There have been dozens of “crypto and AI” posts and essays published over the past year.
At first (and second) glance, most of the conversations seem to be a bit like “Chainwashing” from a few years ago: shoehorning one popular trend into another.
Are there any legs to the overall theme? After all, we have had “AI” in TradFi for years; is this variation any better than continued human involvement?
Based on my own experiences and interactions with experts, I think there could be at least three genuine areas of overlap:
- Search and model training (e.g., Venice)
- Automated on-chain agent interactions (e.g., trading, market making bots)
- Trusted execution environments (e.g., TEEs used by Oracles and Validators such as Switchboard)
We could argue over the utility of each category, whether or not a blockchain is needed or helpful at all in the lifecycle of the activity.
One counter-argument is that in each of these areas: traditional, centralized infrastructure is more efficient (quicker) at achieving the end-goal for the users. But I think – like past cases involving any blockchain – the merits and demerits of the infrastructure usage is specific to the circumstances. That is to say, claiming a priori that X is better than Y because it is faster or cheaper lacks nuance. There are tradeoffs with centrally owned and operated infrastructure that may push certain uses to decentralized infra.
CoinGecko recently had a poll surrounding the (2) topic, asking participants: which crypto AI agent use case(s) are you most excited about?
- KOL/Influencer
- Executing buy/sell orders optimally
- Market intelligence & recommendations
- Trading automation
- Investing automation
- DeFi automation
- Onchain data analysis
- Auditing smart contracts
- Detecting potential hacks or scams
- DAO governance assistance
- Chat
- Gaming/Metaverse NPCs
We don’t have the space to dive into each of these, but I think one category that merits inclusion in the future combines investing and trading automation with market intelligence: prediction and forecast modeling (e.g., Ocean Protocol).
With that said, I do think there is a bit of unwarranted hype around a number of “trading agents” efforts which seem to rely on getting unsophisticated traders to dogpile into zero sum outcomes. For more on that topic, I think readers will be interested in a newly published report from Delphi Research: The Battle of the AI Agent Frameworks.
How fast will these niche areas grow over the next year? Will there be meaningful ‘normie’ adoption or will it continue to be dominate by a handful of participants sybilling?