This post first appeared on Li’s Warpcast and X in two parts.

I’ve been spending a lot of time at the intersection of AI and crypto. At Variant, we believe the coupling of crypto and AI is fundamental to making AI equitable and user-owned.

Sharing some thoughts about what we’re seeing: 

Broadly, projects at the intersection of AI x crypto fall into two categories:

1. Applying crypto to solve AI problems
2. Applying AI to solve crypto problems

Because the market for AI overall is larger today than the world of crypto, most companies are focused on #1. That said, applying AI to crypto (#2) can help expand the pie by making crypto easier to use and interact with.

Applying Crypto to AI

Within the first category, we’re looking at projects across the entire AI stack:

• Data collection (including collecting new, proprietary data that doesn’t exist elsewhere)
• Model training and inference (including data labeling and RLHF)
• Infrastructure marketplaces (including compute and storage)
• AI applications

We see opportunities for crypto to have an impact in all of these categories.

Zooming in on the data collection layer as an example, what we’ve seen is that amassing datasets that don’t currently exist or are hard to access can be a massive unlock for AI companies. Crypto mechanics can help here by incentivizing users to contribute data (as in numerous DEPIN networks).

Among compute marketplaces, we’re also seeing token incentives being used to aggregate the supply side of these networks. We think a differentiating factor in an increasingly competitive landscape will be to offer additional services and models to attract developers.

And in the application layer, we’re seeing projects aiming to create AI agents equipped with wallets to enable them to transact independently. Or AI agents that run on decentralized compute (like Venice).

We’ve made several early investments at that intersection — Worldcoin, Mana, Modulus, Botto, Dawn wallet — and we’re excited to continue supporting the space.

I’m curious to get your thoughts: where do you see crypto having the biggest impact at the intersection with AI?

Applying AI to Crypto

AI’s application to crypto parallels the broader impact we’re already seeing AI and LLMs have on the non-crypto world: creating a new user interface for computing; helping content creators in their creative processes; helping enterprises enhance their operations.

The category of projects applying AI to crypto can be segmented by GTM: consumer, creator, or developer-facing. On the consumer side, projects are building:

• AI interfaces for users (e.g. a natural language interface for wallets to do things onchain)
• AI trading agents and strategies
• Valuation models (e.g. Upshot with NFTs)
• User-owned AI DAOs (e.g. @hollyplus_ voice model, @BottoDAO)
• Onchain AI games (e.g. @ModulusLabs’ Leela)

For creators, there are AI-assisted creation tools (e.g. @titlesxyz for NFTs), as well as AI-generated memecoins.

AI art, in particular, is having a moment in the NFT world.

For developers, projects are applying AI to:

• Smart contract auditing
• Fraud detection and security
• Onchain data analysis
• Community management via chatbots
• DeFi risk scoring
• Sybil detection
• Token distribution

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