Crypto for Advisors: AI + Blockchain + Crypto

In today’s issue, Kelly Ye from Decentral Park Capital takes us through the relationship between AI and blockchain and how this combination will drive these growing technologies' adoption and use cases.

Then, Alec Beckman from Advantage Blockchain answers questions about how AI, blockchain and crypto work together in Ask an Expert.

–S.M.

You’re reading Crypto for Advisors , CoinDesk’s weekly newsletter that unpacks digital assets for financial advisors. Subscribe here to get it every Thursday.

Crypto X AI: Why Blockchain is the Secret Sauce for Mass AI Adoption

Artificial Intelligence (AI) holds transformative potential across industries and daily life, yet its mass adoption faces hurdles—resource intensity, ethical concerns, lack of customization, and challenges surrounding proof of humanhood. With its decentralization and resource coordination strengths, Blockchain provides a compelling solution to these challenges, paving the way for widespread AI integration.

The Challenges of AI Adoption

Resource Intensity: Developing advanced AI demands immense computational power, data, and expertise, favoring well-capitalized firms and sidelining smaller players.

Ethical Concerns: Centralized AI monetization often mirrors Web2’s exploitative model: “If you don’t pay for the product, you are the product.” This raises concerns about user privacy and data exploitation.

Lack of Customization: AI must address diverse, nuanced human needs. Standardized models frequently fail to provide tailored solutions, underscoring the necessity for adaptable, task-specific AI agents.

Proof of humanhood: As AI evolves, distinguishing human-generated content from machine output becomes increasingly difficult, leading to risks of misinformation and content piracy.

Blockchain: A Game-Changer for AI

Blockchains offer a compelling counterpoint to centralized AI development. Their open, permissionless nature and token-based incentives enable large-scale resource coordination, addressing AI’s most pressing challenges:

Decentralized Infrastructure: Projects like Render and Akash leverage token rewards to crowdsource global GPU power, offering competitive alternatives to centralized providers like Amazon Web Services (AWS). While reliability challenges persist, applications like Render’s image-rendering successes showcase blockchain's viability.

Open-Source Model Development: Platforms like Bittensor and AI Alliance incentivize AI model development using their platform tokens. By fostering innovation and reducing reliance on centralized funding, these platforms empower independent developers. Successful models can increase token value, creating a virtuous growth cycle.

OK