ED MARQUEZ

Exploring 5 Key Applications of AI Abundance with Blockchain Assurance

Can we trust the output from our AI models? Learn how blockchain solves the 'garbage in, garbage out' problem by ensuring data integrity and model transparency.

Exploring 5 Key Applications of AI Abundance with Blockchain Assurance
#1about 6 minutes

Understanding the synergy of AI and blockchain technology

AI's rapid growth introduces risks like deepfakes and data integrity issues, which blockchain can mitigate by providing an immutable and transparent ledger.

#2about 5 minutes

Ensuring AI training data integrity with a consensus service

Using a decentralized consensus service like Hedera's HCS allows you to create a verifiable, timestamped log of training data to prevent tampering and ensure model reliability.

#3about 4 minutes

Tracking AI model lineage for transparency and accountability

Anchoring model components and development history on a distributed ledger provides a transparent and auditable trail for compliance and debugging.

#4about 6 minutes

Using RAG to query blockchain data with natural language

Retrieval-Augmented Generation (RAG) and function calling enable AI models like Gemini Pro to access and interpret real-time data from distributed ledgers via APIs.

#5about 3 minutes

Managing content ownership and compensation in the AI era

Blockchain offers solutions for AI-related copyright challenges by creating tamper-proof ownership records and automating royalty payments for creators.

#6about 2 minutes

Implementing transparent AI governance with DAOs

Decentralized Autonomous Organizations (DAOs) provide a framework for community-driven, on-chain governance to make AI development more transparent and collective.

#7about 1 minute

Summary and resources for building with AI and blockchain

A recap of the five key applications of blockchain in AI is provided, along with resources and next steps for developers to get started.

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