Exploration of Extraction Processes in Mining Industry
In the world of science and technology, a groundbreaking blockchain platform is making waves in the realm of drug discovery. Bittensor, a blockchain designed primarily for mining, is set to transform the marketplace for machine intelligence.
The core innovation of Bittensor lies in its separation of the blockchain's core function from the operation of the validation system, creating a digital goods marketplace as an end in itself. This unique approach allows for greater flexibility and scalability, making it an ideal platform for complex scientific simulations.
One such application is the Mainframe subnet (SN25) of Macrocosmos, a mesh of Bittensor subnets established in 2024. SN25 is specifically designed to lower the cost of protein folding simulations, a critical aspect of drug discovery. It employs the GROMACS standard for protein folding simulations but integrates this into a competitive design that incentivizes miners to develop machine-learning models that solve protein folding as efficiently as possible.
The network is split into miners, validators, and stakers of the TAO token. Miners provide "intelligence," validators check their results and vote on them, and stakers elect validators. The system is similar to election-based consensus mechanisms like Ripple's or Proof of Authority such as Binance Smart Chain, where peers in a network vote for consensus and rate each other's trustworthiness.
Validators in the system check miners' outputs using specific heuristics, and the miners who perform best receive tokens from Bittensor-TAO as a reward. Bittensor rewards honest selection of weights as much as possible, making the system resistant to collusion up to 50% of the network's total weight.
The Bittensor blockchain is also being leveraged by a research startup aiming to accelerate the discovery of new drugs. Artificial intelligence and molecular simulations can streamline and enhance the drug development process by simulating compounds in computers instead of developing and testing them physically.
Another project, Rowan Labs, has launched a specialized neural network called Egret-1 for simulating chemical reactions at the atomic level. Egret-1 aims to improve the resource-intensive process of simulating chemical reactions by using quantum mechanical equations. This neural network is decentralized via the Bittensor (TAO) blockchain.
Egret-1, along with the protein folding simulations in SN25, underscores the potential of Bittensor to revolutionize drug discovery. However, to be successful, these projects require "much more high-quality data generated through density functional theory (DFT)".
Moreover, Bittensor's marketplace, the Yuma Consensus, pays for services like machine intelligence, protein folding, data storage, model training, etc., to be made available to the network. This marketplace model further cements Bittensor's role as a catalyst for scientific advancement and drug discovery.
While the exact implementation of the system in the whitepaper is complex and full of mathematical formulas, the potential benefits are clear: a faster, more efficient, and decentralized approach to drug discovery that could potentially save countless lives. The founders of Macrocosmos, a subnet within the Bittensor blockchain, remain undisclosed, adding an air of mystery to this promising venture.
In conclusion, Bittensor is poised to revolutionize the drug discovery process by harnessing the power of decentralized AI and protein folding simulations. As more high-quality data becomes available and more projects leverage this innovative blockchain, we may witness a new era in scientific research and drug development.
