Business
Update on Bitcoin R&D
Update on Bitcoin R&D.
About this update from Quantum Blockchain Technologies Plc
[{"type":"text","content":"\n \n 15 November 2022\n \n Quantum Blockchain Technologies Plc\n \n( “QBT” or “the Company”)\n \n R&D\n U\n pdate\n \n The board of Quantum Blockchain Technologies (AIM: QBT) is pleased to update the market with the latest advances by its research and development (“R&D”) team, which is working at developing proprietary methods to create cheaper, faster and more energy efficient Bitcoin (“BTC”) miners.\n Highlights\n \n Preliminary results of Machine Learning Method “B” indicating 30% improvement over commercially available ASIC chip-based miners,\n Regularities identified within the SHA-256 algorithm mark progress towards potential patent filing\n Investigating potential of third-party licensing strategy to exploit early revenues\n Appointment of Dr. Rita Pizzi as Chief Research Officer\n \n Machine Learning and AI\n The first results obtained by two of the Company's three Machine Learning (ML) groups in respect of the development of the Company’s first two knowledge-based algorithms (described in the Company’s RNS dated 23 May 2022 as Method “A\" and Method “B\"), relate to a prototype proprietary software accelerator for BTC mining, which is now in a position to undergo intensive testing.\n The computational requirements to validate both Method A and Method B by testing at the current level of difficulty of BTC extraction are very challenging. The Company has not ruled out the use of a supercomputer for such tests, but a more pragmatic approach in the short term is based on the use of existing market-available ASIC miners. The Company has already acquired a number of ASIC miners with the intention that the control software on the ASIC miners will be replaced by QBT’s own proprietary software, based on Method B.\n Additional miners will be acquired to test the performance of both Method A and Method B at the current mining difficulty.\n Interesting preliminary laboratory results have been achieved to date with Method B, which is based on two different combined ML methods, indicating a statistical improvement of up to 30% over existing commercially available ASIC chip-based BTC miners. That is, regardless of the performance of the ASIC chip used by the miner, the Company's proprietary software could statistically still increase mining speeds by up to 30%, whilst not impacting the miner’s power consumption.\n Provided th...