REG-Quantum Blockchain Technologies Plc: Update on ASIC Manufacturer AI Oracle Test

Quantum Blockchain TechnologiesAnnouncement

Yesterday 07:02

8 April 2026

 

Quantum Blockchain Technologies Plc                    
          (          “          QBT” or           “          the
Company”)

 

 

Update on ASIC Manufacturer AI Oracle Test

 

Quantum Blockchain Technologies plc (AIM: QBT), the AIM-listed investment
company, is pleased to announce that it has found a way to accelerate the live
testing of its Method C AI Oracle software on the mining rig of the ASIC
manufacturer, the loan of which QBT announced on 6 March 2026. This work
around is expected to shorten live-testing timelines and deliver earlier
preliminary results of the AI Oracle which the Company now expects to receive
by the end of April 2026.

 

The approach has been made possible by connecting the AI Oracle directly to
the ASIC manufacturer’s Mining Development Kit (“MDK”) thereby avoiding
the time-consuming process of fully integrating the AI Oracle onto the mining
rig.

 

The use of the MDK circumnavigates the need to translate and optimise the AI
Oracle for the ASIC control board which, whilst feasible, is a time consuming
task. Instead, QBT has succeeded in modifying the CGminer-like operating
system of the ASIC manufacturer’s rig to intercept all incoming mining jobs
from the mining pool which are then passed to the AI Oracle with the result
that only the best hashes are executed thereby enabling more efficient Bitcoin
mining.

 

The ASIC manufacturer’s CGminer-like operating system has already been
successfully tested on an Intel x86 family server in the Company’s Milan
University laboratory and by its Oregon development team. This process
bypasses the activities normally performed on the rig’s hashboards; instead
replicating them via a cable connected directly to the server.

 

Data collection from the mining rig has started at QBT’s Milan laboratory.
When the minimal critical mass of data has been generated, the training of the
neural networks will begin, followed by the generation of the AI software
model specific to the ASICs on the third-party’s hashboard.

 

Notwithstanding the accelerated process’ successful implementation, the
objective of deployment of the AI Oracle onto the mining rig remains a key
objective and the Company will be running a parallel project to also achieve
this aim.

 

 

Francesco Gardin, CEO and Executive Chairman of QBT, commented                
   , “Connecting the AI Oracle directly to the hashboard of the MDK enables
QBT’s development team to start live-testing immediately once the new AI
Oracle is generated from the data collected from the mining rig. Moreover, we
also believe that this solution will speed up our internal testing on the
Antminer S9 and the Bitaxe Gamma mining rigs, which are both additional
targets for the Company’s future customer demonstrations.

 

“I am, therefore, extremely pleased that this development shortcut will
potentially allow QBT to provide its preliminary results earlier than
expected.”

 

 

 

For further information please contact:

 

Quantum Blockchain Technologies Plc                               +39 335
296573

Francesco Gardin, CEO and Executive Chairman

 

SP Angel Corporate Finance                               (Nominated Adviser &
Broker)                     +44 (0) 20 3470 0470

Caroline Rowe / Devik Mehta

 

Leander                                                    (Financial PR)    
                +44 (0) 7795 168 157

Christian Taylor-Wilkinson

 

 

About Quantum Blockchain Technologies Plc

 

QBT (AIM: QBT) is a London Stock Exchange AIM listed Research & Development
and investing company focused on an intensive R&D programme to disrupt the
Blockchain Technologies sector which includes, cryptocurrency mining and other
advanced blockchain applications. The primary goal of the R&D programme is to
develop Bitcoin mining tools and techniques, via its technology-driven
approach, which the Company believes will significantly outperform existing
market practices.



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