According to records shared by Kaito AI research partner Sandra, at the artificial intelligence conference held in Singapore, former Coinbase CTO and former general partner of venture capital firm Andreessen Horowitz, Balaji Srinivasan, delivered a thought-provoking speech, explaining the relationship between cryptocurrency and artificial intelligence (AI) and their future potential. He provided a simple and concise framework, revealing how these two multi-billion dollar technologies complement each other to shape the future.
Cryptocurrency and AI are relative in many ways. For example, the rise of AI is top-down, originating from renowned research labs and ultimately promoted by institutions such as OpenAI. On the other hand, the rise of cryptocurrency is bottom-up, initially obscure. Despite this, both are equally important large-scale technologies, but their rise patterns are completely different.
In addition, modern AI is primarily based on statistics, is probabilistic, while cryptocurrency is programmatic and deterministic. Diffusion models and large language models (LLMs) essentially start from probability models, while cryptocurrency demonstrates its determinism through methods such as validating digital signatures.
However, this does not mean that these two technologies are mutually exclusive. Balaji Srinivasan instead believes that the two technologies can complement each other perfectly. For example, AI represents digital abundance, making things easy to forge, while cryptocurrency represents digital scarcity, making forgery difficult. AI generates content, and cryptocurrency certifies content.
By linking digital content (whether articles, images, certificates, or other information) to blockchain transactions, a clear and credible record of content origin, authenticity, and any subsequent interactions can be established. Essentially, while artificial intelligence can “preach” through widespread dissemination of messages, cryptocurrency can verify these messages, ensuring that they are trustworthy and authentic.
Furthermore, AI model training is a very centralized task, as it requires massive computational resources. Cryptocurrency, on the other hand, demonstrates the ability to mobilize large amounts of capital through crowdfunding (aggregating resources in a decentralized manner), with many of the largest crowdfunding activities in the market being cryptocurrency projects. Although current applications are still very inefficient, some breakthroughs are expected in this area.
Finally, Balaji Srinivasan stated:
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