Blockchain can become a powerful force as the foundation of decentralized, transparent and fair AI systems – ensuring that everyone can access not only the technology, but also the rewards it offers.
Blockchain has enormous potential to democratize access to AI by addressing concerns about centralization that have emerged with the growing dominance of companies like OpenAI, Google, and Anthropic.
Decentralized AI systems based on blockchains can help democratize access to essential AI resources such as computing power, data and large language models. They are also sorely needed; As AI models become more powerful, their thirst for data and computing power increases, increasing the barrier to entry into the industry.
With blockchain, AI resources can be distributed across open, decentralized networks that anyone can access; leveling the playing field for small operators while fostering a spirit of openness and collaboration essential to moving the industry forward. Blockchain can create a more equitable system ensuring that those who create the data used to train LLMs are fairly rewarded for their contributions.
The challenges of decentralized data
There is a lot to like about the prospect of a decentralized AI ecosystem, but the reality will only emerge if some of the key challenges related to data access, management and analysis in blockchain are overcome.
For AI, blockchain can become an essential tool for secure, transparent and verifiable data management, accessible to everyone. But blockchains have some architectural problems: They are essentially a slow, single-table database that stores information sequentially, which is not flexible or fast enough for huge volumes of data. required by AI systems.
Another challenge is that blockchains do not easily integrate with other data environments or other blockchains. For this reason, most companies using blockchains are forced to deploy a range of point solutions to extract data from the ledger, transform it into a relational format, integrate it into a traditional database, and move it into a warehouse data for analysis. At the same time, to import external data onto any blockchain, it is necessary to use complex and risky data oracles. All of these tools introduce centralization and security risks into the equation.
Innovative solutions lead the way
Fortunately, a number of innovative solutions are being offered to facilitate the integration of blockchains and AI. A good example is Space and Time, creator of a decentralized data warehouse that replaces traditional data stacks and serves as a trustless intermediary between blockchains and enterprise data systems, allowing them to communicate transparently.
Space and Time’s secret sauce is its Proof-of-SQL consensus mechanism, which cryptographically verifies the correctness of SQL database queries and proves that the underlying dataset has not been tampered with. This allows smart contracts to interact with external data, paving the way for more sophisticated blockchain applications using AI. For example, Space and Time can allow an AI chatbot like ChatGPT to access blockchain data without any modification.
Formerly 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 on-chain securely and transparently while ensuring that the Users retain control of the data entered.
OG’s dAIOS has three main components: storage to handle large volumes of data, “data availability” for data verification, and “servicing” to power data retrieval, training and inference. their AI models.
Seeking to solve the blockchain data access challenge, SQD is the creator of an advanced data indexing tool that works by aggregating on-chain data into parquet files and distributing it among nodes in a lake decentralized data. SQD addresses blockchain architectural inefficiencies, namely the way data is stored sequentially in blocks, an architecture that makes queries inefficient.
Every time an application needs to access blockchain data, it sends a request to the nodes hosting the desired data. Each node is assigned to a specific segment of blockchain data and SQD provides a detailed index of this information so dApps can quickly find what they need. It typically assigns 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 aspects is security. AI can improve blockchain security by monitoring transactions and network activity to detect anomalies in real-time and mitigate any suspicious activity.
AI can also enhance the capabilities of smart contracts and make them much smarter. Using analytics, AI algorithms can predict any issues during the execution of contract terms. AI-based 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 real-world tokenized assets is also set to benefit from an injection of AI, used to analyze the provenance and condition of RWA like stocks and artwork. 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 data charges in real time to continuously update their values. Additionally, 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 attempt to capitalize on market volatility.
AI for everyone
The AI sector is growing at an unprecedented pace and the need for decentralization is becoming increasingly important to ensure the sector remains open and competitive. Blockchain will provide the foundation for cutting-edge decentralized AI models, leading to the creation of AI tools that meet the needs of the majority, focused 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 inventor of Proof of SQL. protocol.
As the convergence of AI and blockchain accelerates, both technologies will democratize access to AI resources, fairly reward data contributors, and enable any company to use its proprietary data freely. security. 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 of the utmost importance,” Palencia told Forbes. “There is an urgent need to address the concentration of AI power in the hands of a few companies. »
Want to learn more about AI and Big Data from industry leaders? Discover AI & Big Data Expo taking place in Amsterdam, California and London. This comprehensive event is co-hosted with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week and Cyber Security & Cloud Expo.
Check out other upcoming enterprise technology events and webinars offered by TechForge here.
