The Advanced NLP (Natural Language Processing) capabilities enhance the human-to-computer interaction experience, capable of making it significantly more user-friendly, mainly intuitive.
SAN DIEGO, Jan. 27, 2022 (GLOBE NEWSWIRE) — GBT Technologies Inc. (OTC PINK: GTCH) (“GBT”, or the “Company”), is evaluating the use of an advanced NLP algorithm model to enhance its AI-based healthcare advisory system human interaction experience. The Text-To-Text Transfer Transformer (T5) model introduces an efficient technology to perform a wide variety of supervised Natural Language Processing (NLP) tasks such as classification, Q&A, and summarization.
Typically, most of the new deep learning NLP models are very large and include a vast number of parameters. Normally the larger the NLP model, the more learning capacity it has, yet one of the main disadvantages is the huge dataset which may reduce the overall performance. The advanced NLP algorithm model is considered one of the most advanced, high-performance NLP algorithms that include a vast number of parameters, use significantly less memory, and provide high accuracy. GBT will be evaluating the T5, pre-trained model with the goal of using it in its Hippocrates healthcare advisory system, handling Q/A, text, summarization, and compositional commonsense knowledge.
The model allows more parallel processing than methods like Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) which significantly increases data understanding and reasoning capabilities. For example, T5 model is capable of processing words together rather than on a word-by-word of a given text. As the global data realm is estimated to reach the zettabytes range in the near future, our deep learning computing will need powerful processing capabilities, comprehending and scrutinizing data, particularly in the huge, unstructured NLP domain. The system is designed to perform as a general health Q/A advisory system, providing the first-line of health-related advice. We plan to further develop the system to include intelligent telemedicine capabilities that will assist patients and healthcare specialists through globally connected devices.
“Natural Language Processing (NLP) is currently broadly used for the various tasks involving sentiment analysis, for example, spam email detection, textual/voice-driven virtual assistants, chatbots, and similar.
In the last decade, deep learning technology has become more powerful, allowing larger data and faster processing models to handle the constantly growing unstructured data. The amount of unstructured data has become a challenge for information analysis, especially within the NLP arena due to compositional complexity and the demand for a human-like interaction. Today’s voice and text digital assistants are expected to efficiently “understand” verbal or textual conversations, exactly as an in-person interaction.
Artificial General Intelligence (AGI) is our machine learning solution to “understand” the data, reason, and make decisions exactly as a human would do. One of the key challenges for such a system is to comprehend human’s natural language, interpret, and manipulate it, which is exactly what NLP is. Our Avant! deep neural networks already encapsulate vast computing power, allowing larger language models with faster processing. We are seeking new capabilities by combining new NLP models with our current technology to better “understand” users, their intent, and provide accurately, well summarized, responses.
We are evaluating if the possible implementation of the T5 model within our Hippocrates healthcare AI system may produce a much more robust level of user’s chat interaction with more human-like dialog, mainly intuitive. The Hippocrates healthcare advisory system is aimed to provide first-line health-related advice and to become an assisting tool for the general population and healthcare professionals. Its human interaction aspect, via a robust NLP technology, is one of the most important features to ensure viable and accurate health-related advice information” provided 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, developed, and granted regulatory approval, 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: GTCH) (“GBT”) ( https://gbtti.com ) is a development stage company that 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 technical expertise and is building an intellectual property portfolio consisting of many patents. GBT’s mission is 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 any and 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 as a result 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
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