What Makes Matrix AI Different?
In today’s world, AI is developing at an unprecedented rate, and new AI services are popping up every day. As a next-generation AI-powered blockchain service, Matrix is also launching its 2.0 blueprint following the successful completion of Matrix 1.0. Therefore, one may wonder: what advantages does Matrix have over its competitors? We are going to explore this in the article that follows.
Matrix vs Traditional Public Chains
Matrix is set apart from its competitors in the AI and the blockchain industry in a number of ways.
Integration of AI and Blockchain
Different from blockchain projects seeking to ride the AI hype, Matrix is truly dedicated to its ideal of using AI to empower blockchain and blockchain to manage AI, with a view to building an efficient and decentralized AI ecosystem.
To begin with, Matrix has used AI technologies to build an efficient, environment-friendly and secure blockchain platform. Now on top of that, Matrix is taking advantage of this platform to create a decentralized AI ecosystem to facilitate the exchange of decentralized data, computing power and algorithms.
In this ecosystem envisioned by Matrix, AI and blockchain are equally important. The two are fully integrated and interdependent. This is in stark contrast to most competitor projects where either AI or blockchain takes dominance, and the other only plays a secondary role.
AI Consensus Algorithm
The security of blockchain is thanks to its distributed accounting mechanism, and maintaining this system consumes a lot of resources. This is why Bitcoin mining is criticized by governments and environmental organizations. This issue can be solved in two ways: 1. optimizing the consensus encryption algorithm to reduce energy waste, and 2. optimizing the consensus mechanism to reduce computing power waste.
Matrix hopes to use MCMC (Markov chain Monte Carlo) to take the place of hash algorithms. Like hash, MCMC is a result convergence algorithm where results can be verified. But different from hash, MCMC is suited for wide adoption by the AI industry. MCMC could be the perfect hash replacement, although there is still a long way to go. But even before that happens, Matrix is already employing an optimized hash solution in its current version. Matrix’s consensus encryption algorithm adopts an AI+hash hybrid algorithm. Although this doesn’t eliminate the energy waste of hash computing, it does make Matrix’s mining and accounting beneficial to society. Current Matrix AI services such as facial recognition and license plate reading are all based on this hybrid algorithm.
In the following part, we will compare Matrix with a few well-known AI projects.
Matrix vs DeepBrain Chain
DeepBrain Chain is essentially doing the same thing as Matrix: building an efficient distributed computing power network. But beyond this, there are differences:
Consensus Mechanism vs Consensus Algorithm
DeepBrain uses a DPoS consensus mechanism, while Matrix has a DPoS+PoW consensus mechanism. Matrix also employs AI-based random clustering algorithms in its DPoS. Of the two, Matrix's consensus mechanism is more secure, and with AI algorithms in its PoW, Matrix has more thoroughly integrated AI into its consensus mechanism.
Currently, DeepBrain is focused on building a computing network made up of multiple powerful computing centers. In contrast, Matrix is building a truly decentralized network. Both arrangements have their advantages. DeepBrain Chain is more suited for large-scale computing centers, while Matrix is better at gathering ordinary users' and companies' spare computing power. By the same token, DeepBrain is better for time-sensitive AI tasks with low privacy requirements, while Matrix is better for non-time-sensitive tasks requiring a high privacy level. At the same time, Matrix's decentralized structure will make its computing power more affordable.
DeepBrain envisions a computing power distribution platform, while Matrix is not limited to computing power but also aims to build a data platform, an algorithm and service platform as well as a trading platform. This complete ecosystem will be to Matrix's advantage in attracting more algorithm scientists.
Matrix vs Singularity NET
Singularity NET aims to build a distributed AI platform where AI algorithms are backed up onto every single node on the blockchain. AI scientists can also provide their own AI algorithms and services to Singularity NET’s users, who will pay for the services with the designated token. In this sense, its business model is similar to MANAS of the Matrix ecosystem, although there are differences too.
Singularity intends to use its own platform to host all transactions and has built its own commercialization team. In contrast, Matrix will primarily focus on developing new technologies and platform features, and for the commercialization, Matrix will provide API and SDK for anyone with customer resources or experience operating a business to build his/her own AI cloud computing/AI service platform using our tools. This is an ecosystem where all parties can play to their strengths.
A Single Algorithm Service Market vs A Complete Ecosystem of Market, Data and Computing Power
Singularity provides a secure and easy-to-use market for AI scientists to sell their algorithms. Matrix goes one step further by providing computing power and data for AI scientists as well, which makes working on Matrix very convenient for the scientists. Users of algorithm services on Matrix can benefit from cheaper computing power, and Matrix miners are also better rewarded.
Matrix supports minting algorithm scientists’ works into NFTs to protect their intellectual property. This will also create more liquidity for algorithms on Matrix and give algorithm scientists a new way to profit.
Matrix vs Fetch.ai
Fetch.ai aims to use AI technologies to bring real-world people, equipment, and even companies into the digital world and build an autonomous economic agent (AEA). Simply put, Fetch.ai is an automated data transaction network. So how is this different from the data platform Matrix is building?
Fetch.ai uses the Sharding technology of DAG for data storage. This is a different type of decentralized storage from Matrix’s more traditional IPFS storage, and only time can tell which one is better.
Trading & Usage
Fetch.ai is purely a data trading platform. Its innovative UPOW is advanced in many ways. However, the current design of Fetch.ai makes it relatively easy to duplicate data on its platform. Matrix, on the other hand, has separated the ownership and usage rights of data, making data easier to be traded. Matrix’s distributed machine learning system (federated training) also protects data from being duplicated. This guarantees the value of data so that owners can keep profiting from their data assets into the future.
Matrix vs Centralized AI Platform
Having created an high-performance AI-empowered blockchain in Matrix 1.0, Matrix 2.0 will focus on building a decentralized AI ecosystem based on this efficient blockchain. So how is Matrix better compared to traditional centralized AI platforms?
A Multidimensional Big Data Platform
Different from a centralized platform, Matrix seeks to transform data into the personal assets of users, as opposed to the assets owned by the platform. Not only do users get rewards for uploading data, but they also keep ownership of the uploaded data and earn returns when the data is used by others. This feature would not be possible on a centralized platform.
Under this notion, we could soon see the world’s first multidimensional big data platforms. Compared to “single dimensional big data” provided by current big data companies and “multidimensional small data” owned by individuals, multidimensional big data will be of a higher quality and serve as the source material for AI development. With the arrival of multidimensional big data platforms, Matrix as well as the entire AI industry will see explosive growth.
Affordable Computing Power
Compared to traditional centralized AI computing platforms, another advantage of Matrix is affordable pricing, since computing power providers in Matrix AI Network already earn their investment back through mining, and leasing idle computing power is merely a side income for them. Compared to the expensive computing power which AI companies currently use, Matrix’s cheaper alternative will no doubt benefit the AI industry.
Of course, Matrix’s computing power cannot match centralized computing platforms when it comes to response speed. But affordability still gives Matrix an edge, especially for tasks that don’t require high response speed such as AI model training.
A Diverse Ecosystem
Computing power and data are indispensable resources for the development of AI. In the Matrix ecosystem, we will have a multidimensional big data platform to provide high-quality data, as well as a computing power distribution platform to provide affordable computing power. All this will attract more AI scientists to join Matrix in the future, and competition among a large number of AI services will help diversify the Matrix ecosystem and get the AI industry on the fast track.
An Open Platform
Matrix does not plan to hold monopoly over the computing power and AI services on its platform. Instead, our team will focus on developing new technologies and platform features, while for the commercialization part we provide API and SDK for anyone with customer resources or experience operating a business to build his/her own AI cloud computing/AI service platform using our tools. This is an ecosystem where all parties can play to their strengths. We will let the world promote our services for us, and this is Matrix’s way for the future.
Matrix will also hold an open attitude towards algorithm scientists. Every scientist can create and launch his/her algorithms and services here. This will mean more options for users, and individualized services can better meet the needs of everyone.
Matrix vs Decentralized AI Platforms
A Complete Ecosystem
Compared with the average decentralized AI platform, Matrix provides a complete ecosystem of solutions for building AI services. The multidimensional big data platform supports AI scientists’ demand for data; MANTA provides scientists with affordable computing power; MANIA help scientists authenticate their works; MANAS delivers their services to businesses and customers for commercial use. All this, combined with an open platform, will create endless opportunities.
An Easy-to-Use AI Creation Platform
MANTA, a platform recently launched for beta testing, is the world’s first auto-machine learning platform. Thanks to the platform, the ownership and usage rights of users’ data can now be separated for better protection, More importantly, AutoML will help AI scientists improve the efficiency of their workflow, creating more and better algorithms and services under the same cost. This will attract more AI scientists to the Matrix ecosystem and more AI algorithms and applications onto MANAS.
NFT is a trending topic these days, and Matrix has taken the innovative approach of integrating AI algorithms with NFTs. This way, the works of AI algorithm scientists can be converted into digital assets stored onchain, which can then be used by or traded among community members. This solution guarantees the protection of AI intellectual properties and also boosts the liquidity and value of algorithms. Most importantly, this also marks the first time NFTs with practical value are created.
Matrix has a unique edge over competitors in three ways:
1. High quality source materials (computing power and data) for algorithm scientists;
2. Fewer barriers for AI algorithm creation thanks to AutoML, thus better and more diverse services;
3. An open platform with endless possibilities.
Matrix is pioneering the integration of AI and blockchain, and it will only be a matter of time before Matrix becomes a giant in both industries.