New Bitcoin-mining hardware may increase mining profits by 30%, claims the Indian scientist, Rakesh Kumar. The core concept of the machine is to capitalize on the limitations of existing mining equipment by detecting false positives and mitigating error propagation.
Mining Bitcoin requires a substantial amount of electricity and computing power. Leading mining firms and miners often utilize expensive mining hardware such as ASIC (Application-specific integrated circuit) chips to mine blocks of transactions . Bitcoin mining more difficult
However, the mining difficulty of the BitcoinCT r: 8 network has surged at a rapid pace over the past few months, making it much more difficult for miners with expensive equipment and sophisticated mining infrastructure to profit from Bitcoin mining .
Recently, Bitcoin mining difficulty reached 163,491,654,908.95925903 , recording a 13.44% increase from its previous rise. With that being said, Bitcoin blocks have become 163 billion times more difficult to mine than the minimum difficulty of 1 back in January 2009. As Bitcoin-mining continues to increase in difficulty and create competition within the Bitcoin-mining community , miners have begun to struggle to keep up with the big players in the industry which operate mining establishments in colder regions, including Iceland and Georgia. Since these mining firms use the colder temperatures in their regions to cool down their mining equipment naturally, they have a significant advantage over other miners and mining firms operating in warmer regions such as Asia and South America.
Earlier in February, a group of scientists and researchers, led by Indian scientist Rakesh Kumar, recognized this issue with Bitcoin-mining and introduced a new Bitcoin-mining hardware called “Approximate Hardware.”
According to Kumar’s report, this machine improves the Bitcoin-mining process and increases mining profits potentially by 30%.
“We exploit this inherent tolerance to inaccuracy by proposing approximate mining circuits that trade off reliability with area and delay. […]
