Bytom Blockchain Protocol (hereinafter referred to as compared to the original chain: Bytom) is a kind of the communication Protocol of multiple bits assets running on different than the original chain block chain, heterogeneous bit assets in the form of digital currency, digital assets (native) and atomic assets (with traditional physical world counterparts, warrants, equity, dividends, bond, intelligence information, forecast information, etc.) can be registered through the agreement, exchange, bet, and more complexity of interactions based on contract. Connecting the atomic world with the bit world facilitates the interaction and flow of assets between the two worlds. Compared with the original chain, it adopts a three-layer architecture: the application layer, contract layer, data layer and application layer are friendly to mobile terminals and other multi-terminals, which facilitates developers to develop asset management applications conveniently. The contract layer adopts the creation contract and control contract to issue and manage the assets. The UTXO model BUTXO, which supports the extension at the bottom, optimizes the virtual machine and adopts the introspection mechanism to prevent the dead-in state of complete Turing. Data layer to use distributed books technology, to realize the distribution of assets, cost, and exchange operations, consensus mechanism using of artificial intelligent algorithm, ASIC chip friendly POW introduced matrix in the process of the hash and convolution computation, makes the mill after the idle or be eliminated, can be used for AI hardware acceleration service, so as to generate additional social benefits.
View the full content of BTM
View the full content of BTM
"Our task is to connect the bit world with the atomic world and build a diversified, decentralized network of decentralized assets." Bytom will greatly facilitate the bit information of existing value attributes, the exchange, interaction and flow of bit assets. Through the contract and configuration, will also generate new bit assets. Bytom will also create applications in a decentralized form of market-based management protocols and at the same time provide unique incentives for local and global bit-economy players. Bytom, as a medium, is well-positioned to become an information-enabled economy, an amplifier of information asset effectiveness. In the future, these information assets will not only be available to existing everyday work lives, but also be providers of "data foods" to artificial intelligence, IoT devices to further accelerate their impact on the atomic world.
1. Build a standard for the registration of diversified bit assets
Bytom aims to establish a global open Byte Assets registration platform. It's easier and easier for users to create and define, generate a bit asset.
2. Build a diversified interactive tool bit assets
Bytom will also support more complex forms of interaction, from the most basic means of exchange of assets (the exchange of agreements between ownership and ownership of different digital assets, for example)
A Triggering Tools: Assets Voting in accordance with contractual terms produces deterministic Y / N Boolean or numerical results to activate participants in the atomic world to share datasets;
B Forecasting tools: For example, forecasting information such as zero-sum game, betting between two or more parties, whether a flight is delayed, who will win out of two candidates, and using this forecast information in real-world financial hedging, insurance and other fields.
Artificial intelligence ASIC chip friendly POW algorithm
Adopting artificial intelligence ASIC chips friendly POW algorithm, making the mine machine idle or be eliminated, can be used for AI acceleration service.
Bitcoin miners and artificial intelligence are comparable in depth, all of which rely on the underlying chips for massively parallel computing. The vast majority of deep learning algorithms can be mapped to the underlying linear algebra. Linear algebra has two main characteristics: First, Tensor flow irregularities can be expected; Second, the high computational density. These two major features make AI deep learning especially hardware-accelerated.