Backed by a $43 million AI project #Sahara AI led by Binance and Polychain, the testnet program has recently opened. Everyone is advised to join in; it must be a significant opportunity. If you missed the first season whitelist, remember to apply for the second season opportunity. There are many chances not to be missed. Next, I will share some observations and thoughts from personally participating in the testnet!
#Sahara AI ( @SaharaLabsAI) is a decentralized artificial intelligence network aimed at providing a democratized platform for the development, deployment, and monetization of AI models, datasets, agents, and other related assets. The platform seeks to break the dominance of large companies in the traditional AI industry, enabling everyone to participate fairly in the creation, usage, and economic distribution of AI, truly realizing an interconnected, secure, and equitable AI world.
As an AI innovation platform in the Web3 era, Sahara AI proposes the concept of 'AI assetization,' offering new co-creation opportunities for developers, data contributors, and ordinary users through data sovereignty protection, transparent transactions, and optimized collaboration models.
Sahara AI adopts a four-layer architecture, creating dedicated underlying facilities for Web3 AI to ensure efficiency, security, and scalability:
1. Application Layer: Provides users with an intuitive interface and functions, supporting the development, deployment, and trading of personalized AI products.
2. Transaction Layer: Records and verifies all asset transactions based on blockchain technology, ensuring data transparency and trustworthiness.
3. Data Layer: Focuses on high-quality data collection and management, ensuring that the training data for AI models meets standards.
4. Execution Layer: Supports the execution of smart contracts and the operation of AI models, providing users with efficient service support.
This multi-layer design meets the diverse needs of the platform and provides developers and users with a seamless experience.
Sahara AI provides full-process support in the AI Web3 scenario, reflecting user-centered innovative design. From data labeling to assetization, every step is designed around user participation and benefits.
• Original data platform: Empowering user participation
In this first season test, Sahara AI launched a data labeling platform, emphasizing 'everyone can participate.' Users are not only labelers but can also deeply engage in building the AI data ecosystem through review, optimization, and other stages. The contribution of high-quality data not only directly affects the training effects of AI models but also brings real benefits to users.
• Decentralized economy: Truly realizing 'collaboration equals benefits'
Sahara AI Market allows users to publish and trade AI assets, including datasets and models. This decentralized mechanism enables users to benefit directly while creating value, breaking the limitations of traditional AI platforms dominated by developers.
• Fair incentives: Points and achievements drive ecosystem development
The platform encourages quality participation through a points system and leaderboard. Points can be exchanged for rewards, and high-quality contributors can unlock additional bonuses, truly realizing a fair incentive mechanism where contribution equals reward.
The Sahara AI testnet can be said to be a great innovative attempt to promote the AI collaborative economy, creating a high level of interest. As of now, more than 1 million have signed up for the testnet. The first season testnet's data labeling platform has attracted over 800,000 registrations, with only 10,000 whitelist users successfully selected. The test content mainly revolves around data labeling tasks, including the following processes:
1. Select a task: Covers fields such as creator economy, gaming, social media, etc., with diverse tasks.
2. Qualification certification: Qualification exams ensure contribution quality; completing the qualification certification allows entry to the next stage.
3. Contribute knowledge: Label and optimize datasets to provide high-quality data for the AI ecosystem.
4. Earn rewards: Incentivizing participants through a points and achievements system.
Honestly, this is the first time I've encountered such a rigorous task flow, which is challenging and ensures a high quality of data while establishing a user-driven data ecosystem foundation. #Sahara AI encourages users to participate in high-difficulty tasks through rigorous task design and a transparent reward mechanism, laying a solid data foundation for future AI model development.
If you missed the whitelist opportunity for the first season, the second season is approaching; remember to join the waitlist: https://hi.saharalabs.ai/get-started
If you are an AI developer, you can also apply for early access to Sahara AI Dev:
https://hi.saharalabs.ai/dev-early-access
How to start the first season testnet:
1. Access the platform: http://app.saharalabs.ai
2. Log in using your whitelisted wallet
3. Complete your profile
4. Start contributing!
Whitelist users will be notified through the email address they provided at that time.
Specific tutorial for the first season testnet:
1. Claim water (once a day). Claim water address: https://faucet.saharaa.info
2. Sign in (mandatory daily task). At the end of the first season, you can obtain an NFT to record your sign-in status.
3. Qualification exam, click 'take exam' to participate in the qualification exam, which has a time limit of 5-10 minutes and requires a certain accuracy rate to advance to the next stage. Only by completing the qualification exam can you be assigned tasks and earn SP points.
4. After completing the qualification exam, allocate data labeling tasks, which is also the main channel for obtaining SP points and a key factor for future airdrops.
Some tips and methods:
1. Ensure the accuracy of the qualification exam: You can screenshot + GPT-4, directly send the screenshot to GPT-4 to help you interpret and provide answers.
2. Task answering phase: You can use GPT-4, remember to have it generate three answers at once.
3. SP Points: SP points are directly related to future Sahara airdrops, the more, the better.
4. EXP Experience Points: This determines your leaderboard ranking; a higher rank allows you to undertake more advanced tasks and earn higher SP points.
5. Cherish your account: If you make too many mistakes, your account may be easily banned, as it will be assumed you are a robot answering questions. Be sure to do it manually and carefully.
6. Time preparation: Due to the difficulty of the tasks, you should reserve 1-1.5 hours daily. Since there is a time limit for answering, stopping midway counts as failure.
Sahara AI's powerful partners:
Currently, more than 35 leading technology innovation companies and research institutions trust and use Sahara AI, including Microsoft, Amazon, MIT, Snap, and Motherson Group. Sahara AI currently has over 200,000 AI trainers globally, over 35 enterprise clients, and over 3 million AI annotations.
A rich array of partners and support from top Web2 companies provide solid guarantees for Sahara AI's long-term development and future implementation.
A powerful team lineup:
Sean Ren is the co-founder and CEO of Sahara. Sean has received honors such as Samsung's Annual AI Researcher, MIT TR 35 Innovator Under 35, and Forbes Asia's 30 Under 30. He is a tenured professor of AI in the Computer Science Department at USC, making significant contributions to AI research and innovation.
Tyler Zhou is the co-founder and COO of Sahara, as well as the investment director at Binance Labs. He graduated from the University of California, Berkeley.
Lara Avedissian is the head of the ecosystem at Sahara and has served as Chief of Staff at Comm and Accelerator Director at Seed Club. She graduated from UCLA and Columbia University.
Luxurious investment lineup:
#Sahara AI has raised a total of $43 million.
Sahara AI has received support from top institutions such as Binance Labs, Pantera Capital, and Polychain Capital, while also attracting strategic investments from Samsung, Matrix Partners, and Thailand's Kasikorn Bank. These partners not only provide financial support for Sahara AI but also further promote the project's development through their ecosystem resources.
As stated in the future vision of the #Sahara AI white paper:
The ultimate goal of Sahara AI is to create an AI future where everyone can participate and benefit through decentralized technology and open collaboration. Whether developers, enterprises, or ordinary users, everyone can realize personal value on this platform and jointly promote the advancement of artificial intelligence technology.
• Fair and transparent AI ecosystem: Ensuring that AI is no longer monopolized by a few large companies, allowing every user to enjoy ownership and benefits from data and models.
• An AI economy where everyone can participate: Lowering the barriers to entry for AI technology, giving more people the chance to earn returns through data contribution, model development, and other collaborative activities.
• A more efficient and intelligent AI world: Optimizing AI model training through user co-construction, bringing safer and more efficient AI applications to society.
I believe that through relentless efforts, a better, more transparent, and fairer AI world is coming.
Summary: #Sahara AI breaks the closed nature of traditional AI platforms, closely linking developers and users, and realizes the concept of 'collaboration equals benefits' through innovative economic models and technical architectures. As the first decentralized AI public chain that allows users to participate and benefit from day one, Sahara AI not only enhances the efficiency of AI model construction but also provides global users with opportunities to participate in and share the dividends of AI development. In the wave of deep integration of Web3 and AI, Sahara AI is expected to become a driver and benchmark for the industry, establishing a new paradigm for the future AI ecosystem. It deserves special attention and long-term focus. Remember to actively participate in the first and second season testnets!
