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Bittensor- Blockchain for AI

Bittensor is a decentralized peer-to-peer network for machine intelligence. The Bittensor protocol establishes a marketplace that transforms machine intelligence into a tradable commodity.

 

Bittensor network -

 

It consists of

 

Subnets are competitive, and only 32 subnet slots exist in the Bittensor network. Subnets exist to produce decentralized intelligence. Each subnet is an incentive-based competitive market in action, to produce the best decentralized intelligence. Entities in the subnet, called subnet miners, each perform a useful task. Rewards are given in the form of TAO tokens.

 

Validators-  Separate entities in the same subnet, called subnet validators, each independently evaluates the task performed by the subnet miners.

 

Consensus-

 

The Yuma consensus is a groundbreaking consensus mechanism that the Bittensor Network has developed. It is a decentralized, peer-to-peer consensus algorithm that allows for the distributing of computational resources across a network of nodes. It is highly scalable and it is a combination of Proof-of-Stake and Proof-of-work mechanisms.

 

Every 12 seconds a new TAO is created (i.e., minted). This single TAO is then distributed among the 32 subnets. So every 12 seconds each subnet gets a fraction of this newly-created TAO, based on the performance of the subnet.

 

TAOUSD hit an all-time high and surged more than 25% in the past two days.It holds above the short-term (21 and 55 EMA) and above the long-term moving average. It hit a high of $714 and is currently trading around $685.87.

 

The bullish invalidation can happen if the pair closes below $500. On the lower side, the near-term support is $580. Any break below targets $550/$500. Any breach below $500 targets $394/$300.

 

The pair's near-term resistance is around $720. Any breach above confirms minor bullishness. A jump to $791/$850 is possible. A surge past $850 will take it to $1000.

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 It is good to buy on dips around $600 with SL around $500 for TP of $800.

 

 

 

 

 

 

 

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