A Comprehensive Overview of AI-Powered Crypto Use Cases and Protocols
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A Comprehensive Overview of AI-Powered Crypto Use Cases and Protocols
Although AI-powered crypto has seen various explorations, there is still significant room for improvement in both depth and breadth.
Navigating Web3 tides with focused insightsAuthor: Nanzhi, Odaily Planet Daily
At the end of 2022, ChatGPT opened public testing, igniting the boom of LLM-based AI. Since then, the number of AI-related projects has rapidly increased, spanning various categories such as data, AI models, computing power, and applications. Entering 2024, what are the integration points between AI and Crypto applications? Has AI brought about a productivity revolution for Crypto? This article by Odaily Planet Daily reviews and summarizes these converging applications.
AI Auditing
Back during the early days of the LLM craze last year, SlowMist conducted experimental audits using ChatGPT. At that time, general-purpose AIs like ChatGPT demonstrated some ability to detect vulnerabilities in small-scale codebases but were insufficient for handling complex, long-form logic. Recently, several new tools have emerged specifically targeting Web3 code auditing:
AEGIS AI
Designed specifically for Web3 code auditing, AEGIS AI offers two main services: static code auditing and token auditing (which involves calling and auditing open-source token contract code). The audit process is handled by three types of AI agents: Auditor (conducts code review), Reviewer (performs verification and fact-checking), and Judge (assesses overall risk level).
In addition, AEGIS AI provides real-time monitoring (WatchDog) to actively detect live activities and identify suspicious behavior.
ZAN
ZAN is a plug-and-play toolkit and service suite for projects. In addition to static analysis (basic vulnerability scanning) and fuzz testing (using simulated transactions), ZAN also provides AI-powered auditing services leveraging GPT models fine-tuned on large-scale vulnerability databases for enhanced security checks.
AI Trading / Strategies
These projects use AI to assist trading, aiming to provide users with trading signals and improved trading experiences.
AlphaScan AI
AlphaScan AI connects to thousands of Telegram groups. Users can manually set signal filters, after which AlphaScan AI automatically searches across all channels and executes trades. It also supports advanced AI-driven content analysis to deliver key information alerts.
Hera Finance
Hera Finance is an AI-powered multichain DEX aggregator that leverages AI to provide optimal routing for trades. Hera introduced its AI Pathfinder—an adaptive, self-learning AI whose primary goal is to find swap paths that maximize output (i.e., exchange into more tokens whenever possible).
Aimbot AI
Aimbot AI is a unique project: the team developed AI bots specialized in trading meme coins on-chain. Users can purchase the project's token to share in the profits generated by the AI’s trading activities. As of this writing, Aimbot AI has earned 716.14 ETH through on-chain token trading.
AI Search / Q&A
These products leverage AI to aggregate, train on, and generate insights from platforms like X (formerly Twitter), Telegram, and various project updates. Their functionalities are largely similar, typically including trend tracking and answering Web3-related questions. They offer solid summaries of basic concepts, historical events, and trending topics. However, their depth of understanding remains limited—these tools should only be used as references or supplementary materials, not relied upon for independent decision-making.
Due to high product homogeneity, we will not analyze them individually here. Notable existing solutions include Scopechat AI, QnA3, AwesomeQA, Brian, Libertai, and Clab.AI.
AI Assistants
These products enhance existing platform features with AI, lowering the barrier to entry. Scopechat AI mentioned earlier also falls into this category. Other notable examples include:
Nansen AI
Nansen AI features include detecting on-chain data anomalies, smart search, filtering, grouping, and tracking specific wallets. Its AI-powered Smart Search allows users to ask questions in natural language—such as queries about holder counts or transaction volumes—and Nansen AI will search internal and linked sites to retrieve and present answers.
Dune AI
Allows users to ask questions in natural language. Dune AI automatically generates corresponding SQL query code based on user input, calculates the confidence level between the generated query and the user's intent, and supports further manual editing of the query.
Conclusion
Looking back at the AI + Crypto space, most current developments focus on using Crypto to empower AI—such as decentralized computing power and shared data infrastructures. While there have been multiple attempts at using AI to empower Crypto, both the depth and breadth remain far from sufficient. The market is still awaiting a truly disruptive product.
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