On July 21, China’s tech media Blue Fox Notes has published an exclusive review about DxChain, talking about their deep understanding of DxChain. Please refer down below for this interview.
Computing power, big data, and advanced algorithms are the fuel for artificial intelligence, which has seen tremendous growth over the last several years. Without data and computing power, even the top-notched experts and algorithms can hardly come up with any AI applications.
Most companies find difficulties to obtain high-quality data, a majority of which is concentrated in the hands of the tech giants. As data is the core resource in the future, those tech giants will not share them with small and medium-sized enterprises (SMEs). For example, Google Maps has user navigation data. Facebook has user portraits and behavior data. Amazon has user shopping behavior data, etc. These are the foundations of their business models and their accumulation for decades, which will enhance their advantages. SMEs can only hope to sigh.
At the same time, AI requires a significant amount of computing power and storage, which is also a huge expense for startups.
At the age of the Internet, startups have little chance of winning the battle of artificial intelligence. No data, no computing power, no fundings. But the blockchain technology enables a new age for SMEs. This is why Blue Fox Notes are putting a focus on the hybrid project of blockchain and artificial intelligence.
Recently, Blue Fox Notes noticed DxChain, which can build a decentralized data transaction market and provide services of decentralized computing power and storage infrastructure. DxChain aims to reduce the cost of data acquisition, computing power, and storage for artificial intelligence companies, or those who want to use big data analytics to boost their business and get the opportunity to compete with big companies.
DxChain and artificial intelligence
Startups or early-stage projects face challenges of getting high-quality data from the Internet. The blockchain gives a new opportunity.
First, the blockchain allows data to be returned to individuals. Users control their own data while protecting their privacy through zero-knowledge proof, differential privacy, cryptography, etc. The technology exempts users from worrying about the data leak or data abuse. At the same time, the data owners can also make money from selling data, which encourages users to share and contribute their own high-quality data actively.
Blockchain will bring out the explosion of high-quality data. This is an opportunity for SMEs.
DxChain can use the blockchain technology to build a data transaction market for both parties with data needs, enabling companies to obtain high-quality data at a lower cost and more efficient behavior. Users don’t have to worry about their privacy leaks, and they can also get a return on value — a win-win situation. On the traditional Internet platform, data was often monopolized by large platforms, and users were not rewarded for data contributions.
In addition to the data, you need computing power and storage, a very high threshold for SMEs with limited financial resources. Is it possible to reduce the costs of computing and storage and provide SMEs a competitive opportunity? This is an urgent issue that DxChain wants to address.
DxChain is attempting to use the blockchain technology to create a sharing mode for computing power and storage, which will vastly reduce costs and make big data and machine learning more focused on advancing algorithms, model iteration, and accelerate the development of artificial intelligence.
After all, blockchain is a perfect match to artificial intelligence. Both are the mega technology trends that will transform the world and can complement each other. The blockchain can accelerate the development of artificial intelligence.
DxChain is catching up with the trend by providing compute and storage services for big data analytics and machine learning through blockchains. It also helps SMEs to get data at a lower cost and more efficiently through data transactions. This will be even more powerful for the development of artificial intelligence.
Keywords of DxChain
1. Takes advantages of others
DxChain is good at taking advantages of “others,” one of its fortes Blue Fox Note is impressed with. It builds a novel blockchain technology, drives innovations, and ultimately serves the development of big data analytics and machine learning.
Easy to say, but hard to implement. First of all, DxChain must be able to integrate and use it for good. The DxChain architecture is adapted from IPFS, Hadoop HDFS, GFS, IoTeX, IOTA, Plasma, TrueBit, Morpheo, Golem, etc. DxChain plays up strengths and avoids weaknesses through its entire architecture design. For example, DxChain learns from IoTex’s architecture of a root chain with surrounding subchains, each take on different tasks.
Another example is DxChain Network started with Hadoop, the industry-proven big data platform, as its computation engine. DxChain also innovates on consensus protocol, such as Verification Game and Provable Data Computation. DxChain’s Proof of Spacetime consensus mechanism evolves from Provable Data Possession and now fits in decentralized networks.
2. Chains-on-chain architecture
With the “chains-on-chain” architecture, DxChain provides big data and machine learning related computing services with the support of decentralized data storage services. The chains-on-chain architecture is composed of a master chain, a data storage side chain, and a computing side chain.
This architecture design can accelerate the cross-chain transaction of information, data and assets, meet the speed requirements, and achieve scalability.
The master chain stores ledger and asset information, including states, transactions, receipts, as well as smart contracts. The master chain is useful for storing small pieces of data while the side chains support the complex data storage and computational tasks.
The DxChain master chain applies an account-based model to the storage of transactions and asset information, including account status, cross-account transactions, and receipts. It has regular accounts and contract accounts. DxChain uses an Ethereum-compatible data structure which is composed of hash- linked blocks. Data is distributed across the system via a network of nodes.
The Data Side Chain is built upon a P2P distributed file storage system and stores the non-assets information. The Computing Side Chain is mainly used to perform computational tasks, which solve real business problems. The computing unit can read data from the Data Side Chain and also write the result back to the Data Side Chain.
After one task is completed, the final state will be stored in the master chain via smart contracts. Intermediate status or task-level transaction information are saved in the side chains. Data side chains and computing side chains can interoperate with each other through the chains-on-chain microservices, which includes the data and messages.
In this way, the master chain and the two side chains perform different functionalities and communicate through smart contracts or micro-services, but they are still independent and isolated. The master chain will not be affected even if the side chains go wrong or encounter any damage.
The design of the chains-on-chain architecture helps achieve its goal of providing computing and storage services for big data and machine learning, which is unlike Bitcoin’s primary purpose for financial transactions. The core purpose of the side-chain architecture design is to be efficient, scalable, and to meet specific business scenario needs.
The entire system can keep a low cost on the master chain, as well as high-efficiency computing and data storage on the side chains. They communicate with each other through smart contracts. To implement decentralization, both the data storage side chain and the computing side chain should have their own consensus protocols. We will talk about it later.
Besides, you can write the active transaction of the side chain to the master chain to transfer assets from the master chain to the side chain. The side chains use the same token from the master chain, or each can define its own secondary token with the network-defined rate.
3. Decentralized computing service
Today, artificial intelligence is powered by a large amount of computing power, which is a considerable expenditure. Even large tech companies are challenged to perform large-scale computational tasks in a centralized way, not to mention SMEs.
To provide computing services for big data and machine learning, DxChain turns to decentralization. The unused computing power can be shared, and it can also be used efficiently for specific tasks.
Unlike Bitcoin which uses a massive amount of computing power to maintain the blockchain itself, DxChain provides computational resources not just for network security, but also for real business problems. Instead of giving a digital currency, DxChain delivers a decentralized computing environment.
To ensure the correctness of the computations, DxChain proposed two consensus mechanisms: verification game algorithm and Provable Data Computation.
Verification game is designed as a system with three main types of roles: solver, verifier, and judge. A solver is a miner who offers a solution to a given task, and a challenger is one who disagrees with the solution from the solver. The judges, who always provide the correct computations, use minimal computation bandwidth.
Verification game does not trust or rely on the reputation of its participants or any trusted party in the system. A deposit is needed to perform a task from both the solver and the challenger. For any faulty players, they will lose the deposit. This penalty mechanism will potentially eliminate the untrusted players with the passing of time.
Provable Data Computation was introduced for allowing a client that has stored data on an untrusted server to verify that the server saved the original data without retrieving it.
In Provable Data Computation, a computational task is broadcasted across the network, with N nodes performing the task. The answer which was the first identical one that M nodes generated is chosen as the valid answer.
DxChain also integrates Hadoop to achieve decentralized computing. The Hadoop core elements are job tracker, task tracker, and worker built on MapReduce. Akin to Hadoop, DxChain Network has two designated roles: D-Job Tracker and D-Task Tracker, to perform two different tasks. The miner is intended to receive the incentive if the miner is honest in executing the task that it promises; otherwise, the miner will lose the deposit.
MapReduce is a centralized design system, in which the job tracker manages cluster resources and job scheduling. The task tracker in each agent manages tasks in the nodes as well as communicates with the job tracker.
DxChain Network is a decentralized system which triggers the difficulty of keeping real-time communications between two nodes in a distributed network. In DxChain Network, there is no need to check the states of the task nodes. More copies of redundant computations running in different nodes, as well as whether one or few nodes are off-line or dead, will not have an impact on the final result.
The Hadoop system knows the activeness of the node through its state of activity. If some of the nodes running active tasks are dead, the job tracker must reassign tasks to new nodes.
When a node completes a computation, the job tracker will send the result to the computing side chain through verification game or Provable Data Computation. The computing side chain saves the work assignment information and results.
4. Decentralized data storage service
Providing a decentralized computing environment, DxChain is a decentralized storage network where files are stored for computation results and all kinds of intermediate computation states.
The data side chain is built on a P2P distributed storage network, such as IPFS, Swarm, and so on. The chain works as an incentive layer, which does not need to store data. Data and files are divided into small pieces and kept in the p2p network.
Meanwhile, the meta information and hash for each piece are stored in the chain, known as the file state, which similarly uses the Merkle Patricia Tree structure. DxChain has also designed a cross-chain URI for the file itself so that the data can be easily accessible across the network and chains.
Between the data chain and P2P storage network, DxChain also has a virtual logical layer, which includes a storage task giver, miners for importing and exporting files and a verifier.
Since DxChain uses a decentralized approach, miners who provide data storage need a consensus mechanism to drive incentives and secure the network.
Proof of Spacetime (PoSt) is used as the consensus method for the data storage chain to validate the provision of storage. The data side chain manages storage tasks and will also be connected to the master chain for giving storage miners incentives as well as the computing side chain for storing computation states. Its advantages include faster setting times, lower transaction fees, more rapid transaction speed, higher privacy and the ability for transparency.
Proof of Spacetime is well-suited for the decentralized network because it improves on Provable Data Possession, which allows a client that has stored data on an untrusted server to verify that the server saved the original data without retrieving it.
Provable Data Possession provides a solution that a client must keep sending challenges to a server to verify if the server store some files in continuous time.
Proof of Spacetime, on the other hand, can prevent Sybil attacks with algorithms and ensure the system is complete and secure. It can always produce valid proofs, convince a verifier, and avoid any adversarial assaults if any honest prover stores a file.
The Proof of Spacetime consensus can also be publicly verifiable to protect privacy and prevent other malicious behaviors. It can also enable a prover to prove a statement to a verifier without revealing anything about the statement in a zero-knowledge proof protocol.
5. Privacy protection
Personal identity information can be recognized through the correlation analysis of big data. DxChain also put a lot of focuses on privacy protection.
DxChain provides privacy protection through the following aspects:
Data Model: The DxChain Network supports data models for structured datasets, so clients should encrypt columns containing sensitive data such as SSN before submitting their data to the network.
Differential Privacy: Differential privacy methods mitigate the probability of one user skewing query results and allowing information to be traced back to that user. If the users want to provide data only for statistical analysis, such as calculating mean and standard deviation, DxChain Network has a tool to facilitate the users in running differential privacy before submitting files to the network.
Miner Storage Encryption: The data piece is encrypted by using a storage miner public key in each local machine. Doing this protects against intrusion from network hackers as they do not know the private key of the miner.
Of course, customers want data to be stored privately, which is best to encrypt the data before submitting it to the network.
6. AI infrastructure
From the above description, we can see that DxChain aims to become the infrastructure for big data analysis and machine learning. It supports different industries such as advertising, finance, games, healthcare, travel, energy, logistics, supply chain, education and more. These industries can leverage DxChain’s ability for machine learning, data mining, data storage, and develop a variety of different decentralized applications.
DxChain is infrastructure, so its implementation is especially critical for SMEs and startups. Many SMEs are in shortage of high-quality data, so they have to purchase high-quality data from other large companies. Many high-quality samples owned by these companies are never available to the market
By using the data model of DxChain Network to standardize data,
data exchange and sharing are enabled by each vendor opening their APIs to others through, which is very appealing to companies thirsty for high-quality data, especially for artificial intelligence companies.
DxChain is also a data trading platform. The user can define which data to trade, as well as the price of the transaction. This will benefit both the data consumer and the supplier.
Not only that, the maintenance cost of computing and storage is also high. By building decentralized big data and machine learning networks, DxChain allows artificial intelligence vendors to reduce costs and develop their own machine learning platforms and applications. Their data is stored on the storage miners’ disks, and miners share bandwidth to minimize data storage and network traffic costs.
For example, in the healthcare industry, smart devices can provide users with remote diagnosis and benefit more people. However, many low-income people even cannot afford it. Medical smart devices are fragmented and hard to be integrated. User data can be misused merely.
As a decentralized big data and machine learning network, DxChain network could potentially enable the ecosystem developer to leverage on it to build its own big data and machine learning platform.
With DxChain Network, the cost for storing data and managing traffic will be reduced significantly, which will potentially help to lower the healthcare premium.
The data collected through fitness trackers, mobile apps, smartwatches and other devices linked to the network are encrypted and stored on the blockchain in a tractable and secure way. Users can also exchange their data for economic profits.
Finally, based on data collected by medical devices, healthcare providers can establish their own artificial intelligence technology to monitor patient health and send critical vital signals to the community.
In general, with DxChain, different industries can build their own big data and machine learning platforms and applications, and can significantly reduce the development cost of artificial intelligence. DxChain can help developers in different industries to obtain more high-quality data at a lower price as well as the computing power and storage, ramping up the development of artificial intelligence.
Conclusion
The development of artificial intelligence cannot exist without data, computing power and storage. Regardless of how advanced the algorithm is, AI needs the support of underlying infrastructures.
With blockchain, the way people contribute data and get data is changed. Users can sell their high-quality data to data consumers, such as artificial intelligence vendors, advertisers, etc. while protecting personal privacy. Small and medium-sized artificial intelligence vendors also have the opportunity to obtain high-quality data at a lower cost. This is the best way to break through the data monopoly in the traditional Internet era.
Blockchain also brings decentralized computing power and storage sharing services that can reduce costs by encouraging miners to make contributions. This allows SEMs to build their own big data and machine learning platforms and applications at lower prices.
DxChain is aspired to integrate the advantages of other projects through blockchain technology to design an architecture that can be used for big data and machine learning to achieve more efficient, secure and scalable artificial intelligence infrastructure services.
DxChain proposed the design of the chain, with a master chain and two side chains; designed a consensus mechanism for verification games and verifiable computations; integrated Hadoop into DxChain for big data and machine learning. These designs are based on big data and machine learning business problems. The DxChain blockchain network not only takes advantages of decentralization but also keeps an eye on implementation.
If DxChain can be applied to the real business scenarios smoothly, it will be good news for industries that want to optimize and upgrade with artificial intelligence. We are looking forward to the early implementation of DxChain.
