Bankless: A Review of the Hottest AI Opportunities in the Cryptocurrency Space

Original Title: Unpacking 17 Crypto x AI projects innovating in zkML, AI agents, decentralized compute, and more…

Author: Arjun Chand, Bankless

Compiled by: Bai Shui, Jinse Finance

Cryptocurrency and artificial intelligence are two of the most exciting technological breakthroughs of our time.

But when you combine the two, things get even more interesting.

It is now widely agreed that cryptocurrency x artificial intelligence will be one of the hottest topics of this cycle. You can already see this happening—some early investors in AI tokens have seen their bets pay off tremendously.

But let's face it: the cryptocurrency x artificial intelligence scene is still very new.

Today's article outlines what is happening in this emerging industry. We will break down the different areas where cryptocurrency and artificial intelligence intersect and highlight some top projects.

Cryptocurrency x Artificial Intelligence Overview

Traditionally, artificial intelligence has been the playground of large companies. There are several key reasons for this:

• High costs—developing AI technology requires a significant amount of computing power. This is not cheap, and typically only tech giants have the financial resources to purchase the necessary hardware, creating barriers to entry for smaller entities.
• Data monopolies—AI models require vast amounts of data for training. Large companies possess massive user data that they can leverage to create advanced AI models.

Put together, you can see why this gives large companies such a significant competitive advantage.

Think about it: a handful of companies control most of our data, and they are all building their own AI technologies—Google has Gemini, Twitter is collaborating with Grok, and OpenAI has stirred waves with ChatGPT.

So, how do we create a level playing field for the development of AI technology? That’s where cryptocurrency and blockchain come in. Decentralization, transparency, and economic incentives are inherent principles of cryptocurrency and blockchain.

Combine these core ideas with artificial intelligence, and you get a whole new game—a low-barrier AI industry that anyone can participate in, creating a fairer ecosystem for the development and use of AI technology.

These synergies are being applied to different parts of the AI stack. Let’s take a look at some of these emerging areas:

Decentralized Computing

Training AI models is essentially like building a supercomputer. It is a long and repetitive process that requires trial and error and complex mathematics to get the AI model just right. All this computation is very expensive because it requires specific hardware.

Take OpenAI's computing requirements as an example. From 2012 to 2018, their computing needs doubled every few months! This is where GPUs come into play—they are specialized hardware with the processing power needed for AI.

But nowadays, GPUs are not easy to come by. There is a global chip shortage, and a few big companies like Nvidia and AMD are dominating the show, with everyone from gamers to AI developers wanting a piece of the pie. This has made GPUs very expensive and hard to find.

To address the GPU supply shortage, many projects are adopting cryptocurrency principles to coordinate economic incentives between GPU providers and buyers. The idea is to make it easier and cheaper for you to access the computing power you need.

Some leading projects in this category include:

• io.net—io.net has created an open marketplace that includes underutilized GPUs from data centers and cryptocurrency miners, offering them to anyone at a fraction of traditional GPU costs.
• Akash—Akash is a decentralized computing marketplace that allows users to securely and efficiently buy and sell computing resources. Anyone can become a provider on Akash and offer their hardware to other users on the platform to earn income.
• Render—Render has created a marketplace for idle GPU computing that can be used for various types of projects, such as 3D content creation.

Decentralized AI Model Training and Inference

Crypto x AI projects are adopting a more open and collaborative approach to building AI technology. These initiatives leverage the decentralized principles of blockchain for community-driven AI development.

Imagine an open network where anyone can leverage computing power to train AI models. This creates a collective intelligence repository accessible to everyone, paving the way for a wide range of AI applications.

Some leading projects in this category include:

• Bittensor—Bittensor's mission is to make building AI applications easier. They are creating an open peer-to-peer marketplace where anyone can share and utilize machine learning models.
• Gensyn—Gensyn is coordinating "all the world's computing into one network" to build collective intelligence, training AI models at low cost and high scale.

Zero-Knowledge Machine Learning

Since many AI systems (including popular ones like ChatGPT) are closed-source, we cannot inspect their workings and determine how certain outputs are derived. This may not matter for a question that is easy to fact-check, but as capabilities expand and our reliance on these technologies increases, we will need more insight.

Some leading projects in this category include:

• Giza—Giza offers a one-stop service for building, managing, and hosting verifiable machine learning models. Its tech stack can be used to create reliable and trustworthy blockchain AI solutions.
• Modulus Labs—Modulus uses cryptography to verify AI outputs and employs specialized zk provers to ensure their accuracy.

To make the entire process more transparent, some crypto x AI projects are turning to zero-knowledge machine learning (zkML). zkML combines complex cryptographic techniques with AI to ensure the integrity of the machine learning process and the accuracy of its outputs. It allows us to inspect the workings of AI without having to trust anyone, which is the essence of cryptocurrency.

AI Agents

Developers may want to upgrade AI through cryptocurrency, but they are also looking to upgrade cryptocurrency through AI.

AI agents are essentially intelligent bots that can independently perform tasks across DeFi platforms. They process information, make decisions based on data, and take actions to achieve set goals.

AI agents are increasingly being applied in DeFi, serving various use cases such as:

• MEV arbitrage bots—Jaredfromsubway.eth specializes in exploiting market inefficiencies.
• Telegram bots—Unibot and Banana Gun.
• In-game bots—Parallel's Colony, a game where AI-driven virtual characters interact with each other.
• Bots in social applications—Frenrug, an on-chain AI agent that can chat with users in the app and buy and sell their keys.
• Predictive analytics bots—Numerai on Bittensor, Subnet 8 (prediction subnet).
• AI agents in prediction markets—Omen is a prediction market that uses AI to forecast event outcomes.

AI agents represent an important step toward creating autonomous systems that can interact with the DeFi ecosystem to perform various tasks. They are expected to be a unique catalyst in this bull market.

Some leading projects in this category include:

• Autonolas—Autonolas provides a framework for developing crypto-native AI agents capable of autonomously executing complex DeFi strategies.
• Morpheus—Morpheus is an open-source network designed to power peer-to-peer personal AI (known as smart agents) and is incentivized by the native token "MOR."

Conclusion

The intersection of cryptocurrency and artificial intelligence is not just a speculative bubble; it is an emerging field with real significance.

While the hype is undeniable, and some projects seem to be chasing trends, the fundamental promise of combining cryptocurrency with artificial intelligence is clear—to create a fairer ecosystem for the development and use of AI technology.

Can a crypto x AI project break into the top ten of the crypto market cap rankings this cycle?

The potential for collaboration between cryptocurrency and artificial intelligence is immense, and we are at an exciting moment in this story. Over time, we are likely to witness a project in this field rise to challenge giants like OpenAI.