Cryptocurrency AI Track Panorama Guide: An Overview of AI Business Categories and Noteworthy Crypto Projects

Crypto X AI is the main theme running through this year’s crypto market.

As progress in AI continues to break through in the tech world, a large number of projects related to AI concepts are rapidly emerging in the crypto space. While many projects achieve astonishing gains one after another, you may also easily get lost in the vast sea of projects:

With so many AI projects, what exactly are they doing? Which track do they belong to? How should we analyze the value of these projects?

AI is just an abbreviation of two letters, but when combined with blockchain, the scope of business it can cover is far beyond simple letters.

Therefore, understanding the full picture and segmentation of Crypto X AI business helps us quickly identify whether a project has narrative value and the magnitude of its embedded value.

In this issue, we attempt to classify and organize the business formed by combining Crypto and AI, and highlight noteworthy companies and projects within different categories, aiming to help everyone capture value in the AI wave and provide a reference roadmap.

Crypto X AI Basic Logic First, it is essential to clarify that AI is fundamentally a form of productivity. To leverage this productivity, three basic elements are indispensable:

Computing power, algorithms (models), and data.

As for Crypto or blockchain, it is more about a type of production relationship, providing a better environment to promote AI development.

So, how can this environment influence the three AI elements mentioned above? Different answers will lead crypto projects in different directions:

Optimizing computing power: Providing decentralized and efficient computing resources, reducing single point of failure risks, and improving overall computational efficiency.

Optimizing algorithms: Promoting open-source, sharing, and innovation of algorithms or models.

Optimizing data: Decentralized storage, contribution, usage, and secure management of data.

Focusing on these three optimization points, we can roughly divide the entire AI track into the following six directions (since computing power, algorithms, and data influence each other, ✓ in the table indicates the main optimization point, not necessarily only optimizing that one):

The following sections will introduce the business content of each direction, along with representative companies and projects.

Decentralized Computing and AI Inference Platforms Decentralized computing and AI inference platforms refer to distributed computing networks built using blockchain technology. Through these platforms, idle computing resources worldwide can be shared and utilized for training and inference tasks of AI models.

By dispersing computational tasks across multiple nodes in the network, these platforms improve computational efficiency and reduce the risk of single point failures.

Within this framework, computing power becomes the core element being optimized, as decentralized computing platforms directly provide broader and more economical resources.

Typical projects related to this category include:

Ritual

Aims to create an incentive network to power distributed computing devices and serve inference workloads related to machine learning. Users can build and host ML models, deploying them to Ritual’s Infernet nodes.

On November 8, 2023, Ritual completed a $25 million Series A funding round led by Archetype, with participation from Accomplice and Robot Ventures.

Official website: https://ritual.net/

Twitter: https://twitter.com/ritualnet

Akash Network

A peer-to-peer marketplace for cloud computing, providing a secure platform where users can send data to each other and develop.

Integrated with Cosmos, Akash Network benefits from greater interoperability and scalability of the larger network, enabling seamless communication with other blockchain platforms, allowing developers and organizations to access affordable distributed cloud computing resources.

Official website: https://akash.network/

Twitter: https://twitter.com/akashnet_

Render Network

A well-known decentralized GPU rendering solution provider, aiming to connect users who want to perform rendering jobs with those who have idle GPUs to handle rendering. Owners can connect their GPUs to the Render network, receive and complete rendering tasks, and earn RNDR rewards for performing the work.

Official website: https://rendertoken.com/

Twitter: https://twitter.com/rendertoken

Bittensor

An open-source protocol whose token TAO repeatedly hits new highs.

In the Bittensor network, cryptocurrency incentives encourage participants to share their computing resources, data, and AI models, enabling machine learning models and algorithms worldwide to learn from and improve each other.

Recommended reading: “Decoding Bittensor (TAO): An Ambitious AI Lego That Makes Algorithms Composable”

Official website: https://bittensor.com/

Twitter: https://twitter.com/bittensor_

io.net

A decentralized computing network supporting the development, execution, and scaling of ML (machine learning) applications on the Solana blockchain, leveraging the world’s largest GPU cluster to allow ML engineers to access distributed cloud compute at a fraction of the cost of centralized services.

Official website: https://io.net/

Twitter: https://twitter.com/ionet_official

Hyperbolic

Aims to build a compute platform accessible to everyone, where users can share and access computing resources.

Any enhanced Dockerized application can run on Hyperbolic’s fully decentralized compute network. Hyperbolic offers a fully decentralized alternative to traditional cloud services while maintaining competitive prices.

Official website: https://www.hyperbolic.xyz/

Twitter: https://twitter.com/hyperbolic_labs

Gensyn

Gensyn’s philosophy is to connect idle, ML-capable computing devices worldwide—such as consumer GPUs, custom ASICs, and neural network training SoCs—into a global supercluster, greatly increasing available machine learning compute.

On June 11, 2023, Gensyn completed a $43 million Series A funding round led by a16z, with participation from CoinFund, Canonical Crypto, Protocol Labs, Jsquare, Eden Block, and other angel investors.

Official website: https://www.gensyn.ai/

Twitter: https://twitter.com/gensynai

Prime Intellect

Prime Intellect is a decentralized AI platform that commodifies computation and intelligence, offering developers more affordable distributed computing and sustainable open-source model monetization.

Official website: https://www.primeintellect.ai/

Twitter: https://twitter.com/PrimeIntellect

Inference Labs

Inference Labs is a trustless execution layer for AI, focusing on interoperable AI inference on blockchain. The project considers this a crucial step toward enabling anyone to access AI without counterparty risk.

Official website: https://inferencelabs.com/

Twitter: https://twitter.com/inference_labs

Nosana

A decentralized GPU grid designed and optimized specifically for AI inference workloads.

Cost up to 85% less than traditional public clouds, providing a new solution for organizations and individuals seeking massive compute power without high costs. Users can directly access GPU nodes that scale as needed, and consumers, miners, and enterprises can monetize idle hardware by becoming Nosana nodes.

Official website: https://nosana.io/

Twitter: https://twitter.com/nosana_ci

Lilypad

Lilypad is a verifiable, trustless, decentralized compute network aimed at promoting mainstream adoption of Web3 applications. By expanding unrestricted global compute access, Lilypad has strategic partnerships with decentralized infrastructure networks like Filecoin to create a transparent, efficient, and accessible computing ecosystem.

Official website: https://lilypad.tech/

Twitter: https://twitter.com/Lilypad_Tech

Prodia

Prodia is an AI inference API with the vision of making AI accessible to everyone, providing fast and easy-to-use APIs for image generation.

Official website: https://prodia.com/

Twitter: https://twitter.com/prodialabs

Hyperspace

A new type of supercomputer supported by a browser-based blockchain.

Official website: https://www.hyperspace.computer/

Twitter: https://twitter.com/HyperspaceAI

Vanna Labs

Vanna is a blockchain network supporting on-chain AI/ML inference, compatible with EVM. It also supports native and zkML secure inference, computing, protecting, and verifying directly on-chain; designed for seamless integration in dApps, making AI/ML as simple as function calls.

Twitter: https://twitter.com/0xVannaLabs

Official website: https://www.vannalabs.ai/

Arbius

A decentralized open-source network for machine learning. Participants generate new tokens by contributing GPU compute, providing a way for model creators to earn income.

Official website: https://arbius.ai/

Twitter: https://twitter.com/arbius_ai

CUDOS

CUDOS combines cloud and blockchain to support enterprises in AI, Metaverse, HPC, Web3 nodes, and startups, helping unlock new possibilities in the digital realm.

Currently, Cudos has established its own Layer 1, aiming to provide high-performance, trustless, permissionless decentralized cloud computing for all. The Cudos network runs on a delegated proof-of-stake (DPoS) consensus model, where validators verify transactions and provide compute cycles for DApps.

Official website: https://www.cudos.org/

Twitter: https://twitter.com/CUDOS_

Flux

A decentralized cloud computing platform that helps build more flexible, scalable, and censorship-resistant decentralized applications. It also provides compute resources for AI inference and operation.

Any containerized application can run on Flux’s fully decentralized compute network. Flux offers a fully decentralized alternative to other service providers while maintaining competitive prices.

Official website: https://runonflux.io/

Twitter: https://twitter.com/RunOnFlux

AIOZ Network

AIOZ Network is a comprehensive infrastructure solution for Web3 storage, decentralized AI computing, live streaming, and video on demand (VOD).

Official website: https://aioz.network/

Twitter: https://twitter.com/AIOZNetwork

Aethir

Aethir is a cloud computing infrastructure platform that radically changes the ownership, allocation, and usage models of enterprise-grade GPUs. By moving away from traditional centralized models, Aethir deploys a scalable, competitive framework for sharing distributed computing resources to meet the needs of various industries and enterprise clients.

Official website: https://www.aethir.com/

Twitter: https://twitter.com/AethirCloud

Fulence

Fluence is a blockchain-driven decentralized serverless platform and computing marketplace.

Developers can build applications and deploy them to a network of compute providers, ranging from data centers to home computers. Providers compete on price and performance and earn rewards and incentives.

Official website: https://fluence.network/

Twitter: https://twitter.com/fluence_project

iExec

iExec connects cloud resource sellers with buyers, encouraging the development of decentralized, autonomous, privacy-preserving applications. The network aims to provide scalable, secure, and easy access to services, datasets, and computing resources for companies.

Official website: https://iex.ec/developers/

Twitter: https://twitter.com/iEx_ec

NetMind.AI

NetMind.AI offers two products: NetMind.Power (a distributed computing platform) and NetMind.Chat (a customizable chatbot suitable for individuals and enterprises).

NetMind.Power provides vast computing resources to solve complex problems in AI, data science, and more. With it, individuals and companies can easily access powerful compute to train or run complex AI models.

Official website: https://netmind.ai/home

Twitter: https://twitter.com/NetmindAi

OpSec

As a decentralized physical infrastructure network provider, OpSec uses advanced AI to build, maintain, and operate blockchain infrastructure, ensuring security and privacy of blockchain applications.

OpSec leverages AI to enhance cloud computing, providing scalable, flexible, and cost-effective platforms for blockchain applications.

Official website: https://opsec.software/

Twitter: https://twitter.com/OpSecCloud

AI Data and Model Sources Focuses on managing and verifying the sources of data and AI models through decentralization.

Specifically, this category emphasizes ensuring authenticity, transparency, and traceability of data during AI development, as well as fairness and verifiability of model training. In this framework, data becomes a key element to optimize, as high-quality, trustworthy data is a prerequisite for effective AI training.

Blockchain plays a role by recording data and model provenance on an immutable distributed ledger, providing a transparent and secure environment for data providers, model developers, and users to verify authenticity and integrity.

Additionally, smart contracts can automate licensing and usage agreements for data and models, ensuring compliance with original owners’ intentions and promoting legitimate sharing and utilization.

Typical projects include:

Rainfall

A privacy-preserving smart platform that uses Edge-AI and Web3 technology to unlock economic value from user data while protecting privacy, reshaping data monetization.

It also generates real-time social intelligence from millions of data events, providing data references for companies, organizations, and governments to better serve their customers.

Official website: https://rainfall.one/

Twitter: https://twitter.com/rainfall_one

Numbers

An open and decentralized network ensuring that all digital media created by humans and AI has a verified data source. It protects the provenance of digital media through a decentralized ecosystem and blockchain technology, similar to version control systems like Git.

Official website: https://www.numbersprotocol.io/

Twitter: https://twitter.com/numbersprotocol

Grass

Wynd Network’s flagship product, offering an app that performs data contribution operations in the background of mobile or computer devices. It enables AI labs to directly obtain web data for training their AI models and provides datasets directly.

Official website: https://www.getgrass.io/

Twitter: https://twitter.com/getgrass_io

Koii Network

A distributed cloud computing platform where anyone with a computer can become a node and earn passive income. Using community-supported data to train models benefits everyone and reduces maintenance costs.

Tools provided support federated learning, access to training data, and crowdsourced GPU.

Official website: https://www.koii.network/

Twitter: https://twitter.com/KoiiNetwork

Flock

A unique platform integrating decentralized on-chain machine learning, providing secure and efficient solutions for AI model fine-tuning and inference.

Flock features an AI co-creation platform that rewards individuals who provide and verify data. It uses blockchain’s transparent and secure structure to track data usage and validity, determining rewards accordingly.

Official website: https://www.flock.io/

Twitter: https://twitter.com/flock_io

Hyperspace

Aiming to build a world with millions of community large language models, accessible for billions of people daily for free.

Official website: https://www.hyperspace.computer/

Twitter: https://twitter.com/HyperspaceAI

Ocean Protocol

A privacy-preserving data sharing protocol in AI and new data economy, enabling buying and selling of private data while protecting privacy, for data sharing in scientific or technological environments.

Official website: https://oceanprotocol.com/

Twitter: https://twitter.com/oceanprotocol

Syntropy

Syntropy’s data layer protocol is designed to provide and access blockchain data, allowing anyone to become a provider in the Web3 data open market. Token holders decide which providers are reliable based on data quality and overall performance, rewarding trustworthy providers.

Official website: https://www.syntropynet.com/

Twitter: https://twitter.com/Syntropynet

Token Incentivized AI Applications Utilizes cryptocurrency tokens as incentives to encourage users, developers, and other participants to contribute to AI projects and platforms.

Tokens motivate community engagement through activities like providing data, developing algorithms, offering computing resources, or training and optimizing AI models. They also serve as a medium of exchange within the platform for purchasing data, compute power, or professional AI services.

In this mode, algorithms and models are the core elements being optimized. Community efforts and resource sharing accelerate AI algorithm development and iteration, improving model quality and adaptability. Token incentives also promote data collection and sharing, as participants can earn tokens by providing high-quality data, indirectly optimizing the data element.

Typical projects include:

MyShell

A platform for creating Web3 and AI-based voice chatbots. Users can choose their favorite character to start voice chats instantly and improve language skills through discussions on topics of interest.

Official website: https://myshell.ai/

Twitter: https://twitter.com/myshell_ai

ImgnAI

A consumer-facing AI app offering models comparable to Midjourney for text-to-image generation, providing stunning art with simple text commands. User growth and revenue are driven by a buy-and-burn mechanism for ( tokens, allowing token holders to benefit from the growth of the imgnAI product suite.

Official website: https://imgnai.com/

Twitter: https://twitter.com/imgn_ai

MyPeach

An AI engine-powered companion app, allowing users to customize their companions’ attributes such as race, hair color, hair length, eye color, body type, and then converse with their personalized companions as if in the real world.

Official website: https://www.mypeach.ai/

Twitter: https://twitter.com/mypeachai

Artificial Liquid Intelligence

A decentralized protocol for creating intelligent avatars that interact using AI. The platform has pioneered a new NFT standard called smartNFT )iNFT(, embedding AI animation, voice synthesis, and generative AI functions into NFTs.

In August 2021, the project received $16 million in funding from Multicoin.

Official website: https://www.aiprotocol.info/

Twitter: https://twitter.com/real_alethea

IQ.wiki

IQ.wiki aims to build a blockchain-based AI assistant for knowledge, becoming a Wikipedia for the crypto world. Users can ask questions like GPT to get answers about projects, knowledge, and tokens related to crypto and blockchain. IQ GPT provides reliable crypto insights from multiple sources, meeting exploration, development, and trading needs.

Official website: https://iq.wiki/

Twitter: https://twitter.com/IQWIKI

CharacterX

A next-generation decentralized synthetic social network connecting humans and AI entities. The platform allows users to create their own AI identities and connect with others (AI or human) across time and space. It develops advanced multimodal AI architectures supporting multi-sensory data input/output, including 3D and AR experiences, and proactive AI agents for social scenarios, offering personalized, authentic, and privacy-enhanced social experiences.

Official website: characterx.ai

Twitter: https://twitter.com/CharacterXAI

DeepSouth AI

DeepSouth AI achieves excellent computing power and efficiency by combining neural mimetic algorithms, including spike-timing plasticity )STDP$imgnAI , direct training schemes based on backpropagation, supervised temporal learning, ANN to SNN conversion strategies, reservoir computing, and genetic algorithms.

Current products include autonomous AI, visual AI, and conversational AI.

Official website: https://deepsouth.ai/

Twitter: https://twitter.com/DeepSouthAI

KIP

KIP protocol enables AI value creators to connect their expertise—whether in data production, model training, application design, or other areas—and enjoy transparent accounting and revenue sharing.

Each component is encapsulated in an ERC-3525 semi-homogeneous token (SFT), allowing easy, low-cost real-time transfer of economic value between components, with user interaction.

Official website: https://kip.pro/

Twitter: https://twitter.com/KIPprotocol

On-Chain AI Agents and Security Involves deploying AI agents on blockchain to enhance security and trustworthiness of AI applications.

These AI agents can automatically perform tasks such as trading, data analysis, and decision-making. Deploying on blockchain makes their operations transparent, traceable, and tamper-resistant, increasing overall system security.

Within this framework, both computing power and algorithms/models are key elements being optimized, as secure AI agents require reliable resources to execute complex algorithms and models.

Additionally, on-chain AI agents can share and utilize data and resources across platforms while preserving privacy, as zero-knowledge (ZK) tech can verify data validity and integrity without revealing sensitive information.

Recommended reading: “The Rise of AI Agent Narratives: Which Projects Are Worth Watching Early?”

Typical projects include:

AI Arena

A blockchain game integrating human x AI collaboration, where players design, train, and battle AI-driven NFTs in a global competition.

Researchers drag and drop their machine learning models into the platform, then compete against AI models from other researchers. Top performers earn native tokens of AI Arena.

Official website: https://aiarena.io/#/

Twitter: https://twitter.com/aiarena_

Operator.io

A protocol for creating decentralized agent networks, standardizing information and value exchange among users, protocols, and AI agents. Users build and deploy their own agents and offer them to the world.

Official website: https://operator.io/

Twitter: https://twitter.com/operator_io

Fetch.ai

A public blockchain for AI applications, established in 2017 and mainnet launched in December 2019. It has integrated Cosmos’ IBC protocol for interoperability with other Cosmos ecosystem chains.

It can be viewed as a blockchain + AI infrastructure, with the bottom layer comprising consensus network, smart contracts, and machine learning libraries, and the top layer implementing various AI functions and applications through skill modules.

Official website: https://fetch.ai/

Twitter: https://twitter.com/fetch_ai

Modulus Labs

To enable dApps with powerful AI capabilities, dApps need to sacrifice some decentralization and accept centralized risks. Modulus Labs combines ZKML and AI to effectively verify that AI providers are not manipulating their algorithms on-chain.

On November 1, 2023, Modulus Labs announced a $6.3 million seed funding round led by Variant and 1kx, with participation from Inflection, Bankless, Stanford, and others.

Official website: https://www.modulus.xyz/

Twitter: https://twitter.com/ModulusLabs

Delysium

Delysium is an open-world framework driven by AI, providing a simplified architecture to support advanced AI agent networks and ecosystems, focusing on security, scalability, and high-speed communication. Its ecosystem includes communities, development, and interaction of AI agents, integrated into two main layers: communication (base) and blockchain.

Read more: “Exclusive Interview with Delysium Co-Founder: Solving Future AI Agent Communication and Collaboration”

Official website: https://www.delysium.com/

Twitter: https://twitter.com/The_Delysium

Agent Protocol

Aims to enable gamers worldwide to train their own AI agents from game clips supported by decentralized GPU computing, creating a new on-chain asset class.

Twitter: https://twitter.com/iAgentProtocol

Morpheus

Morpheus aims to incentivize a universal peer-to-peer AI network, where AI can act on behalf of users to execute smart contracts; ordinary users can converse with their intelligent agents in natural language, letting them understand issues and act based on user intent/approval.

Official website: https://mor.org/

Twitter: https://twitter.com/MorpheusAIs

Autonolas

A unified network for off-chain AI agents used in automation, oracles, and shared AI. It provides a composable stack for building these services and incentivizes protocol creation to run complex logic in a decentralized manner, with autonomous, continuous on-chain and off-chain data interaction.

Official website: https://olas.network/

Twitter: https://twitter.com/autonolas

Test Machine

An AI platform designed to help developers and projects quickly identify and fix smart contract vulnerabilities. It provides immediate access to industry-standard tools for compilation, optimization, testing, and real-time security analysis, with instant reporting.

Official website: https://testmachine.ai/

Twitter: https://twitter.com/testmachine_ai

DAIN Protocol

An AI agent network on Solana, still under development, recently attracting attention from multiple KOLs.

Official website: https://dain.org/

Twitter: https://twitter.com/dainprotocol

Oraichain

Oraichain’s mechanism is similar to Band Protocol and Chainlink, enabling smart contracts to securely access external AI APIs. AI enhances smart contract capabilities.

It is also a Layer 1 dedicated to hosting AI-driven dApps and AI agents.

Official website: https://orai.io/

Twitter: https://twitter.com/oraichain

AI Marketplaces and Learning Platforms Driven by Blockchain These platforms leverage AI to enhance blockchain applications, especially in market trading and online education.

They use AI algorithms to analyze market data, predict trends, provide personalized learning experiences, or automatically match buyers and sellers. AI integration improves platform efficiency and offers users more accurate and efficient services.

In this category, algorithms, models, and data are core elements, as AI performance depends on large amounts of high-quality data to train precise models, which then deliver intelligent services. For example, AI can analyze user behavior to offer personalized recommendations in crypto markets or customized educational content on learning platforms.

Typical projects include:

Bagel Network

A decentralized data platform aiming to solve data monopoly issues by creating a marketplace where data scientists and AI engineers can exchange and license verifiable datasets cost-effectively and privately. The project aims to develop a decentralized data platform supporting machine learning models.

On January 23, 2024, Bagel Network completed a $3.1 million pre-seed funding round.

Official website: https://www.bagel.net/

Twitter: https://twitter.com/bagel_network

SingularityNET

A platform for AI service trading, connecting AI service developers and users. Developers can publish their services to earn income; users can integrate these services into their websites, apps, or other products via the SingularityNET marketplace.

Official website: https://singularitynet.io/

Twitter: https://twitter.com/SingularityNET

FedML

A decentralized collaborative machine learning platform for scalable, privacy-preserving AI training, deployment, monitoring, and continuous improvement across any location and scale.

On March 28, 2023, FedML completed a $6 million seed round.

Official website: https://fedml.ai/home

Twitter: https://twitter.com/fedml_ai

Numerai

A new hedge fund built by a network of data scientists using AI techniques. Its core advantage is providing free datasets. It consists of high-quality financial data that has been cleaned, normalized, and obfuscated.

Official website: https://numer.ai/

Twitter: https://twitter.com/numerai

Allora

A self-improving decentralized AI network enabling applications to utilize smarter, safer AI through a network of self-improving ML models, combined with crowdsourcing (peer prediction), federated learning, and zkML research.

Official website: https://allora.network/faq

Twitter: https://twitter.com/AlloraNetwork/

Upshot

Initially attempted to use crowdsourcing to predict asset prices. Evolved into creating AI models capable of analyzing over 400 million assets and a trustless, self-improving decentralized AI network.

Currently, the project has launched the Upshot Machine Intelligence Network, which crowdsources financial alpha generated by ML models, supported by an “Alpha Proof” reward mechanism.

Official website: https://upshot.xyz/

Twitter: https://twitter.com/UpshotHQ

Model Verification In the intersection of blockchain and AI, model verification refers to using blockchain technology to confirm and ensure AI models’ performance, security, and transparency.

This involves leveraging blockchain’s immutable and transparent record-keeping to verify training data, algorithm logic, and performance metrics. The goal is to build user trust, ensure decision traceability and auditability, and prevent malicious tampering or deviation from original design.

In this category, algorithms and models are the key elements being optimized. Recording detailed training and operation processes on the blockchain provides a transparent evidence chain for each AI decision, enhancing trustworthiness and reliability.

Additionally, cryptographic techniques like zero-knowledge proofs can protect data privacy while verifying model outputs without revealing internal logic, further strengthening security and privacy.

Typical projects include:

Giza

Giza is building a trustless protocol that decentralizes machine learning inference computation and powers the open economy of open-source AI. Giza enables AI developers to generate zero-knowledge proofs for their models easily.

Official website: https://www.gizatech.xyz/

Twitter: https://twitter.com/gizatechxyz

EZKL

EZKL supports verifiable AI systems with zero-knowledge encryption. It can prove the authenticity of AI/ML models and generate zero-knowledge proofs that the model produced certain results without revealing the model itself.

Official website: https://ezkl.xyz/

Twitter: https://twitter.com/ezklxyz

Due to space and experience limitations, this article does not list all AI projects within each category.

However, whether for investment or research, understanding the segmentation of the entire AI track helps quickly determine the scope of new projects, providing valuable reference for decision-making.

May every crypto enthusiast harvest their own insights and rewards in the AI wave.