@SaharaLabsAI is positioned as a decentralized platform covering the entire process of AI development, similar to a 'shared market' for AI resources.
- Ordinary users can upload data or participate in data organization (such as labeling images) to receive rewards.
- AI developers can also efficiently train AI models using the data and computing power provided by the platform, reducing development costs.
- Developers in the trading market can list AI tools for sale and receive compensation.
- Enterprises can contribute idle computing power to receive platform incentives.
This model embodies the 'grassroots spirit' of Web3.
The AI industry has long been dominated by giants like Microsoft and Google, with data, computing power, and model resources highly concentrated. $SAHAR allows individual users to share in the dividends of the AI era, lowering the barriers to AI development and providing opportunities for ordinary users.
Let's take a look at the token model of $SAHARA .
It can be used for community governance, allowing holders to participate in future project decisions, and can also be used to pay for data and computing power costs on the platform. Since its launch, the token has performed steadily, with its market value rebounding from 700 million to over 1 billion, currently stabilizing around 750 million. In the face of market selling pressure and short-selling forces, maintaining such resilience shows the strength of community support.
If placed in last year's AI boom, the market value of $SAHARA could perhaps catch up to $WLD, reaching 5 billion or even 10 billion, and its potential cannot be underestimated.
At the same time, it has been launched on top exchanges like Binance and established deep collaborations with over 30 global companies, including Microsoft and Amazon. The ability to gain such endorsement from major players in the Web3 world indicates a high level of recognition from capital. Such cross-border cooperation is rare in the AI + Web3 space.
Of course, the 'decentralized computing power' model of $SAHARA is not without challenges. I am well aware that networking and computing power require professional equipment and maintenance. $SAHARA relies on individual GPUs to provide computing power, similar to a 'computing power version of Airbnb', and its actual implementation must also consider the varying models and stability of individual users' graphics cards.
But on the other hand, the model also has its unique value. Individual GPUs may not meet the SLA (Service Level Agreement) for large AI training, but for small developers or specific scenarios (such as edge computing), this low-cost computing power sharing could be a good option.
Decentralized projects in Web3 have never been achieved overnight. BitTorrent survived for many years by relying on free sharing, and Uber and Didi evolved from individual drivers to organized fleets. If it can optimize the computing power integration mechanism, it may find its own 'cost-efficiency' balance point.
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