Artificial Intelligence on Block chain

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In the past, agencies used central data repositories to support transaction processes and computations. Control of the database is in the hands of its owner, who manages access to and updates to the database, which limits transparency and scalability. It also makes it difficult for outsiders to ensure that data records are not manipulated.
But with advances in software, communications and encryption, a cross-organizational distributed database is now possible.

Data and application development platform for creating block chain
artificial intelligence
Project Ture block chain protocol has an artificial intelligence learning artificial intelligence network module. The distributed artificial intelligence algorithm in block interleaving chain architecture, is the core module of the TURE block chain. Through data validation, AI developers can prevent false files and data on the Ture network.
At present, after the rapid development of the mobile Internet, the field of information technology is experiencing difficulties such as weak innovation and fierce competition. The dividend of innovation in business model based on technological development is disappearing. Industrial development is facing the ceiling, and a new round of technological changes is urgently needed to drive the overall upgrading of business models. It marks the end of the high tide of mobile internet reform and the next wave of artificial intelligence.

Artificial intelligence involves a wide range of fields, and has been deeply into people’s lives. Big data’s accumulation and application, people began to find a certain law in it, which triggered the need for analysis. As hardware performance and computing resources grew stronger, big data gave birth to today’s artificial intelligence. A lot of things that only people could do in the past are now being implemented through machines. Typical examples include voice assistants, driverless, robots.
The AI is based on big data, but these resources are usually in the hands of the giants, which is why the headlines in this area are always in the hands of Microsoft, Google, IBM, Apple, Companies like Amazon and Facebook are taking over. In China, companies like BATand JingDong also have a strong user base and have already launched apps.
The artificial intelligence itself is the partner that big data must combine in further development. Big data collects not only the standardized data, but also a large amount of unstructured data and a large amount of heterogeneous information of different dimensions.
“structured data” can be stored in ordinary databases, and the corresponding processing will be more standardized and simple. “unstructured data” involves a variety of information sources, and the proportion of “unstructured data” will rise sharply in big data’s time. Especially with the rise of social media, there has been an explosion of growth. It is not easy to really analyze these big data, whether it is natural language processing technology, image analysis technology or speech recognition technology. Without the help of artificial intelligence, big data is very difficult to do high-level processing and analysis. Network depth learning is the further development of artificial intelligence. Artificial intelligence needs not only the analysis and interpretation of existing information, but also the establishment of active information acquisition and learning ability.