GBT is Implementing Machine
Learning Driven, Pattern Matching Technology for its Epsilon,
Microchip Reliability Verification and Correction EDA
Tool
SAN
DIEGO, CA -- September 1, 2022 -- InvestorsHub NewsWire -- GBT
Technologies Inc. (OTC PINK: GTCH ) ("GBT"
or the "Company"), is implementing a machine learning driven,
pattern matching technology within its Epsilon, microchip's
reliability verification and correction Electronic Design
Automation (EDA) tool. Design rules are getting increasingly
complex with each new process node and design firms are facing new
challenges in the physical verification domain. One of the major
areas that are affected by the process physics, is reliability
Verification (RV). Microchips are major components nearly in every
major electronics application. Civil, military and space
exploration industries require reliable operations for many years,
and in severe environments. High performance computing systems
require advanced processing with high reliability to ensure the
consistency and accuracy of the processed data. Complex integrated
circuits are in the heart of these systems and need to function
with high level of dependability. Particularly in the fields of
medicine, aviation, transportation, data storage and industrial
instrumentation, microchip's reliability factor is crucial. GBT is
implementing new machine learning driven, pattern matching
techniques within its Epsilon system with the goal of addressing
the advanced semiconductor's physics, ensuring high level of
reliability, optimal power consumption and high performance.
As Epsilon analyzes the layout of an integrated circuit (IC),
it identifies reliability weak spots, which are specific regions of
an IC's layout, and learns their patterns. As the tool
continues analyzing the layout it records problematic zones taking
into account the pattern's orientations and placements. In
addition, it is designed to understand small variations in
dimensions of the pattern, as specified by the designer or an
automatic synthesis tool. As the weak spots are identified, the
tool will take appropriate action to modify and correct them. A
deep learning mechanism will be performing the data analysis,
identification, categorization, and reasoning while executing an
automatic correction. The Machine Learning will understand the
patterns and record them in an internal library for future use.
Epsilon's pattern matching technology will be analyzing the
chip's data according to a set of predefined and
learned-from-experience rules. Its cognitive capabilities will make
it self-adjust to newest nodes with new constraints and challenges,
with the goal of providing quick and reliable verification and
correction of an IC layout.
The Company
released a video which explain the potential functions of the
Epsilon tool: https://youtu.be/Mz4IOGRHeqw
"The
ability to analyze and address advanced IC's reliability parameters
is necessary to mitigate risk of system degradation, overheating,
and possible malfunction. It can affect microchip's performance,
power consumption, data storage and retrieval, heat and an early
failure which may be critical in vital electronic systems. Epsilon
analyzes a microchip data for reliability, power and electrothermal
characteristics, and performs auto-correction in case violations
found. We are now implementing an intelligent technology for
Epsilon with the goal of utilizing pattern matching algorithms to
formulate a smart detection of reliability issues within integrated
circuits layout. The new techniques will analyze and learn weak
spots within microchip's data, predicting failure models that are
based on the process' physics and electrical constraints knowledge.
It will take into consideration each device's function,
connectivity attributes, electrical currents information,
electrothermal factors and more to determine problematic spots and
perform auto-correction. Particularly for FinFet and GAA FET (Gate
All Around FET) technologies, a device's functionality is developed
with major reliability considerations ensuring power management
efficiency, optimal thermal analysis aiming for long, reliable life
span. Using smart pattern matching methods, we plan to improve
reliability analysis, achieving consistency and accuracy across
designs within advanced manufacturing processes. As
dimensions of processes shrink, IC's layout features become much
more complex to analyze for electrical phenomenon. To provide an
intelligent answer for these complexities, we are implementing deep
learning-based pattern matching technology with the goal of
ensuring efficient, 'green' microchip's power consumption, higher
performance, optimized thermal distribution, and ultimately
superior reliability" stated Danny Rittman, the Company's CTO.
There
is no guarantee that the Company will be successful in researching,
developing or implementing this system. In order to
successfully implement this concept, the Company will need to raise
adequate capital to support its research and, if successfully
researched and fully developed, the Company would need to enter
into a strategic relationship with a third party that has
experience in manufacturing, selling and distributing this
product. There is no guarantee that the Company will be
successful in any or all of these critical steps.
About Us
GBT
Technologies, Inc. (OTC
PINK: GTCHD) ("GBT") (http://gbtti.com)
is a development stage company which considers itself a native of
Internet of Things (IoT), Artificial Intelligence (AI) and Enabled
Mobile Technology Platforms used to increase IC performance. GBT
has assembled a team with extensive technology expertise and is
building an intellectual property portfolio consisting of many
patents. GBT's mission, to license the technology and IP to
synergetic partners in the areas of hardware and software. Once
commercialized, it is GBT's goal to have a suite of products
including smart microchips, AI, encryption, Blockchain, IC design,
mobile security applications, database management protocols, with
tracking and supporting cloud software (without the need for GPS).
GBT envisions this system as a creation of a global mesh network
using advanced nodes and super performing new generation IC
technology. The core of the system will be its advanced microchip
technology; technology that can be installed in any mobile or fixed
device worldwide. GBT's vision is to produce this system as a low
cost, secure, private-mesh-network between all enabled devices.
Thus, providing shared processing, advanced mobile database
management and sharing while using these enhanced mobile features
as an alternative to traditional carrier services.
Forward-Looking Statements
Certain
statements contained in this press release may constitute
"forward-looking statements". Forward-looking statements
provide current expectations of future events based on certain
assumptions and include any statement that does not directly relate
to any historical or current fact. Actual results may differ
materially from those indicated by such forward-looking statements
because of various important factors as disclosed in our filings
with the Securities and Exchange Commission located at their
website ( http://www.sec.gov).
In addition to these factors, actual future performance, outcomes,
and results may differ materially because of more general factors
including (without limitation) general industry and market
conditions and growth rates, economic conditions, governmental and
public policy changes, the Company's ability to raise capital on
acceptable terms, if at all, the Company's successful development
of its products and the integration into its existing products and
the commercial acceptance of the Company's products. The
forward-looking statements included in this press release represent
the Company's views as of the date of this press release and these
views could change. However, while the Company may elect to
update these forward-looking statements at some point in the
future, the Company specifically disclaims any obligation to do
so. These forward-looking statements should not be relied
upon as representing the Company's views as of any date subsequent
to the date of the press release.
Contact:
Dr. Danny Rittman,
CTO
press@gopherprotocol.com