Alaya – Integrated solution for data collection and labeling services
With the introduction of ChatGPT’s conversational model by American AI company Open AI, it has quickly taken the world by storm and is rapidly iterating. Algorithms, data, and arithmetic power as the three cornerstones of artificial intelligence. It plays a pivotal role in the industry. In the training process, a large amount of data is needed to train the model, the data needs to be pre-processed and feature extraction, and then use algorithms for optimization, these algorithms need arithmetic support, the three are indispensable to drive the development of artificial intelligence.
Alaya plays the role of data provider in this system. According to professionals, data will account for 80% of the whole industry, and the design of the model only occupies about 20%. For example, the world-famous AlphaGo, after the completion of the model, the collection of all the ancient and modern game algorithms, and their own continuous data connection, to create the strength of the first in the Go world, and now the Go industry has been because of AlphaGo has changed radically, and players are taking AlphaGo’s overlap as a reflection of their strength.
There are three pressing issues that need to be addressed in AI collection and labeling:
- The data quality is poor, the population responsible for data feeding is currently concentrated in the third world, because the population is less educated, so the quality of some of the data is poor, with large deviations in hyperparameters;
- For the more specialized industries, the current collection and labeling can not meet the requirements, similar to the medical field, the current manual feeding industry is unable to do so for such a specialized field labeling;
- It unable to do decentralization, in the field of data, intelligence to take most of the answers to do the model behavior guidelines, then it needs enough cut decentralized data to verify, and the current too centralized data feeding is not conducive to the development of the field of artificial intelligence.
Alaya identifies problems and comes up with its own solutions. Its focus is on data collection, classification, labeling, transcription, etc. It is a distributed AI data platform that integrates collection and labeling, that originated from Swarm Intelligence and connects communities, data, and AI through Social Commerce, providing the AI industry with high quality scalable data and full protection of its ownership and privacy. Alaya is equipped with a gamified AI data training platform and has achieved exponential growth through its built-in social recommendation mechanism. The community is used to solve the pain point of lack of data and scarcity of labor for AI practitioners and to bring group intelligence together across time and space and reorganize it efficiently.
Compared with similar products in the market, Alaya pays particular attention to the breadth of data collection and the accuracy of data quality.
Data scope breadth:
In terms of the world, data collection is limited by geography and salary, is only done by a very small range of people, and cannot be done on a large scale worldwide. openAI, for instance, employs mostly third-world citizens to label its data. alaya uses blockchain technology, which is not limited by geography and allows people from all over the world to participate, making the data more credible.
Accuracy of data quality:
Alaya collects data worldwide, utilizing its own gamification model to improve data quality through a built-in hierarchy and a unique intelligent recommendation algorithm that precisely assigns needs to users with the same attribute tags.
Finally, we could clear that the importance of data feeding for the whole AI industry, more professional model building, and more accurate matching will be the direction of data feeding in the future, Alaya has been using its own advantages to move forward on this route, which deserves people’s continuous attention.
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