Why artificial intelligence needs cryptocurrency values

The tech industry’s dreams of an AI revolution have always been a double-edged sword.

Unleashing AI could solve humanity’s greatest challenges, but it could also concentrate power in dangerous ways.

This is where cryptocurrencies and blockchain come into play. The same values ​​that make cryptocurrencies interesting can help improve artificial intelligence. These values ​​can help build a fairer, safer and more open future for artificial intelligence.

Decentralization, permissionless innovation, open source systems, privacy, transparency, user ownership. These are not just fancy words; they can potentially open the black box of artificial intelligence.

Here’s why the AI ​​industry needs the magic of cryptocurrencies 👇

Building an inclusive, open source AI ecosystem

The synergies between AI and cryptocurrencies. Source: The promise and challenges of crypto + AI applications

Some large tech companies currently control the majority of computing power and are building moats around their AI research. This has created an “AI mafia” that stifles innovation and competition faster than you can say “walled garden”.

Decentralization, however, is the ultimate twist.

In the decentralized AI paradigm, there is permissionless access to computing power and AI research. Artificial intelligence becomes a tool for everyone, breaking down the barriers established by the AI ​​mafia and democratizing access to knowledge, tools and resources.

Sharing resources means more people can work on AI’s toughest challenges. The more diverse the builders, the less biased the algorithms will be, and that’s a win for everyone.

However, open source development has always been difficult to monetize. How do you get people to build great things if they can’t make money from it? This often forces companies to adopt closed-source, for-profit solutions.

Decentralized AI with cryptographic incentives‘ solves this problem.

Cryptocurrencies offer new ways to monetize open source AI. Create an open market for AI development by granting access and rewarding contributions with tokens.

For example, in decentralized artificial intelligence networks like Bittensordevelopers earn TAO tokens for their machine learning models when used in different AI applications.

This dynamic allows decentralized AI networks to attract top talent through tokenized incentives, creating a sustainable value chain that does not exist in centralized, closed-source models.

Ensure the privacy of user data

We live in a data-hungry world. Everyone wants your data to know your likes and dislikes and then use it to sell you things.

Artificial intelligence is no different. AI systems need a lot of data to work well. Often large AI companies store entire conversation histories to train their models and improve their services, but this creates a huge privacy problem.

Imagine all your personal information (shopping habits, browsing history, and even health data) being thrown into a big AI bin. You need to trust that the company doesn’t misuse it or sell it. Scary, right?

To truly gain user trust, AI must adopt privacy-preserving techniques. Building trust requires transparency and verifiability zero-knowledge proofs (ZKP) can help with this.

There are also other ways that cryptocurrency AI projects are adopting privacy-preserving techniques. For example, Venice.ai stores conversation history only in the user’s browser and ensures that user requests are encrypted. GPU vendors process these requests, but no server sees the entire conversation history or knows the user’s identity.

We can create AI systems that respect user privacy and data ownership by integrating these cryptographic approaches and values.

How do we train AI models while maintaining privacy but without using user data? Without sufficient data, AI is unable to understand real-world situations well, which leads to “AI hallucinations” in which the AI ​​generates incorrect results.

This is where synthetic data comes in. Synthetic data is artificially generated using algorithms to mimic real data. It has privacy-preserving qualities because it does not expose personal information. All important AI companies use itand is an emerging research area.

Cryptocurrencies can incentivize the creation of synthetic datasets for training AI models by crowdsourcing work. Users can earn tokens by contributing verified data points, solving the problem of insufficient training data.

For example, projects like Synthetic AI build tools to create synthetic data, allowing users to provide synthetic data and earn SAI tokens. Ensuring the quality of these datasets can significantly accelerate efforts to generate data for training AI models, while maintaining the privacy of user data.

Closing thoughts

The future of AI is uncertain, but one thing is certain: it must be built on an open source foundation of trust and transparency.

Cryptocurrencies, with their focus on decentralized ownership, permissionless access, and privacy, offer the missing piece. The tools are there and it’s time to use them and write the next chapter in the history of artificial intelligence.

Can cryptocurrency values ​​improve the artificial intelligence sector? Comment below and let us know your thoughts!

This is the AI ​​x Crypto cycle on Bankless

AI x Crypto is real. The fundamentals are there, as is the speculative degeneration.

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