Nebula AI is committed to building a decentralized basic artificial intelligence computing chain (Zhiyun Chain), reducing the energy consumption of traditional proof of work by converting GPU mining machines into artificial intelligence computing services. NBAI tokens are used to purchase computing power, such as: developer testing; the use of DAI applications; purchase of DAI training services, etc.

Project Objectives

In order to improve the current situation of centralized cloud computing, we use the decentralized features of blockchain technology to rent and allocate computing power globally. Blockchain encryption technology effectively avoids the existence of internal leaks, while the maintenance of distributed AI computing units is handed over to the owners of large and small artificial intelligence computing units, greatly reducing the maintenance workload. This overall goal can be split into the following sub-targets: 1. Shared AI computing platform
The shared AI computing device platform will address the imbalanced demand situation between owners and users of AI devices. The owner of an AI computing device cannot achieve its computing potential 100%, resulting in some of the computing resources being idle. At the same time, a large number of users who need the computing power of artificial intelligence cannot obtain cost-effective AI computing resources. Point-to-point payment and blockchain accounting technology completed through blockchain technology can enable shared AI computing power to complete payment and sharing in the most convenient way.
2. AI Physical Computing Unit
A large number of GPU computing miners can be converted into AI computing units, thereby converting from simple hash computing to more meaningful AI task computing. Due to the particularity of AI computing, it is necessary to preinstall a designated system and regularly update the client, including the accounting system, in order to better utilize the hardware performance and share AI computing capabilities.
3. Decentralized AI Application
When decentralized AI applications are connected to the system, the corresponding connection is required for DAI App programmers to develop and call in a convenient way to use the powerful computing power in the platform. It mainly includes payment API, computing power estimation API, workload estimation API, etc., thereby accelerating the development of AI applications.
4. Integrated IPFS distributed storage
Decentralized applications need to use file storage systems to store data. One option is to replace traditional centralized cloud storage or local file storage, thereby achieving better distributed storage.
IPFS InterPlanetary File System (IPFS) is a network transmission protocol designed to create persistent and distributed storage and shared files. It is a content addressable peer hypermedia distribution protocol. Nodes in an IPFS network will form a distributed file system. Most of the future IPFS will use cross-chain technology to call. For cross-chain technology, please see Cross-chain service calls.
5. AI Engineer Training Center
Nebula AI will build a system-based artificial intelligence training center to provide basic knowledge in the field of artificial intelligence practice. Engineers will gradually build and train artificial intelligence models in product design through systematic learning and project practice. We are committed to disseminating the latest applications and knowledge of the artificial intelligence industry and cultivating and delivering outstanding artificial intelligence talents. We have the mission of filling the talent shortage and giving full play to the power of artificial intelligence in business.

User value

The system's tokens are used to purchase computing power. When the training data is small, the tokens are consumed relatively fewer, and when the training data is large, the tokens consumed correspondingly increase. The fees paid are related to the training cost and the value of the current token. Calculate the computing power generated in one minute for each 1080Ti graphics card, which is 7514 GFLOP/s× 60.

User usage scenarios

1. Quantitative Trading
Quantitative trading has been using machines to assist in the work since early on. Analysts design some indicators through various quantitative models, observe data distribution, and use the machine as an operator. Until the rise of machine learning in recent years, data can be quickly analyzed, fitted and predicted in large quantities, thereby more accurately predicting the future trend of financial products. However, the calculation of these models requires a lot of artificial intelligence computing power. If the traditional approach is adopted, each trading department needs to build a data center on its own. Shared computing power can save expensive maintenance costs. Make financial trading companies more focused on predictions themselves.
2. Artificial Intelligence Learner Program
Colleges and universities are currently gradually offering artificial intelligence courses, and this trend will become more popular in the next year. When students are studying, they will generally choose to run small tasks locally and time-consuming tasks in the school computer room. However, these fragmented tasks can be solved with blockchain computing power cloud. Low-cost AI computing services are ideal for students to complete various computing exercises and quickly modify their own models.
3. Biomedical Artificial Intelligence
Early screening of tumors is of great significance, but due to the small areas of early cancer lesions, traditional methods are difficult to judge benign and malignant, which creates difficulties in clinical diagnosis. Doctors often need to conduct testing through biopsy, which not only increases medical costs, but also brings great pain to patients. The application of artificial intelligence to medical image recognition and multidisciplinary collaborative diagnosis can effectively break through this difficulty, improve doctors' diagnostic capabilities, help make quick decisions, and promote the transformation of medical services to individualization and precision.

*The above content is compiled by the official account of non-small accounts. If reprinted, please indicate the source.