SHENZHEN, China, March 13,
2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or
"MicroAlgo") (NASDAQ: MLGO), today announced that their
research team has used quantum neural networks to classify and
extract features from data in databases, focusing the search space
on subsets that are more likely to contain the target. By
leveraging feature extraction and pattern recognition techniques in
quantum machine learning, they preprocess and filter the features
of the database in advance, narrowing down the search range.
Grover's algorithm is then applied for precise searching, thereby
improving search efficiency.
Quantum Neural Networks, an emerging technology that combines
the principles of quantum mechanics with the architecture of
artificial neural networks, are capable of running complex learning
algorithms on quantum bits, enabling high-speed data processing and
optimization analysis. By simulating the neural network structure
of the human brain and integrating quantum superposition and
entanglement states, they achieve nonlinear data mapping and
advanced abstraction, significantly enhancing the efficiency of
pattern recognition and classification.
MicroAlgo's Quantum Neural Network-based intelligent search
system follows a sophisticated process framework, ensuring
effective data filtering and efficient processing.
Data Preprocessing: Using advanced quantum pattern
recognition technology, the raw data is initially filtered to
remove irrelevant information, extract core features, and form a
dataset that is easy to index.
Feature Extraction: Leveraging the deep learning
capabilities of quantum neural networks, the system automatically
uncovers hidden correlations within the data, constructing
multi-level feature representations to lay the foundation for
subsequent searches.
Subset Focusing: Based on the preliminary feature
analysis, the search space is finely segmented to identify
potential subsets where the target is likely to be, significantly
reducing unnecessary computations.
Applying Grover's Algorithm: For the preselected subsets,
Grover's algorithm is directly employed, utilizing its quantum
parallel search advantages to quickly locate the target and achieve
efficient retrieval.
Result Feedback and Optimization: For each search result,
the system automatically evaluates its effectiveness, optimizes the
search strategy, and iteratively improves the quantum neural
network model, continuously enhancing both accuracy and
efficiency.
Thanks to the quantum parallel processing mechanism, the quantum
neural network intelligent search developed by MicroAlgo
outperforms conventional algorithms by a significant margin,
especially in the context of big data, where the performance gap
becomes even more pronounced. With the support of deep learning
technologies, the system has a more profound understanding of the
data, enabling it to identify targets with greater accuracy and
avoid missed detections or false positives. The combination of
quantum neural networks and Grover's algorithm enhances
adaptability, making the search system capable of self-learning,
automatically adjusting search strategies with data changes, and
maintaining long-term effectiveness.
The integration of quantum neural networks with Grover's
algorithm has broad application prospects. In the field of database
search, this technology can significantly improve search
efficiency, reduce search costs, and bring revolutionary changes to
database management. Additionally, this technology can also be
applied in areas such as big data analysis, information security,
and bioinformatics, offering new solutions for data processing and
analysis in these fields.
In the future, as quantum technology continues to mature,
MicroAlgo is expected to further expand the application boundaries
of this technology, such as integrating it with more emerging
technologies to create a completely new paradigm for intelligent
data analysis. The steady increase in the number of quantum bits
and the continuous improvement in computational precision will help
solve more complex and challenging real-world problems, leading
data processing and search technologies to new heights and deeply
empowering various industries.
About MicroAlgo Inc.
MicroAlgo Inc. (the "MicroAlgo"), a Cayman
Islands exempted company, is dedicated to the development and
application of bespoke central processing algorithms. MicroAlgo
provides comprehensive solutions to customers by integrating
central processing algorithms with software or hardware, or both,
thereby helping them to increase the number of customers, improve
end-user satisfaction, achieve direct cost savings, reduce power
consumption, and achieve technical goals. The range of
MicroAlgo's services includes algorithm optimization,
accelerating computing power without the need for hardware
upgrades, lightweight data processing, and data intelligence
services. MicroAlgo's ability to efficiently deliver software and
hardware optimization to customers through bespoke central
processing algorithms serves as a driving force for MicroAlgo's
long-term development.
Forward-Looking Statements
This press release contains statements that may constitute
"forward-looking statements." Forward-looking statements are
subject to numerous conditions, many of which are beyond the
control of MicroAlgo, including those set forth in the Risk Factors
section of MicroAlgo's periodic reports on
Forms 10-K and 8-K filed with the SEC. Copies are
available on the SEC's website, www.sec.gov. Words such as
"expect," "estimate," "project," "budget," "forecast,"
"anticipate," "intend," "plan," "may," "will," "could," "should,"
"believes," "predicts," "potential," "continue," and similar
expressions are intended to identify such forward-looking
statements. These forward-looking statements include, without
limitation, MicroAlgo's expectations with respect to future
performance and anticipated financial impacts of the business
transaction.
MicroAlgo undertakes no obligation to update these statements
for revisions or changes after the date of this release, except as
may be required by law.
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SOURCE Microalgo.INC
