Extraction Process in the Mining Industry
In the realm of scientific research, a revolutionary approach is being pioneered by a startup that seeks to harness the power of the Bittensor blockchain for drug discovery. This innovative platform, designed to accelerate the discovery of new drugs, is attracting attention for its potential to transform the pharmaceutical industry.
At the heart of this endeavour is a neural network named Egret-1, specifically developed for drug research. Egret-1 is designed to simulate chemical reactions at the atomic level, a feat that could significantly speed up the drug discovery process. However, for Egret-1 to be successful, it requires much more high-quality data generated through density functional theory (DFT).
The Bittensor blockchain, unlike traditional systems, operates on an election-based consensus mechanism similar to Ripple's or Proof of Authority systems like Binance Smart Chain. In this system, peers in the network vote for consensus and rate each other's trustworthiness. This approach creates a digital goods marketplace as an end in itself.
One of the key subnets within the Bittensor blockchain is Macrocosmos's "Mainframe" subnet (SN25), designed for scientific simulations, particularly protein folding. SN25 is designed to lower the cost of protein folding simulations, a foundational problem in chemical biology for which AI is particularly promising.
In each Bittensor subnet, the consensus tasks for miners and their validation by validators are defined. In the Macrocosmos system, validators check miners' outputs using specific heuristics, and the miners who perform best receive tokens from Bittensor-TAO as a reward.
The network is divided into miners, validators, and stakers of the TAO token. Peers in the network vote on their influence in the network, mutually rank themselves and their neighbours, and log these scores on a blockchain. This system is designed to be resistant to collusion up to 50% of the network's total weight, providing the same security parameters as Bitcoin and other blockchains.
SN25 employs the "GROMACS" standard to simulate protein folding but integrates this into a "competitive design" that incentivizes miners to develop machine-learning models that solve protein folding as efficiently as possible. Once consensus is reached in a subnet, it is propagated to the global blockchain layer.
To generate the necessary data for Egret-1, the neural network will leverage the decentralized computing power of the Bittensor network's Macrocosmos subnet. While no specific companies have publicly announced using the Bittensor blockchain specifically for drug development, the platform is expanding its decentralized AI infrastructure with 128 active subnets serving applications like fraud detection, synthetic identity generation, autonomous navigation, and federated learning.
The Bittensor blockchain is intended to become a marketplace for machine intelligence, where intelligence is priced peer-to-peer on the internet by other intelligent systems within the Bittensor network. This decentralized approach could potentially make drug discovery more accessible and cost-effective, revolutionizing the pharmaceutical industry.
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