MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"),
a technology service provider, announced the development of a
neural network-based quantum-assisted unsupervised data clustering
technology, utilizing a hybrid quantum-classical algorithm
framework. This framework integrates the classical self-organizing
feature map (SOM) neural network with the powerful capabilities of
quantum computing, enabling efficient data clustering in an
unsupervised manner.
The Self-Organizing Feature Map (SOM) is an
unsupervised learning neural network model widely used in fields
such as data clustering, dimensionality reduction, and data
visualization. Its core concept involves mapping high-dimensional
data from the input space to a low-dimensional topological space
through a competitive learning algorithm. This process ensures that
similar input data points are mapped to adjacent neurons, thereby
achieving data clustering.
In classical computing, the SOM algorithm
continuously adjusts weight vectors to reasonably group input data
within the feature space. However, when dealing with massive
datasets, the traditional SOM algorithm faces challenges related to
computational complexity and storage demands.
To address the limitations of classical
computing in large-scale data clustering, HOLO has introduced
quantum computing into the SOM framework, developing a
Quantum-Assisted Self-Organizing Feature Map (Q-SOM) model. In this
model, the powerful parallel computing capabilities of quantum
computing are leveraged to accelerate the weight adjustment and
data point mapping processes in SOM. Through quantum parallelism,
it becomes possible to process a larger volume of data in a shorter
time, thereby reducing the number of computations and overall time
consumption.
HOLO's technology leverages the quantum
superposition and quantum entanglement properties of quantum
computing, enabling the results of each clustering computation to
be processed in parallel across multiple qubits. This quantum
parallel computing approach not only significantly enhances
computational efficiency but also demonstrates superior
computational power compared to classical computing in certain
scenarios.
HOLO believes that quantum computing does not
entirely replace classical computing but rather works in tandem
with it. In this technology, the quantum component is primarily
responsible for accelerating the data point mapping and weight
adjustment processes within the SOM network, while the classical
component handles post-processing of results and the final
decision-making for data clustering. This hybrid architecture fully
exploits the respective strengths of quantum and classical
computing, theoretically enabling more efficient clustering.
By incorporating quantum computing, each
iteration of the SOM network can be completed more quickly,
significantly reducing the number of computations required during
the clustering process. Furthermore, the interference properties
and noise tolerance of quantum computing provide additional
robustness and reliability to the model.
HOLO’s neural network-based quantum-assisted
unsupervised data clustering technology, leveraging the advantages
of quantum computing, exhibits significant technical strengths:
Computational Efficiency: Through quantum
parallelism, it can significantly reduce the time cost of
clustering computations. Particularly when dealing with large-scale
data, quantum computing can handle more data points and quickly
converge to optimal solutions.
Data Processing Capability: The quantum-assisted
algorithm can process higher-dimensional data. Especially when
tackling complex high-dimensional datasets, quantum computing
accelerates the data mapping process, reducing the complexity of
high-dimensional computations.
Accuracy and Stability: Compared to classical
methods, quantum computing demonstrates higher accuracy and
stability in addressing certain nonlinear and highly complex
problems. Through quantum entanglement and superposition effects,
it can avoid some of the local optima issues encountered in
classical algorithms.
Wide Applicability: This technology is not only
suitable for data clustering but can also be extended to various
fields such as image processing, natural language processing, and
financial data analysis. As quantum computing technology advances,
more industry applications will become feasible in the future.
The integration of quantum computing and machine
learning marks the advent of next-generation computing technology.
By developing quantum-assisted neural network technology, HOLO not
only achieves breakthroughs in the field of data clustering but
also drives progress across multiple industries. Particularly in
areas such as big data, artificial intelligence, and financial
technology, the introduction of quantum computing will
fundamentally transform data processing methods and provide new
solutions for tackling complex problems.
In the future, as quantum computing technology
continues to mature, quantum-assisted machine learning algorithms
will play an increasingly important role across multiple
industries. Especially in fields with extremely high demands for
computational speed and precision—such as quantum supremacy
experiments, drug discovery, and climate change prediction—the
integration of quantum computing and machine learning will unlock
unprecedented potential.
HOLO’s breakthrough in neural network-based
quantum-assisted unsupervised data clustering technology provides
new perspectives for interdisciplinary research in quantum
computing and artificial intelligence. With ongoing technological
optimization and advancements in quantum computing hardware,
quantum computing is poised to achieve practical applications in a
broader range of fields, driving technological innovation and
societal progress. Through continuous development and application
of this technology, HOLO will inject new momentum into global data
analysis, decision-making support, and the advancement of
artificial intelligence.
About MicroCloud Hologram Inc.
MicroCloud is committed to providing leading
holographic technology services to its customers worldwide.
MicroCloud’s holographic technology services include high-precision
holographic light detection and ranging (“LiDAR”) solutions, based
on holographic technology, exclusive holographic LiDAR point cloud
algorithms architecture design, breakthrough technical holographic
imaging solutions, holographic LiDAR sensor chip design and
holographic vehicle intelligent vision technology to service
customers that provide reliable holographic advanced driver
assistance systems (“ADAS”). MicroCloud also provides holographic
digital twin technology services for customers and has built a
proprietary holographic digital twin technology resource library.
MicroCloud’s holographic digital twin technology resource library
captures shapes and objects in 3D holographic form by utilizing a
combination of MicroCloud’s holographic digital twin software,
digital content, spatial data-driven data science, holographic
digital cloud algorithm, and holographic 3D capture technology. For
more information, please visit http://ir.mcholo.com/
Safe Harbor Statement
This press release contains forward-looking
statements as defined by the Private Securities Litigation Reform
Act of 1995. Forward-looking statements include statements
concerning plans, objectives, goals, strategies, future events or
performance, and underlying assumptions and other statements that
are other than statements of historical facts. When the Company
uses words such as “may,” “will,” “intend,” “should,” “believe,”
“expect,” “anticipate,” “project,” “estimate,” or similar
expressions that do not relate solely to historical matters, it is
making forward-looking statements. Forward-looking statements are
not guarantees of future performance and involve risks and
uncertainties that may cause the actual results to differ
materially from the Company’s expectations discussed in the
forward-looking statements. These statements are subject to
uncertainties and risks including, but not limited to, the
following: the Company’s goals and strategies; the Company’s future
business development; product and service demand and acceptance;
changes in technology; economic conditions; reputation and brand;
the impact of competition and pricing; government regulations;
fluctuations in general economic; financial condition and results
of operations; the expected growth of the holographic industry and
business conditions in China and the international markets the
Company plans to serve and assumptions underlying or related to any
of the foregoing and other risks contained in reports filed by the
Company with the Securities and Exchange Commission (“SEC”),
including the Company’s most recently filed Annual Report on Form
10-K and current report on Form 6-K and its subsequent filings. For
these reasons, among others, investors are cautioned not to place
undue reliance upon any forward-looking statements in this press
release. Additional factors are discussed in the Company’s filings
with the SEC, which are available for review at www.sec.gov. The
Company undertakes no obligation to publicly revise these
forward-looking statements to reflect events or circumstances that
arise after the date hereof.
ContactsMicroCloud Hologram Inc.Email:
IR@mcvrar.com
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