Blockchain can become a powerful force as a foundation for decentralized AI systems, transparent and fair, allowing everyone to have access not only to the technology, but also to the rewards it brings.
Blockchain has enormous potential to democratize access to AI by addressing the centralization concerns raised by the growing dominance of companies like OpenAI, Google and Anthropic.
Decentralized AI systems built on blockchains can help democratize access to essential AI resources such as computing power, data, and large language models. They are also desperately needed; As AI models become more powerful, their appetite for data and computing power grows, increasing the barrier to entry into the industry.
Blockchain allows AI resources to be distributed across open, decentralized networks that anyone can access; creating a level playing field for smaller operators and promoting a spirit of openness and collaboration that is essential to moving the sector forward. Blockchain can create a more equitable system that ensures that those who create the data used to train LLMs are fairly rewarded for their contributions.
Challenges in decentralized data
There’s a lot to like about the prospect of a decentralized AI ecosystem, but the reality won’t emerge until some of the key data access, management, and analytics challenges in blockchain are overcome.
For AI, blockchain can become a crucial tool for secure, transparent and verifiable data management, a tool that is accessible to everyone. But blockchains have some architectural problems: They are essentially a slow, single-table database that records information sequentially—not nearly flexible, nor fast enough for the massive amounts of data AI systems need.
Another challenge is that blockchains cannot be easily integrated with other data environments, nor with other blockchains. This has forced most enterprises using blockchains to deploy a series of point solutions to extract data from the ledger, transform it into a relational format, place it in a traditional database, and move it to a data warehouse for analysis. Meanwhile, bringing external data onto a blockchain requires the use of complex and risky data oracles. All these instruments introduce centralization and security risks.
Innovative solutions pave the way
Fortunately, a number of innovative solutions are being proposed to help facilitate the integration of blockchains and AI. An example of this is Space and Time, creator of a decentralized data warehouse that replaces traditional data stacks and serves as a trusted intermediary between blockchains and enterprise data systems, allowing them to communicate seamlessly.
Space and Time’s secret sauce is its Proof-of-SQL consensus mechanism, which cryptographically verifies the accuracy of SQL database queries and proves that the underlying data set has not been tampered with. This allows smart contracts to interact with external data, paving the way for more advanced blockchain applications that use AI. For example, space and time can allow an AI chatbot like ChatGPT to access blockchain data without any modification.
Previously known for its modular AI blockchain, OG recently rebranded itself as a “decentralized AI operating system” called dAIOS. The system uses blockchain to coordinate decentralized resources for AI, including storage, data availability and computing power, so that AI applications can operate securely and transparently on-chain while ensuring users maintain control over the data being input .
OG’s dAIOS has three main components – storage for managing large data volumes, ‘data availability’ for data verification, and ‘serving’ to enable data retrieval, training and inferencing – that can be used by any developer to access the resources needed their AI models.
SQD aims to solve the challenge of accessing blockchain data and is the creator of an advanced data indexing tool that works by aggregating on-chain data into parquet files and distributing them across nodes in a decentralized data lake. SQD addresses the architectural inefficiencies of blockchain, namely the way data is stored sequentially in blocks, an architecture that makes querying inefficient.
When an app needs to access blockchain data, it sends a query to the nodes hosting the desired data. Each node maps to a specific segment of blockchain data, and SQD provides a detailed index of that information so dApps can quickly find what they need. It typically allocates the same blockchain data to multiple nodes to ensure availability, using an algorithm to manage query volumes.
What will AI do for blockchain?
Modern blockchain data infrastructures are paving the way for a number of new AI/blockchain applications. One of the most promising is in the area of safety. AI can improve blockchain security by monitoring transactions and network activity to detect anomalies in real-time and limit suspicious activity.
AI can also enhance the capabilities of smart contracts and make them much more intelligent. By using analytics, AI algorithms can predict any issues when the contract terms are executed. AI-powered natural language processing algorithms can enable smart contracts to understand legal contracts. And generative AI technology can be used to automate the creation of smart contracts, eliminating the need to learn a specialized programming language like Solidity.
The realm of tokenized real-world assets will also benefit from an infusion of AI, used to analyze the provenance and condition of RWAs such as stocks and fine art. By correlating the analysis with market trends, AI can more accurately calculate the fair market value of tokens. AI can also be used to monitor real-time data costs to continuously update its values. Moreover, it can be used to automate the process of converting RWAs into digital tokens.
Finally, AI can be used to predict future price movements of digital assets by monitoring market trends and industry news. Traders will be able to use the analysis to improve their decision making, hedge their investment portfolios and try to take advantage of market volatility.
AI for everyone
The AI industry is growing at an unprecedented pace and the need for decentralization is becoming increasingly important to ensure the industry remains open and competitive. Blockchain will lay the foundation for advanced, decentralized AI models, leading to the creation of AI tools that meet the needs of the majority, focusing on simplicity, privacy and ease of use.
“Space and Time is excited to lead Web3 into a new era of data-driven smart contracts and the next generation of DeFi,” said Jay White PhD, co-founder and head of research at SxT, and the inventor of the Proof of SQL protocol.
As the convergence of AI and blockchain increases, the two technologies will democratize access to AI resources, reward data contributors fairly, and enable every company to use its proprietary data securely. It’s no wonder that industry experts like Miguel Palencia, co-founder of Qtum, express nothing but confidence in their potential.
“Giving everyone true ownership and provenance of AI assets is paramount,” Palencia told Forbes. “There is an urgent need to address the concentration of AI power in the hands of a few companies.”
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