QBT Quantum Blockchain Technologies Plc

 
TIDMQBT 
 
18 August 2021 
 
                      Quantum Blockchain Technologies Plc 
                           ("QBT" or "the Company") 
 
                       Crypto Mining R&D Project Update 
 
The board of Quantum Blockchain Technologies (AIM: QBT) is pleased to update 
the market on its Crypto Mining Research and Development ("R&D") project, which 
in the first instance will be used for the deployment of a proprietary 
technology for more efficient cryptocurrency mining. 
 
The primary goal of the project is to develop Bitcoin mining tools and 
techniques which will significantly outperform existing mining equipment, both 
in speed and energy consumption. While it is understood that this is extremely 
ambitious, the radically advanced technologies being utilised; quantum 
computing, Artifical Intelligence and Deep Learning, amongst others, renders 
the goal achievable. 
 
For this purpose, QBT has assembled a team of 13 sector experts, which is now 
fully operational. The members of the team have been selected from across the 
UK and Italy, and includes highly skilled professionals, Ph.D students and 
university professors, with expertise in, Quantum Computing, Machine Learning, 
Cryptography and Algorithms Optimisation Theory. QBT has entered into formal 
agreements with various university departments to retain the services of the 
new team. Any intellectual property and patents developed during the R&D 
project will belong exclusively to QBT. 
 
A number of working groups have been formed to address the key technologies at 
the core of QBT's crypto mining strategy. These are: 
 
  * Quantum Computing 
 
  * Cryptographic Optimisation 
 
  * Deep Learning and Artificial Intelligence ("AI") 
 
  * FPGA / ASIC Design 
 
  * Algebraic and Boolean Equation Reduction 
 
  * Very Large Big Data 
 
  * High performance computing architectures 
 
As previously stated in the RNS of 2 June 2021, the Company has secured the 
services of an expert specialising in cryptocurrency mining blockchain 
optimisations. 
 
The development of only half of the optimisations previously created by the 
expert, has proved a 9.56% speed improvement using a commercial Graphic 
Processing Unit (GPU), compared to the standard Bitcoin mining algorithm on the 
same GPU. While it was never intended to use a GPU processor for Bitcoin 
mining, it is providing invaluable quantitative feedback on the optimisation 
techniques discovered by the in-house expert. 
 
A second and more impactful set of optimisations for the Bitcoin mining 
algorithm have now been identified by the expert, which will be filed as an 
international patent within weeks. This is ideally the first of several patents 
the Company plans to file in the coming months. More details on the efficiency 
in running the Bitcoin mining algorithm with this new set of optimisations, 
will be released shortly after filing the patent. 
 
The Field Progammable Gate Arrays ("FPGA") and Application Specific Integrated 
Circuit ("ASIC") expert retained by the Company will start implementing the 
first set of optimisations on FPGA this month and early completed versions of 
the FPGA are due by the end of October 2021, while the optimisations covered by 
the patent being filed are due by December 2021. Based on the performance 
achieved by the FPGA chip, it may be decided to use it as the Company's first 
mining engine. ASIC development work will start in parallel in October 2021. 
 
The design of the new IT infrastructure, which includes a 128 core Machine 
Learning workstation and an initial one Petabyte memory expandable unit, to 
host the proprietary enriched Bitcoin mining "Very Large Big Data", is now 
complete and its deployment into a data centre in Northern Italy will, due to 
favourable tax benefits on R&D, happen in September 2021. To date, all R&D has 
been completed using cloud resources. 
 
At the beginning of August 2021, the first Deep-Learning optimisation of the 
Bitcoin mining algorithm was autonomously generated by one of QBT's AI systems. 
This optimisation is identical to one of the phase-one optimisations created by 
the expert, but generated independently. This early result strongly supports 
the strategy adopted by the Company to invest in the heavy use of Deep 
Learning. 
 
Work on the D-Wave quantum computer has begun by QBT's quantum team. While an 
implementation of the core Bitcoin mining algorithm has already been developed, 
programming of this quantum processor requires a totally different approach to 
traditional software design. This is due to the specific approach to quantum 
computing of D-Wave's quantum processor, namely, quantum annealing. However, 
the efforts represented by the very steep initial learning curve, will 
hopefully, be rewarded by the significantly improved performance expected to be 
delivered by D-Wave's quantum processor. Updates on progress achieved will be 
released in due course. 
 
Francesco Gardin, CEO and Executive Chairman of QBT, commented, "Assembling a 
new team and taking this project to operational status within four months has 
been a difficult challenge and has required a tremendous effort. However, 
thanks to our exceptional team, we have been able to achieve this. 
 
"Over the past few months we have resisted the temptation to mine for 
cryptocurrencies using 'standard' methods as it is not part of our current 
strategy. QBT is looking to be a highly disruptive influence in the circa £75 
billion* market of  approximately 2.21m Bitcoins yet to be mined and we believe 
that the past few months of intensive R&D will be crucial to achieving this. 
Our strategy for Bitcoin mining is knowledge intensive, rather than capital 
intensive, based on the unique, combined interaction between our human experts 
and our innovative AI systems. 
 
"I would like to thank our shareholders for their patience and state that our 
roadmap is clearly defined and we will pursue it with determination." 
 
* at the current market price of US$46,400 per Bitcoin 
 
This announcement contains inside information for the purposes of Article 7 of 
the Market Abuse Regulation (EU) 596/2014 as it forms part of UK domestic law 
by virtue of the European Union (Withdrawal) Act 2018 ("MAR"), and is disclosed 
in accordance with the Company's obligations under Article 17 of MAR. 
 
                                    -ends- 
 
For further information please contact: 
 
Quantum Blockchain Technologies Plc 
Francesco Gardin, CEO and Executive Chairman          +39 335 296573 
 
 
SP Angel Corporate Finance 
(Nominated Adviser & Broker)                          +44 (0)20 3470 0470 
Jeff Keating 
 
 
Leander (Financial PR)                                +44 (0) 7795 168 157 
Christian Taylor-Wilkinson 
 
 
About Quantum Blockchain Technologies Plc 
 
QBT (AIM: QBT) is an AIM listed investment company which has recently realigned 
its strategic focus to technology related investments, with special regard to 
Quantum computing, Blockchain, Cryptocurrencies and AI sectors.  The Company 
has commenced an aggressive R&D and investment programme in the dynamic world 
of Blockchain Technology, which includes cryptocurrency mining and other 
advanced blockchain applications. 
 
For further information, please visit, www.quantumblockchaintechnologies.co.uk 
 
Glossary of Terms: 
 
 
Deep Learning:  Deep learning is an artificial intelligence (AI) function that 
imitates the workings of the human brain in processing data and creating 
patterns for use in decision making. Deep learning is a subset of machine 
learning in artificial intelligence that has networks capable of learning 
unsupervised from data that is unstructured or unlabeled. Also known as deep 
neural learning or deep neural network. 
 
FPGA:  A field-programmable gate array is an integrated circuit designed to be 
configured by a customer or a designer after manufacturing - hence the term 
"field-programmable". The FPGA configuration is generally specified using a 
hardware description language (HDL), similar to that used for an 
application-specific integrated circuit (ASIC). 
 
ASIC: An application-specific integrated circuit is an integrated circuit chip 
customized for a particular use, rather than intended for general-purpose use. 
ASIC chips are typically fabricated using metal-oxide-semiconductor (MOS) 
technology, as MOS integrated circuit chips. 
 
GPU: A graphics processing unit is a specialized electronic circuit designed to 
rapidly manipulate and alter memory to accelerate the creation of images in a 
frame buffer intended for output to a display device. GPUs are used in embedded 
systems, mobile phones, personal computers, workstations, and game consoles. 
 
Big Data: Big data refers to the large, diverse sets of information that grow 
at ever-increasing rates. It encompasses the volume of information, the 
velocity or speed at which it is created and collected, and the variety or 
scope of the data points being covered (known as the "three v's" of big data). 
Big data often comes from data mining and arrives in multiple formats. 
 
Quantum annealing (QA): is a metaheuristic for finding the global minimum of a 
given objective function over a given set of candidate solutions, by a process 
using quantum fluctuations. Quantum annealing is used mainly for problems where 
the search space is discrete with many local minima; such as finding the ground 
state of a spin glass or the traveling salesman problem. 
 
 
 
END 
 
 

(END) Dow Jones Newswires

August 18, 2021 02:00 ET (06:00 GMT)

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