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Crypto X AI is the main theme running through the cryptocurrency market this year.
With continuous breakthroughs in AI within the tech sector, numerous projects related to AI concepts are rapidly emerging in the crypto space. While each project sets astonishing records of gains, it's easy to get lost in the vast sea of projects:
With so many AI projects, what exactly are they doing? Which category do they belong to? How do we analyze the value of these projects?
AI is just a two-letter abbreviation, but when combined with blockchain, its business scope goes far beyond the simplicity of letters.
Therefore, understanding the full landscape and subtypes of Crypto X AI helps us quickly identify whether a project has narrative value and the magnitude of the value it holds.
In this edition, we attempt to classify and organize the business formed by the combination of Crypto and AI, providing a reference roadmap for capturing value in the AI wave.
The Basic Logic of Crypto X AI
Firstly, it needs to be clarified that AI is fundamentally a form of productivity. To unleash this productivity, three basic elements are indispensable:
Computing power, algorithms (models), and data.
As for Crypto or blockchain, it is more of a production relationship, promoting the development of AI by providing a better environment.
So, how can this environment affect the three elements of AI mentioned above? Different answers will lead cryptographic projects in different directions:
Optimizing Computing Power: Providing decentralized and efficient computing resources, reducing the risk of single points of failure, and improving overall computing efficiency.
Optimizing Algorithms: Encouraging the open-source, sharing, and innovation of algorithms or models.
Optimizing Data: Decentralized storage, contribution, usage, and secure management of data.
Around these three points of optimization, we can roughly divide the entire AI track into the following six directions (since computing power, algorithms, and data mutually influence each other, a ✓ in the table represents the main optimization point, not necessarily meaning only one point is optimized).
The following will introduce each direction's business content and representative companies and projects.
Decentralized Computing and AI Inference Platforms
Decentralized computing and AI inference platforms refer to the use of blockchain technology to establish a distributed computing network. Through this platform, idle computing resources can be shared and utilized globally for executing AI model training and inference tasks.
This platform disperses computing tasks to multiple nodes in the network, enhancing both computing efficiency and reducing the risk of single points of failure.
In this framework, computing power becomes the core element being optimized, as decentralized computing platforms directly offer a broader and more economical range of computing resources.
Typical projects related to this classification include:
Ritual
Aims to create an incentive network to power distributed computing devices and provide services for machine learning-related inference workloads. Users can build and host ML models, deploying them to Infernet nodes in Ritual.
On November 8, 2023, Ritual completed a $25 million Series A funding round, led by Archetype, with participation from Accomplice, Robot Ventures, and others.
Akash Network
A distributed peer-to-peer marketplace for cloud computing, offering a secure platform where users can send data to each other and develop.
Through integration with Cosmos, Akash Network benefits from interoperability and scalability, enabling seamless communication with other blockchain platforms. This allows developers and organizations access to distributed cloud service computing power at a fraction of the cost of centralized services.
RNDR
A well-known decentralized GPU rendering solution provider aiming to connect users wishing to perform rendering jobs with individuals having idle GPUs for rendering. Owners can connect their GPUs to the rendering network, receive and complete rendering jobs, and earn RNDR rewards for executing rendering tasks.
Bittensor
An open-source protocol with its token TAO reaching new highs. In the Bittensor network, participants are encouraged to share their computing resources, data, and AI models using a cryptocurrency incentive mechanism, enabling global machine learning models and algorithms to learn and improve from each other.
Read more: "Decoding Bittensor (TAO): The Ambitious AI Lego That Makes Algorithms Composable."
Analyze
A decentralized computing network supporting the development, execution, and scaling of machine learning (ML) applications on the Solana blockchain. It utilizes the world's largest GPU cluster, allowing machine learning engineers to access distributed cloud service computing power at a cost considerably lower than centralized services.
Hyperbolic
Aiming to create a computing platform accessible to everyone, where people can share and access computing resources.
Gensyn
The concept of Gensyn is to link the computing power of idle, machine-learning-capable computing devices (such as consumer-grade GPUs, custom ASICs, and SoC devices capable of training neural networks) from around the world through a global supercluster. This significantly increases the available computing power for machine learning.
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.
Prime Intellect
A decentralized AI platform that commodifies computing and intelligence, providing developers with more affordable distributed computing and a sustainable business model for open-source models.
Inference Labs
Inference Labs is the trustless execution layer of artificial intelligence, focusing on interoperable AI inference on the blockchain. The project sees this as an important step toward making artificial intelligence accessible to anyone without counterparty risk.
Nosana
A decentralized GPU grid developed and customized for AI inference workloads.
It offers a new solution for organizations and individuals seeking massive computing power without spending too much money, with costs up to 85% lower than traditional public clouds. Users can directly access GPU nodes that can scale computing needs on demand, while consumers, miners, and enterprises can monetize idle hardware by becoming Nosana nodes.
Lilypad
Lilypad is a verifiable, trustless, and decentralized computing network designed to promote mainstream adoption of web3 applications. By extending access to unrestricted global computing power, Lilypad strategically collaborates with decentralized infrastructure networks like Filecoin to create a transparent, efficient, and accessible computing ecosystem.
Prodia
Prodia is an AI inference API, envisioning making AI accessible to everyone and providing a fast and user-friendly API for image generation. |
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Post time 3-3-2024 04:16:02
