sahara AI's Solutions

The Sahara platform provides one-stop services for the entire AI lifecycle, covering all aspects from data collection and annotation to model training, deployment, and the creation and application of AI agents, as well as AI asset trading and resource crowdsourcing. By democratizing the AI development process and lowering barriers to entry, Sahara AI offers individuals, businesses, and communities equal opportunities to participate in the construction of an AI future.

All transactions within the platform are immutable and traceable, ensuring the protection of ownership and the recording of asset origins. This supports a transparent and fair profit-sharing model, guaranteeing that developers and data providers receive appropriate compensation.

User Participation Methods

Sahara offers various participation methods for users from different backgrounds:

• Experienced AI developers can use the Sahara SDK and API to interact with blockchain and AI stacks, creating authorized and monetizable AI agents.

• AI development beginners can create and deploy AI assets through no-code/low-code environments, using intuitive interfaces and pre-set templates.

• Ordinary users can earn token rewards by completing AI training tasks, which range from answering basic math questions to describing short videos.

• AI users can use AI agents through a simple user interface, flexibly purchase access rights or further development licenses, and can even trade shares of AI assets.

• Enterprises can create their own AI agents, train them using proprietary data, and benefit from the cost advantages brought by decentralized AI agent generation and services.

Technological Innovation

The Sahara team has incorporated multiple innovations in the system design:

• The Sahara blockchain has optimized gas fees and achieved secure cross-chain data transmission through a cross-chain communication protocol.

• AI-native precompiled smart contracts are used to optimize AI task performance and reduce computational overhead.

• Blockchain protocol management of AI assets, ensuring contribution tracking, reward distribution, and asset registration.

• Data management adopts a combination of on-chain and off-chain methods to optimize data retrieval, security, and availability.

• The collaborative execution protocol supports the development and deployment of joint AI models, while also providing features such as privacy-preserving computation and fraud proof.

Team Background and Partners

Sahara AI is led by USC tenure professor Sean Ren and UC Berkeley alumnus Tyler Z, with team members from renowned institutions and companies such as Stanford University, UC Berkeley, AI2, Stability AI, Microsoft, and Google.

In addition, Sahara has received advisory support from top AI experts from companies and research institutions such as Motherson Group, Nous Research, Together AI, and Midjourney.

Currently, Sahara AI has been adopted by more than 35 leading technology innovation projects and research institutions for various AI services such as data collection/labeling and personalized domain agents.

Conclusion

Generative AI technology and the market are still in the early stages, and integrating the entire AI stack into a single product poses challenges. Sahara AI uniquely addresses this bottleneck through modular design and blockchain technology as a foundation. To achieve an AI future where everyone can participate, Sahara AI is moving towards building an accessible and fair ecosystem.