Blockchain Can Ensure Authentic Data for AI at Scale

As AI continues to evolve and integrate into various industries, the need for authentic, verifiable information has become crucial. Blockchain technology, particularly within the Polkadot ecosystem, is poised to meet this demand, ensuring AI's data integrity and reliability.

The Importance of Data in AI

Former Gartner executive Peter Sondergaard once described information as the "oil of the 21st century." With AI's growing prominence, data has now become the new gold. The global volume of data created, captured, copied, and consumed is expected to triple within five years, according to Statista. In 2023, more than $1 in every four dollars invested in U.S.-based startups went to AI-related projects, highlighting the significant role of data in AI development.

AI's Challenges and Blockchain's Potential

Despite substantial investments, AI faces challenges, particularly concerning data authenticity and bias. AI's reliance on data makes it susceptible to inaccuracies, leading to biased or erroneous outputs. To be effective at scale, AI must mitigate these issues, manage biases, and avoid intellectual property infringements.

Blockchain's features—immutability, traceability, and transparency—make it an ideal solution for these challenges. However, blockchain technology has struggled with issues like security, scalability, and decentralization, known as the "blockchain trilemma."

Polkadot's Approach

Polkadot, with its sharded multichain network, aims to overcome these limitations by enabling parallel processing of transactions. Sharding, a technique that breaks data into smaller segments, allows Polkadot to handle the exponential growth in data processing required by AI.

Polkadot's ecosystem also includes multiple parachains—individual layer-1 blockchains within the Polkadot network—that enhance its capabilities. Examples include:

Decentralized Knowledge Graph

OriginTrail, a Polkadot parachain, addresses data authenticity concerns by building a decentralized knowledge graph. It organizes critical knowledge assets, making them discoverable and verifiable through decentralization. OriginTrail collaborates with BSI, the UK’s national standards body, and the EU’s Next Generation Internet initiative to ensure transparency and authenticity in various sectors.

Co-Processor for Blockchains

Phala Network provides a decentralized physical infrastructure network (DePIN)-powered coprocessor for Web3 AI. It enables AI to interact with blockchains and helps developers build, ship, and monetize smart contract-centric AI agents. Phala's AI Agent Contract allows developers to create AI agents regulated by decentralized autonomous organizations (DAOs) and build profitable tokenomic models.

AI Network for P2P Collaboration

Bittensor is an open-source protocol that powers a decentralized, blockchain-based, tokenized machine learning network. It incentivizes the peer-to-peer sharing and collaboration of decentralized machine learning models, democratizing AI by making it accessible to more people and not just large corporations or research institutions.

Polkadot's Role in the AI Revolution

With its scalable and forward-looking infrastructure, Polkadot is set to play a vital role in the AI revolution. It offers a robust platform that supports the exponential growth in data processing needs, ensuring AI can operate with reliable and authentic information. As AI continues to shape the future, Polkadot stands at the forefront, unlocking productivity and solving real-world challenges. Go deeper and read more.