Original title: "Why AI Needs Crypto's Values"
By Arjun Chand, Bankless
Compiled by: Chris, Techub News
The dream of an AI revolution has always been a double-edged sword.
Unleashing the potential of AI can solve challenges facing humanity, but it can also lead to dangerous concentrations of power.
This is where cryptocurrency and blockchain come in. The core values of cryptocurrency also apply to improving AI. These values can create a fairer, safer, and more open environment for the future of AI.
Decentralization, permissionless innovation, open source systems, privacy, transparency, user ownership are not just empty words, they can help uncover the black box of AI.
Here are the reasons why the AI industry needs cryptocurrency.
Building an inclusive and open source AI ecosystem
The synergy between artificial intelligence and cryptocurrency.
来源：The promise and challenges of crypto + AI applications
Currently, a few large technology companies control the vast majority of computing power and have built high walls in their AI research fields, forming an "AI mafia." This monopoly stifles innovation and competition, limiting the development speed of the entire industry.
However, the advent of decentralization has brought about a change in this status quo. In the decentralized AI model, computing power and AI research are accessible without permission. AI becomes a tool for everyone, breaking down the barriers set up by the AI mafia and democratizing access to knowledge, tools, and resources.
This model of shared resources means that more people can participate in AI research and solve the most challenging problems. The more diverse the participants, the less biased the algorithm will be, resulting in fairer results for everyone. This diverse group of builders not only promotes technological progress, but also brings a win-win situation for society.
However, the open source development model has always been difficult to make money. If you can't make money from it, how can you motivate people to create great works? This dilemma often forces companies to choose a closed source model to achieve profitability.
One solution is "cryptocurrency-powered decentralized AI."
Cryptocurrency technology provides a new approach to open source AI. It creates an open market for AI development, incentivizing it through tokens while ensuring open source access.
For example, in decentralized AI networks such as Bittensor, developers can earn TAO tokens when their machine learning models are used in different AI applications.
This mechanism attracts top talent through tokenized incentives, forming a sustainable value chain that cannot be achieved in a closed-source, centralized model.
Ensure the privacy of user data
We live in a data-driven world where everyone wants to use your data to understand your preferences and market products to you. Artificial intelligence systems require a lot of data to work properly. Large AI companies usually store the entire conversation history to train their models, but this brings huge privacy issues.
Imagine that all your personal information, shopping habits, browsing history, and even health records were stored in a giant AI database. You wouldn't necessarily trust these companies not to misuse or sell this data, right?
To truly earn user trust, AI needs to adopt privacy-preserving technologies. Building trust requires transparency and verifiability, and zero-knowledge proofs can help achieve this.
AI projects in the cryptocurrency space are also using privacy-preserving techniques in other ways. Venice.ai, for example, stores conversation history only in the user’s browser and ensures that user requests are encrypted. GPU providers process these requests, but no server can see the entire conversation history or know the user’s identity.
By integrating these cryptographic methods and values, we can create AI systems that respect user privacy and data ownership.
Training AI models with synthetic data
How do we train AI models while protecting user privacy? Without enough data, AI cannot understand the real world well, leading to "AI hallucinations," where AI generates erroneous outputs.
This is where synthetic data comes in. Synthetic data is generated using algorithms to simulate real data and has privacy-preserving properties because it does not reveal personal information. All major AI companies are using it and it is an emerging research field.
Cryptocurrencies can incentivize the creation of synthetic datasets for training AI models. Users can earn tokens by contributing verified data points, thus solving the problem of insufficient training data.
For example, projects like Synthetic AI build tools for creating synthetic data, allowing users to contribute synthetic data and earn SAI tokens. Ensuring the quality of these datasets can significantly speed up the process of generating data for training AI models while maintaining user data privacy.
Conclusion
The future of AI is uncertain, but one thing is certain: it needs to be built on an open source foundation of trust and transparency.
Cryptocurrencies, with their focus on decentralized ownership, permissionless access, and privacy, fill in the gaps. The tools exist, it’s time to use them to write the next chapter in the evolution of AI.
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