Comprehensive Analysis of Sahara AI: Building an Open, Fair, and Collaborative Artificial Intelligence Economy

Sahara AI is committed to creating a more open, fair, and collaborative artificial intelligence economy that enables people to participate more easily. By leveraging blockchain technology, Sahara ensures that all contributors (including data providers, annotators, and model developers) receive fair compensation while safeguarding the sovereignty of data and models, ensuring the security of artificial intelligence assets, and allowing for the creation, sharing, and trading of permissions.

1. Current State of AI Stack

The current AI stack can be divided into the following layers:

Data Collection and Annotation Data sources are diverse, including web scraping, public datasets, and user-generated content. To avoid legal issues, data collection must comply with relevant licensing requirements. Data should be annotated according to specific task requirements, such as classification or object recognition.

Model Training and Services Input the processed data into the model, which adjusts its internal parameters (weights) to minimize the error. This process typically requires a significant amount of time and computational resources.

Creation and Deployment of AI Agents Creating user experiences for AI agents typically involves the use of specialized tools and requires a high level of technical expertise.

Computing Resources Model training requires expensive processing power.

There is intense competition and a variety of solutions at every level, but in most cases, some of the most effective execution methods have already been established. For example, data collection is best done using large public datasets (such as books), and fine-tuning should be done with specialized data (such as research papers). Model training is best completed on dedicated hardware, and AI agents should easily utilize plug-and-play resources to build a developer community; compute resources should be deployed in a distributed manner to accurately reward resource providers. The combination of these elements will lead to higher quality AI models and a stronger community.

Traditional Web2 companies are working in this direction, but they face serious limitations due to their centralized design. From the perspectives of business and technology, these companies tend to restrict access and isolate various parts of the stack, resulting in different security standards, database designs, backend integrations, and monetization strategies. This design is actually inefficient and struggles to adapt to the shifts in the artificial intelligence economy.

2. AI Collaborative Economy

The Sahara platform provides a one-stop service for all development needs throughout the entire artificial intelligence lifecycle: from data collection and annotation, to model training and servicing, the creation and deployment of AI agents, multi-agent communication, trading of artificial intelligence assets, and crowdsourcing of artificial intelligence resources. By democratizing the AI development process and lowering the entry barriers of existing systems, Sahara AI offers equal access for individuals, enterprises, and communities to collaboratively build the future of artificial intelligence.

In the Sahara ecosystem, the process of AI assets from creation to use to achieving user stickiness is transparent and traceable. All transactions within the platform are immutable and traceable, ownership is protected, and the source of assets is also recorded. This supports a transparent and fair profit-sharing model, ensuring that both developers and data providers receive appropriate compensation for generating revenue.

Sahara aims to make it easier for people to participate in the artificial intelligence economy. Different types of users can use Sahara in the following ways:

Experienced AI Developers: You can use the Sahara SDK and API to interact with any layer of the Sahara blockchain and its AI stack, such as personalized computing power, data storage, and incentive structures, to create your own Sahara AI agent, which can be authorized and monetized for others to use.

AI Development Beginner: By using a no-code/low-code environment, AI assets can be created and deployed using an intuitive interface and pre-built templates.

AI Training Participants: Users only need to visit the specified website and complete AI training tasks to earn tradable tokens as rewards, with tasks ranging from solving basic math problems to describing short videos.

AI User: Easily use AI agents through an intuitive UI. Users can flexibly purchase access rights and licenses for further development, and can even trade shares of AI assets.

Users can also create their own personalized data "knowledge base" and use their own data to create specialized artificial intelligence. These AIs can allow others to access them while ensuring complete privacy and security of the training data.

Enterprise: Businesses can create AI agents (or "business agents") that are trained using their proprietary data. Because the system operates on the Sahara blockchain, the costs are significantly reduced thanks to the decentralized generation and service of AI agents.

Companies can also pay to generate Sahara data, which combines AI auto-labeling and manual labeling, effectively creating high-quality, privacy-protected multi-model datasets.

Currently, apart from the enterprise-oriented products that have been used by some well-known clients, other features have not yet been released, but there are clear release plans in place.

3. Technical Overview

The Sahara team is dedicated to designing simple and user-friendly systems while abstracting the complexities required to ensure the compatibility, profitability, and security of various parts of the AI stack. Behind the scenes, the team has developed numerous innovative technologies, including:

• Sahara Blockchain: Minimizing gas fees to the maximum extent, fully compatible with EVM, equipped with Sahara Cross-Chain Communication (SCC) protocol to achieve secure, permissionless data transfer across blockchains.
• Sahara AI-Native Precompiles (SAPs): Precompiled smart contracts that optimize AI task performance and reduce computational overhead.
• Sahara Blockchain Protocols (SBPs): Manage AI assets to ensure accountability and traceability, including AI Attribution tracking contributions and distributing rewards, AI Asset Registry manages the registration and provenance of AI assets, licenses, and ownership.
• Data Management: Conducted on-chain and off-chain, with AI asset metadata, commitments, and proofs on-chain, while important datasets, AI models, and supplementary information are off-chain to optimize data retrieval, security, and availability.
• Collaborative Execution Protocols: Support the development and deployment of joint AI models for cross-AI training, aggregation, and services.
• Other innovative technologies: including models such as PEFT that allow for technical fine-tuning, Privacy Preserving Compute that supports differential privacy, homomorphic encryption, and secret sharing, as well as Fraud Proofs, etc.

4. Team Background and Partners

Sahara AI is led by an experienced team, with core members including USC tenured professor Sean Ren and UC Berkeley alumnus Tyler Z. Other team members come from renowned institutions and companies such as Stanford University, UC Berkeley, AI2, Toloka, Stability AI, Microsoft, Google, Chainlink, LinkedIn, and Avalanche.

In addition, Sahara has received advisory support from top AI-native researchers and enterprise clients, including Laksh Vaaman Sehgal, Vice Chairman of Motherson Group, Rohan Taori, Human Research Scientist, Teknium, Co-Founder of Nous Research, Vipul Prakash, CEO of Together AI, and Elvis Zhang, founding member of Midjourney.

Currently, Sahara AI is being used by over 35 leading technology innovation projects and research institutions, including Microsoft, Amazon, MIT, Motherson Group, and Snap, for various AI services such as Sahara Data for data collection/labeling and Sahara Agents for personalized domain agents.

Generative AI is still in its infancy in terms of technology and market size. Due to the difficulty of integrating the entire AI stack into a single product, the current centralized chat and video tools have limited coverage. Sahara AI addresses this bottleneck with its unique modular design, utilizing blockchain as a foundation for permissionless access, token distribution, and security. To realize a future of artificial intelligence that allows everyone to participate, Sahara AI is working to create an accessible and fair ecosystem.