Patent information can be utilized in various ways depending on how it is understood. I have devised a method to extract useful insights for the development of new products or services from patents in specific technology fields by using the analysis and cognition capabilities of GPT-4 based ChatGPT. I have applied this to the fields of generative AI, metaverse, and Web3-based fintech.
For the case study, in the generative AI field, I examined Google's patent US10452978 "Attention-based sequence transduction neural networks" (this patent describes the transformer architecture, which is the basis of most large language models (LLMs) for generative AI); in the metaverse field, I looked at Meta's patent US11302063 "3D conversations in an artificial reality environment"; and in the Web3-based fintech field, I explored nChain's patent US10776761 "Virtual currency system."
I input into ChatGPT a guideline consisting of five key steps: identifying the main purpose of the patent invention, summarizing the technological innovations in the patent claims, describing potential products or services based on the technology, identifying the main industry participants, and evaluating competitive advantages. For more details, please refer to the attached file and evaluate the level of results at your discretion.
The outputs generated from the method described can provide valuable insights for various business applications:
Patent licensing promotion: By identifying the main purpose, technological innovations, and potential products or services related to a patent, businesses can better understand the value proposition of their intellectual property. This information can be used to showcase the benefits of the patented technology to potential licensees, making it more appealing for them to enter into licensing agreements. Thus, you can more effectively promote patent licensing.
Finding potential infringement: Summarizing the technological innovations in the patent claims helps businesses clearly understand the scope of their intellectual property protection. By comparing this information with competing products or services in the market, they can identify potential infringement cases and take appropriate legal actions to protect their intellectual property.
M&A target identification: Evaluating competitive advantages and identifying the main industry participants can help businesses spot potential acquisition targets. Companies with complementary technologies, strong market presence, or unique intellectual property could provide strategic opportunities for growth through mergers and acquisitions.
Product or service market fit: Describing potential products or services based on the patented technology can help businesses identify new opportunities for product development or market expansion. By understanding the potential applications and market demand for a particular technology, businesses can better tailor their offerings to meet customer needs.
Presented at All Things Open RTP Meetup
Presented by Karthik Uppuluri, Fidelity
Title: Generative AI
Abstract: In this session, let us embark on a journey into the fascinating world of generative artificial intelligence. As an emergent and captivating branch of machine learning, generative AI has become instrumental in myriad of sectors, ranging from visual arts to creating software for technological solutions. This session requires no prior expertise in machine learning or AI. It aims to inculcate a robust understanding of fundamental concepts and principles of generative AI and its diverse applications. Join us as we delve into the mechanics of this transformative technology and unpack its potential.
OpenAI is an artificial intelligence research laboratory consisting of both non-profit and for-profit entities. It was founded in 2015 with the goal of developing AI that is beneficial to humanity. OpenAI conducts research in machine learning, computer vision, natural language processing, and robotics. Notable projects include ChatGPT, an AI assistant capable of answering questions and generating text. OpenAI makes many of its research findings and models openly available via its API and GitHub.
Research Applications in Artificial Intelligence and Machine LearningRupesh Gupta
The document provides an overview of a faculty development program on research applications in artificial intelligence and machine learning. It discusses the history of AI, the current status of AI applications in industries like healthcare, aviation, education, finance, and heavy industry. It also outlines the building blocks of AI and different types of machine learning models.
ChatGPT (Chat Generative pre-defined transformer) is OpenAI's application that performs human like interactions. GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor. Deck contains more details about ChatGPT, AI, AGI, CoPilot, OpenAI API, and use case scenarios.
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
The 7 Biggest Ethical Challenges of Artificial IntelligenceBernard Marr
Artificial intelligence technology has been a worldwide game-changer for many industries, but it is not without its challenges. In this article, we’ll dig into some of the biggest ethical concerns around AI.
Presented at All Things Open RTP Meetup
Presented by Karthik Uppuluri, Fidelity
Title: Generative AI
Abstract: In this session, let us embark on a journey into the fascinating world of generative artificial intelligence. As an emergent and captivating branch of machine learning, generative AI has become instrumental in myriad of sectors, ranging from visual arts to creating software for technological solutions. This session requires no prior expertise in machine learning or AI. It aims to inculcate a robust understanding of fundamental concepts and principles of generative AI and its diverse applications. Join us as we delve into the mechanics of this transformative technology and unpack its potential.
OpenAI is an artificial intelligence research laboratory consisting of both non-profit and for-profit entities. It was founded in 2015 with the goal of developing AI that is beneficial to humanity. OpenAI conducts research in machine learning, computer vision, natural language processing, and robotics. Notable projects include ChatGPT, an AI assistant capable of answering questions and generating text. OpenAI makes many of its research findings and models openly available via its API and GitHub.
Research Applications in Artificial Intelligence and Machine LearningRupesh Gupta
The document provides an overview of a faculty development program on research applications in artificial intelligence and machine learning. It discusses the history of AI, the current status of AI applications in industries like healthcare, aviation, education, finance, and heavy industry. It also outlines the building blocks of AI and different types of machine learning models.
ChatGPT (Chat Generative pre-defined transformer) is OpenAI's application that performs human like interactions. GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor. Deck contains more details about ChatGPT, AI, AGI, CoPilot, OpenAI API, and use case scenarios.
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
The 7 Biggest Ethical Challenges of Artificial IntelligenceBernard Marr
Artificial intelligence technology has been a worldwide game-changer for many industries, but it is not without its challenges. In this article, we’ll dig into some of the biggest ethical concerns around AI.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
This document provides an overview of Chat GPT, an AI tool launched in November 2022 by OpenAI. It discusses that Chat GPT allows for conversational dialogues and aims to give accurate answers while admitting mistakes. The document notes that Chat GPT was trained on huge amounts of online text data to generate human-like responses. Potential uses of Chat GPT discussed include powering virtual customer service agents, personal assistants, social media moderation, and improving machine translation.
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
As generative AI adoption grows at record-setting speeds and computing demands increase, hybrid processing is more important than ever. But just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices, AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential. In this talk you’ll learn:
• Why on-device AI is key
• Which generative AI models can run on device
• Why the future of AI is hybrid
• Qualcomm Technologies’ role in making hybrid AI a reality
The document discusses the evolution of the internet from static Web 1.0 pages to today's dynamic Web 2.0 and upcoming Web 3.0. It defines the Internet of Things (IoT) as connecting physical objects through sensors and internet connectivity. Examples discussed include connecting devices in homes, cities, healthcare, mining and law enforcement. Challenges of IoT include bandwidth, power consumption, security and data management. Standards organizations are working to address these issues and advance IoT technologies. The future may see an "Internet of Everything" connecting people, processes, data and physical things.
Artificial intelligence (AI) aims to create intelligent machines that can function like humans. AI involves techniques like machine learning and deep learning. AI is used in many applications today including smart assistants, self-driving cars, spam filters, and recommendations. Major companies and countries are investing heavily in AI research and development. Future trends may include greater use of AI in areas like cybersecurity, healthcare, transportation, and combining AI with augmented or virtual reality technologies.
Generative AI for Teaching, Learning and AssessmentMike Sharples
AI is disrupting education. Students, teachers and academics can access software that writes essays, summarises scientific texts, produces lesson plans, engages in conversations, and drafts academic papers. These are already being embedded into office tools and will soon be interconnected into an AI-enhanced social network. I will introduce the capabilities and limitations of current generative AI and discuss how it is transforming education, including emerging policy. I will suggest new roles for AI in supporting teaching, learning and assessment. Rather than seeing AI solely as a challenge to traditional education, we can prepare students for a future where AI is a tool for creativity, to be operated with great care and awareness of its limitations.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
As an AI language model, ChatGPT is a program consisting of a large neural network that has been trained on vast amounts of textual data. Specifically, ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) family of models developed by OpenAI.
This presentation discusses various applications of artificial intelligence technologies including neural networks, fuzzy logic, agents, genetic algorithms, natural language processing, and knowledge-based systems. It provides examples of how each technology has been applied in areas like predicting events, diagnosing cancer, automating decisions, and translating languages. The presentation concludes that while AI is still limited, it has matured into an effective tool that allows for new approaches to problem solving in fields like engineering.
The document discusses generative AI models provided by Microsoft's Azure OpenAI Service. It describes that the service provides access to OpenAI's powerful language models like GPT-3 and Codex which can generate natural language, code, and images. It also mentions that the service allows customizing models with your own data and includes built-in tools for responsible use along with enterprise-grade security controls. Examples of tasks the AI models could perform are provided like answering questions, summarizing text, translating between languages, and generating code from natural language prompts.
This document provides an overview of the history and development of artificial intelligence (AI). It discusses early pioneers like Alan Turing and his proposal of the Turing Test. Key developments include the first AI programs for games in the 1950s, the Dartmouth Conference in 1956 which defined the field, and John McCarthy's creation of the Lisp programming language. The document outlines a variety of applications of AI throughout its history from gaming to robotics to military uses. It concludes by discussing predictions for the future role of AI and its potential to solve major problems and change the world.
This document discusses using artificial neural networks for hand gesture recognition. It introduces gesture recognition and ANNs, describing how ANNs can be used for gesture recognition by being adaptive systems that change structure based on information flow. The document outlines training ANNs using feedforward and backpropagation algorithms in MATLAB for gesture recognition. It also provides steps of the recognition process and discusses advantages like learning without reprogramming and disadvantages like needing training.
This document outlines a syllabus for a course on Internet of Things technology. It discusses several topics that will be covered in Module 4 on data and analytics for IoT, including an introduction to data analytics for IoT, structured versus unstructured data, data in motion versus data at rest, and an overview of descriptive, diagnostic, predictive, and prescriptive analytics. Specific techniques that will be examined include machine learning, big data analytics tools, edge streaming analytics, and network analytics. Examples are provided for each topic to illustrate key concepts relating to analyzing large amounts of IoT sensor data.
The document discusses the development and use of a recruitment chatbot. It proposes that a chatbot could automate many time-consuming recruitment tasks like collecting candidate information, screening, and scheduling interviews. This would help address the challenges of sifting through large numbers of resumes and finding qualified candidates more efficiently. The document outlines the design and implementation of a recruitment chatbot using techniques like neural networks, machine learning, and generative dialogue models. It suggests chatbots could handle initial recruitment stages and free up recruiters to focus on human aspects of the process.
Key Features of mHealth:
Accessibility: mHealth allows users to access health-related information and services anytime and anywhere, making it convenient for both healthcare providers and patients.
Remote Monitoring: With mHealth, patients can monitor their health conditions remotely using wearable devices or mobile apps, enabling real-time data tracking and sharing with healthcare professionals.
Health Education and Awareness: Mobile apps and platforms offer health education materials and raise awareness about various medical conditions, preventive measures, and healthy lifestyles.
Telemedicine: mHealth facilitates telemedicine, where patients can consult with healthcare providers through video calls or messaging services, reducing the need for in-person visits.
Health Data Management: Mobile health applications enable users to store and manage their health data, such as medical records, test results, and medication reminders.
Personalized Health Solutions: mHealth platforms can provide personalized health solutions based on individual health data, promoting targeted interventions and better healthcare outcomes.
Benefits of mHealth:
Improved Access to Healthcare: mHealth eliminates geographical barriers and improves access to healthcare services, especially in remote or underserved areas.
Better Patient Engagement: Patients can actively participate in managing their health, leading to improved self-care and adherence to treatment plans.
Cost-Effectiveness: mHealth solutions can reduce healthcare costs by avoiding unnecessary visits to healthcare facilities and preventing hospital readmissions.
Real-Time Data Sharing: Healthcare providers can receive real-time data from patients, allowing timely interventions and personalized treatment plans.
Enhanced Public Health Initiatives: mHealth applications contribute to public health initiatives by delivering health education and promoting preventive measures for specific health issues.
Despite its numerous benefits, mHealth also faces challenges such as ensuring data security and privacy, regulatory compliance, and reaching populations with limited access to mobile technology. Nonetheless, mHealth continues to transform healthcare delivery, making it more efficient, accessible, and patient-centered.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
This document provides an overview of Chat GPT, an AI tool launched in November 2022 by OpenAI. It discusses that Chat GPT allows for conversational dialogues and aims to give accurate answers while admitting mistakes. The document notes that Chat GPT was trained on huge amounts of online text data to generate human-like responses. Potential uses of Chat GPT discussed include powering virtual customer service agents, personal assistants, social media moderation, and improving machine translation.
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
As generative AI adoption grows at record-setting speeds and computing demands increase, hybrid processing is more important than ever. But just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices, AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential. In this talk you’ll learn:
• Why on-device AI is key
• Which generative AI models can run on device
• Why the future of AI is hybrid
• Qualcomm Technologies’ role in making hybrid AI a reality
The document discusses the evolution of the internet from static Web 1.0 pages to today's dynamic Web 2.0 and upcoming Web 3.0. It defines the Internet of Things (IoT) as connecting physical objects through sensors and internet connectivity. Examples discussed include connecting devices in homes, cities, healthcare, mining and law enforcement. Challenges of IoT include bandwidth, power consumption, security and data management. Standards organizations are working to address these issues and advance IoT technologies. The future may see an "Internet of Everything" connecting people, processes, data and physical things.
Artificial intelligence (AI) aims to create intelligent machines that can function like humans. AI involves techniques like machine learning and deep learning. AI is used in many applications today including smart assistants, self-driving cars, spam filters, and recommendations. Major companies and countries are investing heavily in AI research and development. Future trends may include greater use of AI in areas like cybersecurity, healthcare, transportation, and combining AI with augmented or virtual reality technologies.
Generative AI for Teaching, Learning and AssessmentMike Sharples
AI is disrupting education. Students, teachers and academics can access software that writes essays, summarises scientific texts, produces lesson plans, engages in conversations, and drafts academic papers. These are already being embedded into office tools and will soon be interconnected into an AI-enhanced social network. I will introduce the capabilities and limitations of current generative AI and discuss how it is transforming education, including emerging policy. I will suggest new roles for AI in supporting teaching, learning and assessment. Rather than seeing AI solely as a challenge to traditional education, we can prepare students for a future where AI is a tool for creativity, to be operated with great care and awareness of its limitations.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
As an AI language model, ChatGPT is a program consisting of a large neural network that has been trained on vast amounts of textual data. Specifically, ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) family of models developed by OpenAI.
This presentation discusses various applications of artificial intelligence technologies including neural networks, fuzzy logic, agents, genetic algorithms, natural language processing, and knowledge-based systems. It provides examples of how each technology has been applied in areas like predicting events, diagnosing cancer, automating decisions, and translating languages. The presentation concludes that while AI is still limited, it has matured into an effective tool that allows for new approaches to problem solving in fields like engineering.
The document discusses generative AI models provided by Microsoft's Azure OpenAI Service. It describes that the service provides access to OpenAI's powerful language models like GPT-3 and Codex which can generate natural language, code, and images. It also mentions that the service allows customizing models with your own data and includes built-in tools for responsible use along with enterprise-grade security controls. Examples of tasks the AI models could perform are provided like answering questions, summarizing text, translating between languages, and generating code from natural language prompts.
This document provides an overview of the history and development of artificial intelligence (AI). It discusses early pioneers like Alan Turing and his proposal of the Turing Test. Key developments include the first AI programs for games in the 1950s, the Dartmouth Conference in 1956 which defined the field, and John McCarthy's creation of the Lisp programming language. The document outlines a variety of applications of AI throughout its history from gaming to robotics to military uses. It concludes by discussing predictions for the future role of AI and its potential to solve major problems and change the world.
This document discusses using artificial neural networks for hand gesture recognition. It introduces gesture recognition and ANNs, describing how ANNs can be used for gesture recognition by being adaptive systems that change structure based on information flow. The document outlines training ANNs using feedforward and backpropagation algorithms in MATLAB for gesture recognition. It also provides steps of the recognition process and discusses advantages like learning without reprogramming and disadvantages like needing training.
This document outlines a syllabus for a course on Internet of Things technology. It discusses several topics that will be covered in Module 4 on data and analytics for IoT, including an introduction to data analytics for IoT, structured versus unstructured data, data in motion versus data at rest, and an overview of descriptive, diagnostic, predictive, and prescriptive analytics. Specific techniques that will be examined include machine learning, big data analytics tools, edge streaming analytics, and network analytics. Examples are provided for each topic to illustrate key concepts relating to analyzing large amounts of IoT sensor data.
The document discusses the development and use of a recruitment chatbot. It proposes that a chatbot could automate many time-consuming recruitment tasks like collecting candidate information, screening, and scheduling interviews. This would help address the challenges of sifting through large numbers of resumes and finding qualified candidates more efficiently. The document outlines the design and implementation of a recruitment chatbot using techniques like neural networks, machine learning, and generative dialogue models. It suggests chatbots could handle initial recruitment stages and free up recruiters to focus on human aspects of the process.
Key Features of mHealth:
Accessibility: mHealth allows users to access health-related information and services anytime and anywhere, making it convenient for both healthcare providers and patients.
Remote Monitoring: With mHealth, patients can monitor their health conditions remotely using wearable devices or mobile apps, enabling real-time data tracking and sharing with healthcare professionals.
Health Education and Awareness: Mobile apps and platforms offer health education materials and raise awareness about various medical conditions, preventive measures, and healthy lifestyles.
Telemedicine: mHealth facilitates telemedicine, where patients can consult with healthcare providers through video calls or messaging services, reducing the need for in-person visits.
Health Data Management: Mobile health applications enable users to store and manage their health data, such as medical records, test results, and medication reminders.
Personalized Health Solutions: mHealth platforms can provide personalized health solutions based on individual health data, promoting targeted interventions and better healthcare outcomes.
Benefits of mHealth:
Improved Access to Healthcare: mHealth eliminates geographical barriers and improves access to healthcare services, especially in remote or underserved areas.
Better Patient Engagement: Patients can actively participate in managing their health, leading to improved self-care and adherence to treatment plans.
Cost-Effectiveness: mHealth solutions can reduce healthcare costs by avoiding unnecessary visits to healthcare facilities and preventing hospital readmissions.
Real-Time Data Sharing: Healthcare providers can receive real-time data from patients, allowing timely interventions and personalized treatment plans.
Enhanced Public Health Initiatives: mHealth applications contribute to public health initiatives by delivering health education and promoting preventive measures for specific health issues.
Despite its numerous benefits, mHealth also faces challenges such as ensuring data security and privacy, regulatory compliance, and reaching populations with limited access to mobile technology. Nonetheless, mHealth continues to transform healthcare delivery, making it more efficient, accessible, and patient-centered.
The document describes a mobile shopping website project created by Tejveer Arvind Singh. The project uses PHP and MySQL to allow customers to shop virtually and purchase items online that are then shipped to the address they provide. The website has two modules - one for customers and one for storekeepers to maintain product and customer information. The end user of the application is a departmental store where the administrator maintains the database. The project contains modules for customers, security/authentication, and maintains customer, product and invoice details in the database.
This document provides a summary of Abby Brown's technical experience including book reviews and editor roles, software patents submitted and issued, research projects and presentations conducted, and technical memberships. Key details include serving as technical editor for two books on Tibco software, submitting several patents around automated tools for services, metadata, and network alarms, presenting on topics such as cloud computing and SOA, and holding memberships in technical organizations like IEEE, The Open Group, and OASIS.
This document provides an overview of designing Internet of Things (IoT) systems. It begins with definitions and then describes the key components of an IoT architecture including devices, communication protocols, platforms, and programming languages. Example open source platforms are also discussed. The presentation aims to provide a general understanding of creating IoT prototypes and selecting suitable technologies. Security, analytics, cognitive capabilities and solutions templates are also reviewed at a high level. The overall goal is to help understand the big picture of designing IoT systems and connect concepts to daily work.
IRJET - E-Assistant: An Interactive Bot for Banking Sector using NLP ProcessIRJET Journal
This document describes a proposed chatbot called E-Assistant that would be used in the banking sector to help customers complete tasks like opening accounts or applying for loans. It would use natural language processing to understand user queries and respond in text, speech, or visual form. The chatbot's architecture includes modules for context recognition, preprocessing text, intent classification, entity extraction, and context reset. The goal is to provide a helpful and user-friendly assistant to guide customers through banking processes.
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Definitions
Term
Definition
Access
A means of approaching, entering, exiting, communicating with, or making use of: used a browser to access a website; accessed her bank account online.
Authentication
To positively verify the identity of a user, device, or other entity in a computer system, often as a prerequisite to allowing access to resources in a system.
Connection
A communications link between two points:
Established a connection to the Internet.
Customer
One that buys goods or services.
Data
Distinct pieces of digital information. Data is usually formatted in a specific way and can exist in a variety of forms, such as numbers, text, etc. When used in the context of transmission media, data refers to information in binary digital format.
Device
A device is a unit of physical hardware or equipment that provides one or more computing functions within a computer system. It can provide input to the computer, accept output or both. A device can be any electronic element with some computing ability that supports the installation of firmware or third-party software.
DSL
Digital Subscriber Line or Digital Subscriber Loop. Refers to the variety of different types of Digital Subscriber Line protocols – high-speed data transmission protocols that are compatible with regular copper telephone wire. DSL is typically used to provide a continuous, high-speed connection directly to an Internet Service Provider
Email
Electronic mail. A service that sends messages on computers via local or global networks.
Home network
A local area network (LAN) that connects the PCs in a home and lets users access the Internet simultaneously, share drives, share files and printers, and play head-to-head multi-player games.
Internet
A network of networks; a group of networks interconnected via routers. The Internet (with a capital I) is the world's largest internet.
Internet Access
Access to the Internet via a dial-up account via telephone circuit or direct connection.
Internet Protocol
(IP). The IP part of TCP/IP; the protocol used to route a data packet from its source to its destination over the Internet.
IP Address
The unique 32 bit number assigned to each computer connected to the Internet and used by the TCP/IP protocol to route packets of data to their destinations. The number is usually written in shorthand "dotted octet" notation in which the 32 bit address is grouped into four sets of 8 bits. Each of those eight-bit sets is converted into a decimal number, and the four resulting decimal numbers are written separated by dots. Most Internet addresses consist of a network portion and a node portion. The address for a host must be unique on the network. When you connect to a web server, for example, you may tell your browser to connect to www.mysite.com, but your computer ultimately has to translate the name to its IP .
A CASE Lab Report - Project File on "ATM - Banking System"joyousbharat
A CASE Lab Report - Project File on "ATM - Banking System"
The software to be designed will control a simulated automated teller machine
(ATM) having a magnetic stripe reader for reading an ATM card, a keyboard and
display for interaction with the customer, a slot for depositing envelopes, a
dispenser for cash (in multiples of $20), a printer for printing customer receipts, and
a key-operated switch to allow an operator to start or stop the machine. The ATM
will communicate with the bank's computer over an appropriate communication
link. (The software on the latter is not part of the requirements for this problem.)
Generative AI: A Comprehensive Tech Stack BreakdownBenjaminlapid1
Build a reliable and effective generative AI system with the right generative AI tech stack that helps create smarter solutions and drive growth.
Click here for more information: https://www.leewayhertz.com/generative-ai-tech-stack/
The document summarizes a proposed technology insights discovery platform that aims to provide more intelligent search and discovery of insights from text than current competitors. It would extract entities and insights from sources like news, papers and Wikipedia and present them to users categorized by type and showing their relationships. The startup plans to initially focus on the German market among technology analysts and validate their technology before seeking funding to further develop the product and experience.
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET Journal
The document proposes a new framework for efficient semantic search in large datasets. It aims to improve understanding of short texts by enriching them with concepts and related terms from a probabilistic knowledge base. A deep learning model using stacked autoencoders is designed to learn features from the enriched short texts and encode them into binary codes, allowing similarity searches. Experiments show the new approach captures semantics better than existing methods and enables applications like short text retrieval and classification.
IRJET- A Survey on Technologies used in Mall AssistantIRJET Journal
The document discusses technologies used in developing mall assistants, including chatbots, indoor navigation, artificial intelligence, and machine learning. It surveys recent research on applications and devices that provide services like chatbots for information, indoor navigation through technologies like augmented reality and NFC tags, and automated bill generation and payment. The goal of mall assistants is to enhance the customer shopping experience and increase store profits through personalized services and business intelligence.
Decentralized exchange-Banco: presented by PentagonLuyaoZhangPhD
Here are the key points discussed:
- Discussed the project topic and divided tasks
- Brian will research on the background and key information of Bancor
- 吴希婷 will focus on the cons of Bancor
- 董欣怡 will collect information on the key partners
- 焦月诣 will work on the presentation slides
- Set up a schedule to exchange information before the deadline
All members showed good cooperation and understanding of each other's strengths. The meeting ended smoothly with clear tasks and timeline.
Data Security String Manipulation by Random Value in Hypertext Preprocessorijtsrd
Hypertext Preprocessor PHP and Hypertext Markup Language HTML were important as scripting languages in most of the web based development. As an open source type, it has benefited educators and web developers in either education or commercial context due to their easy accessibility. However, there were many concepts and mechanisms that could be learnt and explored in order to produce quality system design in this respective language. As web based system transmit and exchange data within a vast network of Commercial Interconnected Network Internet , the data were exposed to many attackers who wish to steal the data, therefore the security aspect which focusing on protecting the data technically automated computation should be taken into account when designing the system, apart from the policies, rules or laws enforcement in cyber security environment. In this experiment, a light data manipulation technique were developed to convert the string user input into different forms of text representation of numerical value. Danial Kafi Ahmad | Zul Hilmi Abdullah | Siti Nuraini Ahmad "Data Security: String Manipulation by Random Value in Hypertext Preprocessor" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31283.pdf Paper Url :https://www.ijtsrd.com/computer-science/computer-security/31283/data-security-string-manipulation-by-random-value-in-hypertext-preprocessor/danial-kafi-ahmad
The document discusses developing an online auction system using technologies like ASP.NET and SQL Server to allow sellers to list products and buyers to bid on products, with modules to handle administration, sellers, buyers, bidding, and online payments. It aims to provide a more efficient platform for auctions by allowing interdependent values and information sharing between bidders.
License Plate Recognition Using Python and OpenCVVishal Polley
License Plate Recognition Systems use the concept of optical character recognition to read the characters on a vehicle license plate. In other words, LPR takes the image of a vehicle as
the input and outputs the characters written on its license plate.
Controlling Home Appliances adopting Chatbot using Machine Learning ApproachMinhazul Arefin
In the last decades, home automation becomes popular and rapidly increased artificial intelligence-based controlling systems. So, many researchers have been interested in the Internet of things so that every appliance should be autonomous. Smart home technology is one of them. It involves certain electrical and electronic systems in a building with some degree of computerized or automated control. It can control elements of our home environments (e.g. light, fans, electrical devices, and safety systems). We propose an approach that fully controlled the home appliances by chatbot technology. In our research, the system can extract the device name such as light, fan, etc using synonyms. In the device name extraction part, we use Jaro-Winkler string matching algorithms. We have also used the Naive Bayes algorithm to take command for action. Finally, a Firebase-based system connects the users and controls hardware. Our model can control the home appliances from a long distance because we used the wireless fidelity system.
This document discusses the development of a chatbot using natural language processing (NLP) to provide information to users about Indian Railways. The chatbot is designed to answer common queries about train routes, fares, arrivals and departures. It uses NLP techniques like tokenization, stop word removal and intent classification to understand user queries. The chatbot architecture involves an NLP module that processes text input and classifies intent, which is then used to query the official Indian Railways API and return responses to the user. Algorithms like naïve bayes, recurrent neural networks, decision trees and SVM are used. The chatbot has the potential to replace physical railway inquiry counters and provide information to users in both English and
Accelerating Application Development in the Internet of Things using Model-dr...Pankesh Patel
This document discusses model-driven development approaches for accelerating application development in the Internet of Things (IoT).
It introduces IoTSuite, a toolkit that enables IoT application development with minimal effort through separation of concerns. Domain, functionality, and deployment specifications are compiled to generate programming frameworks. This reduces development time and effort and improves reusability.
It also describes the SMEWB (Subject Matter Expert Workbench), which aims to empower industrial subject matter experts to create, reuse, and deploy analytic algorithms with little coding. It allows dragging and dropping to develop analytic modules and supports various deployment options.
[DOCUMENT]
This document contains summaries of 26 different projects related to various domains including networking, image processing, healthcare, education, and more. The projects cover a range of modules and functionalities like user registration, file uploading/downloading, password authentication, device control, and more. The technologies used include Java, J2EE, SQL, and various other tools and platforms.
Similar to Maximizing Innovation through ChatGPT Powered Patent Analysis (20)
Intangible assets, which account for up to 90% of a company's value, especially patents, which make up the largest proportion of these assets, are hardly ever utilized for corporate value creation despite their value. In this presentation, I introduce patent management solutions for the development of patents that can contribute to corporate value creation, using the latest digital technologies such as AI, blockchain, and Web 3.0. I also introduce measures to maximize the financial use of patent assets secured through such patent management. In particular, I will look into the domestic and overseas trends of STO (Security Token Offering), which have recently been gaining attention in S. Korea, and learn about strategies and methods for patent asset STO.
The Metaverse x AI x Web3 x Sustainability convergence presents a future vision that transforms how we interact with the digital realm, combining the expansive, immersive qualities of the Metaverse, the advanced computational abilities of AI, the decentralized nature of Web3, and the global imperative of sustainability.
Metaverse and AI Integration: AI technologies shape the Metaverse to be an immersive, interactive, and deeply engaging digital universe. Tools like the Meta AI Builder Bot, Nvidia's GANverse3D/GET3D, and Magic3D create 3D environments and objects, contributing to the Metaverse's realism. Lifelike human avatars, AI-powered digital fashion design, and immersive shopping experiences further enrich user engagement. Additionally, the Metaverse can become a testing ground for AI innovation, enabling developers to leverage its vast data generation and system testing capabilities.
AI and Web3 Integration: AI fortifies the decentralized Web3 ecosystem, creating unique digital assets for Non-Fungible Tokens (NFTs) and potential markets within the Metaverse. Furthermore, AI's capability to automate DeFi processes paves the way for more efficient, accessible financial services in the decentralized digital economy.
Web3 and Metaverse Integration: Blockchain technologies, the backbone of Web3, could be woven into the fabric of the Metaverse, giving rise to novel, decentralized commerce systems. It can enable peer-to-peer transactions and build decentralized marketplaces, providing users with greater control over their economic interactions in the virtual realm.
Metaverse and Sustainability Integration: The Metaverse offers a virtual platform to drive sustainable initiatives, reducing real-world resource consumption. In the Metaverse, renewable energy systems could be simulated and managed, virtual stores could advocate for sustainable products, and virtual factories could optimize sustainable manufacturing processes and supply chains. Furthermore, it could serve as a prototyping platform for sustainable smart cities, providing an efficient way to plan, simulate, and refine before real-world implementation.
To conclude, the convergence of Metaverse, AI, Web3, and Sustainability initiates a transformative movement toward a digital ecosystem that's immersive, intelligent, decentralized, and sustainable. This synergy could redefine digital experiences, promote efficient and fair economic interactions, and support global sustainability goals, signifying a new dawn in our digital evolution.
Tokenization, securitization, and monetization of real-world assets refer to the process of converting traditional assets into digital assets that can be traded, managed, and invested in a new way. Tokenization involves the creation of a digital token that represents ownership or a proof of authenticity of a real-world asset. The token can be traded on blockchain-based platforms, providing a secure and transparent record of ownership and enabling the creation of new markets for these assets. Securitization refers to the process of pooling together a set of assets and creating new securities backed by the underlying assets. In the context of tokenization, securitization involves the creation of asset-backed tokens that represent ownership in a portfolio of assets. Monetization refers to the process of generating revenue from an asset. In the context of tokenization and securitization, monetization can involve selling tokens or securities, licensing assets, or generating income from the underlying assets.
This webinar is designed to explore the tokenization, securitization, and monetization of real-world assets that have the potential to revolutionize the way we trade, manage, and invest in real-world assets, and to create new markets and opportunities for investors and asset owners.
Agenda:
Asset‐Backed Tokens
Security Token Offering (STO)
Securitization of Real-World Assets
NFT & DeFi for Securitization and Monetization of Real-World Assets
Metaverse for Monetization of Real-World Assets
Case Studies: Real Estates, Securities, Intangible Assets
IP Asset Tokenization, Valuation, Monetization: IPwe SIAM Platform
The document discusses various applications of artificial intelligence (AI) and how patents related to AI innovations can be utilized commercially and financially. It describes how AI is being used to create virtual environments, 3D objects and models, and human avatars. It then discusses how patents covering AI technologies are important assets that can be used strategically for competitive advantages, partnerships, investment and mergers & acquisitions. The document also introduces IPwe's Smart Intangible Asset Management platform, which uses AI to evaluate patent quality and value, tokenize patents as non-fungible tokens, create a marketplace for monetizing patents, and enable various financial applications of patented technologies like securitization and lending.
Real-World Assets STO + Institutional DeFi Integration
Institutional DeFi refers to tokenize real-world assets with regulatory compliance and institutional-level controls for consumer protection. One of the main benefits of Institutional DeFi is the potential to transform the traditional financial system by making it more transparent, efficient, and accessible while maintaining the necessary safeguards for investor protection and financial stability. This can lead to new products, cost reduction, and faster settlement times for financial institutions.
STO (Security Token Offering) of real-world assets involves the issuance of security tokens that represent ownership of a real-world asset, such as a share of stock, bond, or real estate property. The tokenization and securitization process is carried out by an issuer who follows the necessary regulatory requirements. These security tokens can be listed, distributed, and traded on Institutional DeFi applications to automate various processes such as trading, settlement, and custody. This allows for greater security, efficiency, transparency, and liquidity.
#defi #fundraising #sto #tokenization #nft #securitization #security
Presentation of the Interoperable Metaverse x Web3 Development Webinar
Agenda:
Challenges in Building Interoperable Metaverse
3D Objects/Contents/Avatars/Assets Cross-Metaverse Interoperability
NFT Cross-Chain Interoperability
Interoperability in Metaverse Fashion
Metaverse Interoperability Standards
Speakers
Mikeldi Rodriguez, Metaverse Creative Technologist at Telefónica
"Avatar Interoperability Based On Metadata"
Leo Hilse, Founder at STYLE Protocol
"STYLE Protocol: NFT Inter-Metaverse Interoperability"
Alain Dessureaux, CTO at SpatialPort
"SpatialPort's Interoperable 3D eCommerce Platform"
This webinar is designed to explore the state of the art AI innovation and business applications for the web3 based metaverse development.
Agenda:
AI for Building Metaverse World
AI for 3D Objects/Contents/Avatars Creation
AI for Metaverse Commerce
AI for Metaverse Fashion
AI for NFT
AI for DAO
IP Issues with AI Created Assets
[Reminder] NFT•Web3•Metaverse Global Leaders Roundtable
Thais is a reminder that the NFT•Web3•Metaverse Global Leaders Roundtable will begin in three days on December 1 (Thursday) 2022, 12 pm ET (https://www.linkedin.com/events/nft-web3-metaversegloballeaders6988852388136640513/about/).
This roundtable is a hybrid Zoom + Metaverse event. At the start of the event, all participants will join the Zoom for a scheduled speaker introduction and networking. Those who want to participate in the metaverse event will join after the Zoom event.
Schedule:
12:00 - 12:05 EST "Introduction" Alex G. Lee, CEO & Founder at TechIPm
Part I. Zoom Meeting
12:05 - 12:20 EST “Reviews of NFT•Web3•Metaverse Global Leaders Presentations” Alex G. Lee
12:20 - 13:00 EST Speaker Introduction & Recap”
Matteo Gamberale, Founder & CEO at Zappy
Jens Laugesen, Founder at JENS_LAUGESEN DESIGN ADVISORY & KONsensX
Ofer Rubin, 3D/XR Executive Advisor at RealeyeZ3D
Erich Spangenberg, CEO & Co-Founder at IPwe
Tapan Lala, Founder at ZcureZ
Husam Yaghi, Group VP at Mawarid Media & Communications Group
Alex Bellesia, CEO & Founder at Spatial Port
Nick Cherukuri, CEO & Founder at ThirdEy
Doug Hohulin, Affiliate Faculty at Kansas University School of Nursing
Ruben Sananes, CEO & Founder at IMRSIVE
Se-Joon Chung, CEO & Co-Founder at AForm
James Costa, Founder at Clubhouse Archives
Tom Wallace, Founder at CreatedBy DAO
Aditya Mani, Founder at YOLOgram app
Aline Conus-Moulin, Managing Partner at E-NOTAM Ltd.
Vandana Taxali, Founder & CEO at Artcryption
Alex Di Giovanni, Founding Lawyer at Pando Law
13:00 - 13:15 EST
“Guidance for the Metaverse Event Places " Alex G. Lee
Part II. Metaverse Meeting
At the Metaverse Campus’ Lecture Hall (https://www.challau.com/college/techipm)
13:15 - 13:30 EST "Present and Future of NFT•Web3•Metaverse" Presentation by Doug Hohulin,
At the Metaverse Networking Place (https://www.challau.com/town-square/alex-g--lee)
13:30 - 14:00 EST “Networking with Speakers”
The document discusses the Hyper Connected Fashion Metaverse being developed by FAME UNIVERSE Co., Ltd. It aims to connect the physical and digital fashion worlds by digitizing physical fashion designs and garments for use as NFTs and wearables in virtual spaces. This will help address issues like counterfeiting and give creators new ways to showcase and monetize their work. FAME provides services like transforming physical designs into 3D digital assets and launching crowdfunding campaigns for physical production. Partnerships are in place to expand access to metaverses and marketplaces. The goal is a hybrid online/offline marketplace and ecosystem that nourishes both the physical and digital fashion universes.
The fashion industry represents the estimated global revenues of $1.5T.
The global counterfeiting industry is expected to hit the $4.2T mark by 2022.
References
The fashion industry lost more than $50B in 2020 due to the sale of the counterfeit products:
Clothing appears to be the most counterfeited product followed by cosmetics and personal care, watches and jewelry, handbags and luggage.
The COVID-19 pandemic accelerates the digital transformation globally, and the fashion industry is no exception.
Citi expects the metaverse economy as large as $13T by 2030 and Gartner predicts that , and Gartner predicts that 25% of people will spend at least one hour a day
in the metaverse by 2026.
The creator economy has already exceeded a $100B market size. The NFT
market reaches $1.05T. The wearable NTF market is expected to be $11B in 2022.
Fashion industry lends well to the metaverse where the ecosystem includes metaverse fashion digitalization, metaverse fashion house/brand,
Ph i l f hi h d f hi k l il d h f hi k i d ygitalwear, metaverse fashion show and metaverse fashion marketplace/retail, and the metaverse fashion market is expected to increase
up to $55B by 2030.
As sustainability became the mainstream business the anti , the anti-sustainability and anti-circularity nature of the fashion business place
the sustainability as the top priority agenda in the fashion business practices.
Fashion digitalization and the metaverse fashion can be a potential solution for mitigating the anti-sustainability and anti-circularity nature
TechIPm, LLC
of the fashion business.
Gen Z and Gen Alpha become the future big spenders and sustainability advocates in fashion.
Schedule
12:00 - 12:10 EST
"Introduction" Alex G. Lee, CEO & Founder at TechIPm
12:10 - 12:25 EST
“JENS LAUGESEN X META\SENS Digital Collaboration in London Fashion Week” Jens Laugesen, Founder at JENS_LAUGESEN DESIGN ADVISORY
12:25 - 12:40 EST
"Ecoolska: Phygital Sustainable Fashion Brand" Olska Green, Founder at Ecoolska
12:40 - 12:55 EST
"WEARSPACES: Dress like a game-changer in Metaverse & IRL" Julien Chmilewsky, Co-Founder at WEARSPACES
12:55 - 13:10 EST
"Innovation in Fashion Brands Metaverse Shopping Experiences" Ruben Sananes, CEO & Founder at IMRSIVE
13:10 - 13:25 EST
"NEOMODEST: Inclusive, Accessible, Decentralized Metaverse Fashion" Afroja K, Founder at NEOMODEST
13:25 - 13:40 EST
"XTENDED iDENTiTY: The Experiential Digital Fashion Lab" Xing Yunjia, Co-Founder at XTENDED iDENTiTY
13:40 - 13:55 EST
“GAD (Garment Automated Digitisation)” Pietro Dalpane, CEO & Co-Founder at DeepGears
13:55 - 14:10 EST
"Fostering Interoperable Digital Fashion Through Graphics Technology" Se-Joon Chung, CEO & Co-Founder at AForm
14:10 - 14:25 EST Coffee Break
14:25 - 14:40 EST
“3D Garment Creation to Simulation - Connecting Digital Fashion with Digital Human” Kenneth Ryu, CSO at z-emotion
14:40 - 14:55 EST
"A Luxury Fashion Brand & Web3 Marketplace" James Costa, Founder at Clubhouse Archives
14:55 - 15:10 EST
"Marketing Digital Fashion with Avatar Generated Content" Diego Rios, Founder at Animalz
15:10 - 15:25 EST
"CreatedBy DAO: A Phygital NFT Ecosystem" Tom Wallace, Founder at CreatedBy DAO
15:25 - 15:40 EST
"MaisonDAO: Decentralized Digital Fashion Brand and ArtTech Collective" Elena Nazaroff, Co-Founder at MaisonDAO
15:40 - 16:05 EST
"Browzwear Innovative 3D Digital Fashion Solution" Afsha Iragorri, 3D Fashion Designer at 3D Fashion Solutions
16:05 - 16:20 EST
“Innovative 3D Digital Fashion Design” Olesya Pupchenko, Director at Global Rise Group
Agenda
Metaverse Fashion Design
Interoperable Metaverse Fashion
NFTs for Metaverse Fashion
Web3 for Metaverse Fashion
Metaverse Fashion Commerce
NFT financialization refers to bringing NFTs closer to financial use, mostly, by making NFT useful in DeFi protocols. NFT financialization is the most important element of NFT monetization innovation to overcome the low liquidity and high price volatility of almost all NFTs currently.
NFT Fractionalization splits a NFT into smaller fungible tokens that represent partial ownership of the NFT. The NFT is locked in a smart contract and the ownership remains with the original holder. Fractionalization can unlock liquidity for NFT owners and cheapens access to valuable NFTs, and improves the NFT market spectrum. An issue with fractionalization is a reconstitution after ractionalization. Buyout auctions alleviate the reconstitution problem to some extent.
*NFT fractionalization protocols: NFTX (https://nftx.io/), Fractional (https://fractional.art/), NFT20 (https://nft20.io/), Unic.ly (https://www.unic.ly/), Szns (https://www.szns.io/)
NFT Lending uses NFT as collateral for loans. In peer-to-peer lending, borrowers and lenders manually negotiate and come to an agreement for loan terms such as duration, interest rates and loan-to-value ratios in a peer-to-peer fashion. This lending enables a customizable loan terms without a need to rely on price oracles. Because the matching process is manual time-to-liquidity may be slow. In peer-to-pool lending, liquidity providers fungible tokens into pools and borrowers take up loans from these pools instantaneously. Borrowers should put up their NFTs as collateral by locking them in smart contracts (digital vaults). This lending, however, must rely on price oracles to automate loan terms.
*Peer-to-peer NFT lending protocols: NFTfi(https://www.nftfi.com/), Arcad (https://www.arcade.xyz/), MetaStreet (https://metastreet.xyz/)
*Peer-to-pool NFT lending protocols: Bridgesplit (https://www.bridgesplit.com/), BendDAO (https://www.benddao.xyz/en/, PINE (https://pine.loans/), JPEG’d (https://jpegd.io/)
NFT Rental market is where NFT owners can rent out their NFTs to receive income and renters can rent NFTs to use but without owning them. In collateral renting, renter has to put up collateral to rent the NFT to use (e.g., reNFT (https://www.renft.io/). Collateral-free renting separates ownership and utility of an NFT (e.g., IQ Protocol (https://iq.space/#top).
NFT Price Discovery uses AMMs (Automated Market Makers)/bonding curves for an automatic price discovery in DeFi exchange liquidity pools (e.g., Uniswap and Sushiswap).
*NFT Price Discovery protocols: Sudoswap (https://sudoswap.xyz/#/), Pilgrim (https://pilgrim.money/), Rootswap (https://rootswap.xyz/)
I. Metaverse Digital RevolutionMetaverse Revolution ImperativesMetaverse Present and Future InfographicsMetaverse Industry ApplicationsII. Metaverse Technology InnovationWhy Metaverse Now?Meta Metaverse XR Device PrototypesApple Metaverse XR Device Insights from PatentsRoblox Metaverse Game Platform Innovation Insights from PatentsDigital Twin Innovation Insights from PatentsMetaverse Patents Development Boom3D Metaverse Space Development: 3D Rendering 3D Metaverse Space Development: 2D to 3D Translation 3D Metaverse Object Development: 2D to 3D ConversionInteractive Experience Design: Multi-Sensory PerceptionVirtual Product Development: NFT Digital AssetsMeatavere Application Development: Retail ShoppingMeatavere Application Development: Automotive ShowroomMeatavere Application Development: TourMeatavere Application Development: MeetingMeatavere Application Development: Smart FactoryMetaverse Enterprise PlatformMetaverse Enterprise Platform System Components
III. Metaverse Business Development: Metaverse BM & InvestmentExperience EconomyMetaverse User Experiences (MUXs)Metaverse BM Innovation for New Experience EconomyMetaverse Angel/VC Investors IV. Metaverse Economic SystemNFT Functions and Legal Status NFT + DeFi ConvergenceMetaverse Economic System ComponentsMetaverse Economic System ArchitectureV. Metaverse + ESG ConvergenceESG/Sustainability ImperativeMetaverse Renewable Energy System ManagementMetaverse Factory for Sustainable Manufacturing/Supply ChainMetaverse for Sustainable Smart City Development Metaverse NFT/DeFi Based Sustainable FinancingDesigning Sustainable Metaverse Experiences (SMXs)Metaverse Impact on EnvironmentMetaverse Impact on People/Society
This webinar is designed to explore the innovative NFT monetization through the convergence of NFT securitization and DeFi.
Agenda
Reviews of NFT Monetization
NFT Valuation
NFT IP Licensing
NFT + DeFi Convergence: MetaFi, GameFi, DAOFi, ...
NFT Securitization Development
Legal Challenges of NFT Securitization
NFT Securitization Use Cases
NFT Securitization + DeFi Convergence
Schedule:
12:00 – 12:15 ET, Alex G. Lee
"Introduction & Overview"
12:15 – 12:30 ET, Ted Kim
"XBRIK: NFT Securitization & Brick Exchange & IBO DeFi Platform"
12:30 – 12:45 ET, Aditya Mani
"In-app monetization of NFTs for Style"
12:45 – 13:00 ET, Aline Conus-Moulin
"NFT Valuation: Challenges & Solutions"
13:00 – 13:15 ET, Yael Tamar
"NFTs in Real Estate"
13:15 – 13:30 ET, Vandana Taxali
"NFT IP Rights Licensing: Deep Dive"
13:30 – 13:45 ET, Joshua Hale
"NFTDAOs not spelled S A F E: Why the most interesting things you can do in crypto can land you in hot water!"
13:45 – 14:00 ET, Alex G. Lee
(Optional) Q&A/Discussion
The document discusses an upcoming seminar on using NFTs to generate revenue through metaverse and web3 applications. The seminar will have a basic session covering the fundamentals of metaverse, web3 and NFTs, and an advanced session covering key aspects of NFT valuation and monetization strategies. It also lists some reference materials on NFTs, metaverse and web3.
This webinar is designed to explore the current status of the NFT ecosystem and monetization potentials exploiting the web3 based metaverse. If you are a tech-savvy IP legal professional, you will be interested in legal challenges and opportunities with the NFT/Web3/Metaverse/Cryptocurrency.
Please join on September 22 (Thu) at 12:00 ET to learn from legal experts in NFT, Web3, Metaverse, Tokenization, Intellectual Property:
"NFT IP Rights: Monetization Opportunities & Legal Challenges" from Vandana Taxali, Founder & CEO at Artcryption
"Legal Challenges of Web3 Gaming Studios and Platforms" from Andrew Cripps, Founder at MetaCounsel
Agenda:
Utility NFT for Metaverse Monetization
NFT for Customer Loyalty Program 3.0
NFT for X2E (Play-to-Earn, Wear-to-Earn, ...)
NFT Interoperability
NFT Valuation
NFT for Web2/Legacy to Web3/Metaverse Business Transition
NFT for Creator/Experience Tokenomics
NFT based Monetization for Metaverse Fashion & Other Industries
NFT for Monetizing IP Portfolio Development (NFT IP Securitization)
NFT IP Rights Legal Issues
NFT + DeFi Convergence: MetaFi, GameFi, DAOFi, ...
NFT for Physical + Virtual Convergence Economy/Commerce
Future of NFT: Composable NFT, Dynamic NFT, Consumable NFT, ...
Other speakers/topics:
"The Future of NFT" from Mohamed Hafiz, Advisor at First Abu Dhabi Bank
"NFT based Monetization for Metaverse Fashion & Other Industries" from Nova Lorraine, Director at Raine Drops NFT Art House
"Phygital Fashion with NFTs" from Fahmid Uddin, Founder at M3RCH.xyz
"Interoperable NFTs for GenZ: Gaming and Fashion" from Matteo Gamberale, Founder & CEO at Zappy
"NFT for Web2/Legacy to Web3/Metaverse Business Transition" from Gianfranco Lopane, President at Smarterverse
"Your Digital DNA & NFT: Monetization of Digital Identity in the Metaverse" from Kelvin Troy, CEO at Cross-Metaverse Avatars LLC
Fame Universe (https://fameuniverse.xyz/) is a platform builder that hyper connecting fashion “From Physical to Digital And From Digital to Physical.” Fame’s mission is to lead the “Sustainable Metaverse Fashion Ecosystem” that nourishes existing physical and digital fashion universes where we can build, create, enjoy, play, earn and shop in a sustainable way.
Fame Platform
Patent pending Fame platform is a sustainable metaverse fashion ecosystem building platform that provides a play ground where the ecosystem players and stakeholders can co-create a sustainable metaverse fashion ecosystem. Fame platform provides the interfaces for the ecosystem players and stakeholders can cooperate synergetically to build sustainable metaverse fashion ecosystem more efficiently and effectively. Fame platform provides/integrates the tools/solutions/knowledge/expertise for supporting a sustainable metaverse fashion ecosystem development.
Fame Fashion NFT Monetization Platform
Patent pending Fame fashion NFT monetization platform (FameFiTM) is a core element of the fame platform.
FameFiTM is designed to provide most innovative fashion monetization solution that can maximize opportunities and resolve many challenges in fashion NFT monetization.
FameFiTM is designed to employ various innovative monetization methods including fashion IP NFT licensing, securitization and NFTFi for maximizing monetary rewards to the Fame ecosystem/community members and for enabling financially sustainable Fame metaverse fashion ecosystem development.
FameFiTM is designed to resolve many legal issues in fashion NFT monetization and overcome several huddles in the fashion NFT valuation.
FameFiTM is designed to innovate the fashion NFT value creation through NFT scarcity, utility and sustainable tokenomics development.
C: The metaverse is designed to give like-minded communities of common interests digital sandboxes to play, earn, own, and socialize.
U: The decentralized economy is user controlled, not centrally governed.
T: The metaverse experience is possible through Web 3.0 technology, such as blockchain, 5G networks, VR, AR, and cloud computing.
E: Experiences and interactions give NFTs greater utility, which drives greater value.
R: A connection to the real world gives the metaverse value beyond entertainment as it augments real-world experiences and offers the potential for real financial gains as well.
Fame Universe (https://fameuniverse.xyz/)
Fame is a platform builder that hyper connecting fashion “From Physical to Digital And From Digital to Physical.”
Fame’s mission is to lead the “Sustainable Metaverse Fashion Ecosystem” that nourishes existing physical and digital fashion universes where we can build, create, enjoy, play, earn and shop in a sustainable way.
Fame Platform
Fame platform is a sustainable metaverse fashion ecosystem building platform that provides a play ground where the ecosystem players and stakeholders can co-create a sustainable metaverse fashion ecosystem.
Fame platform provides the interfaces for the ecosystem players and stakeholders can cooperate synergetically to build sustainable metaverse fashion ecosystem more efficiently and effectively.
Fame platform provides/integrates the tools/solutions/knowledge/expertise for supporting a sustainable metaverse fashion ecosystem development.
Fame Platform Design
Fame platform is designed to provide a simple way of embracing digital/web3 fashion business for legacy/web2 fashion business.
Fame platform is designed to provide a community building solution that the ecosystem players and stakeholders can participate with self-sovereignty and consensus.
Fame platform is designed to employ various innovative monetization methods for increasing market scalability.
Fame platform is designed to be modular considering current technology limitations and emerging technology expectations.
Fame platform is designed to resolve fashion’s inherent sustainability/circularity issues.
Agenda
1. Fashion Digitalization
2. NFT for Metaverse Fashion Ecosystem Development
3. DAO for Metaverse Fashion Ecosystem Development
4. Token/Creator/Experience Economy for Metaverse Fashion Ecosystem Development
5. DeFi for Metaverse Fashion Ecosystem Development
6. Sustainability Issues in Fashion Ecosystem
7. Sustainable Metaverse Fashion Retail Development
8. Building Sustainable Metaverse Fashion Ecosystem
9. Best Use Cases/Practices
10. Web3 based Sustainable Metaverse Fashion Ecosystem Development Insights from Patents
11. Investing in Metaverse Fashion
Schedule
12:00 – 12:15 ET, Alex G. Lee
Overview & Fame Universe Introduction
12:15 – 12:30 ET, Aditya Mani
Creator/Experience Economy For The Metaverse Fashion Ecosystem
12:30 – 12:45 ET, Ayesha Mubarak Ali
Phygital Fashion And Identity Through Fusion Art Techniques
12:45 – 13:00 ET, Miki Elson
DAO And Sustainable DeFi For The Metaverse Fashion Ecosystem
13:00 – 13:15 ET, Jade McSorley
The Digitization of Fashion: Opportunity or Risk?
13:15 – 13:30 ET, Dennis Zhang
Web3 Based Sustainable Fashion: Challenges And Opportunities
13:30 – 13:45 ET, Marta Waydel
Digitalizing Sustainable Fashion Consumption
13:45 – 14:00 ET, Louise Laing
Fashion Digitalization For Making Fashion Business More Sustainable and Profitable
14:00 – 14:30 ET, Alex G. Lee, (Optional) Q&A/Discussion
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Maximizing Innovation through ChatGPT Powered Patent Analysis
1. 1
Maximizing Innovation through ChatGPT Powered Patent Analysis:
Insights for New Product/Service Development
in Generative AI, Metaverse, and Web3 based FinTech
Alex G. Lee (https://www.linkedin.com/in/alexgeunholee/)
Methodology
The key to staying competitive in today's fast-paced technological landscape is to constantly innovate and develop
new products or services that meet the changing demands of markets. One valuable resource for obtaining insights
into state-of-the-art technology innovation is through patent analysis for specific technology fields.
In order to leverage the vast amount of information contained in patents and extract valuable insights for new
product or service development in the fields of Generative AI, Metaverse, and Web3 based fintech, a guideline was
created and provided to GPT-4 based ChatGPT. The guideline consists of five key steps, including identifying the
main objectives of the patented invention, summarizing the technology innovation described in the patent claims,
elaborating potential products or services based on the technology, identifying key players in the industry, and
evaluating competitive advantages. For each of the selected fields, a single patent was chosen to apply the guideline
and demonstrate its effectiveness in extracting valuable insights for innovation and staying ahead of the competition.
Step 1: In order to identify the main objectives of the patented invention, specification of the patent document must
be carefully analyzed. This involves reading through the patent document to gain a thorough understanding of the
technology being described, the problem it aims to solve, and the potential applications of the invention.
Step 2: Once the main objectives of the patented invention have been identified, the technology described in the
patent claims must be analyzed. This involves identifying the key features and components of the invention, and
how they work together to achieve the stated objectives. This step provides a clear understanding of the technology
and its potential applications.
Step 3: Elaborating on potential products and services based on the technology described in step 2 involves
brainstorming and identifying different ways the technology can be applied. This may involve considering different
industries, markets, and use cases, and thinking about how the technology can be adapted or modified to suit these
different applications.
Step 4: Identifying key players in the industry is an important step in understanding the potential market for the new
product or service. This involves researching and analyzing the different companies and organizations operating in
the industry and identifying those that are best positioned to take advantage of the new technology.
Step 5: Elaborating on the competitive advantages of the potential products, or services compared to industry
players involves identifying the unique features and benefits that the new product or service offers. This may
involve comparing the new product or service to existing solutions in the market and identifying areas where it
outperforms the competition, such as in terms of cost, functionality, or ease of use. This step helps to determine the
potential market share and revenue potential of the new product or service.
Generative AI Case Study
Google Patent US10452978 Attention-based sequence transduction neural networks
(https://patents.google.com/patent/US10452978)
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium,
for generating an output sequence from an input sequence. In one aspect, one of the systems includes an encoder
neural network configured to receive the input sequence and generate encoded representations of the network inputs,
the encoder neural network comprising a sequence of one or more encoder subnetworks, each encoder subnetwork
configured to receive a respective encoder subnetwork input for each of the input positions and to generate a
respective subnetwork output for each of the input positions, and each encoder subnetwork comprising: an encoder
self-attention sub-layer that is configured to receive the subnetwork input for each of the input positions and, for
2. 2
each particular input position in the input order: apply an attention mechanism over the encoder subnetwork inputs
using one or more queries derived from the encoder subnetwork input at the particular input position.
*This patent covers the famous transformer architecture which is the fundamental build block of most of the large
language model (LLM) generative AI. It was introduced by Vaswani et al. in the paper "Attention is All You Need"
in 2017. Since then, many variants and adaptations of the original transformer architecture have been developed.
Base on my analysis, it reads on OpenAI ChatGPT Architecture, which means ChatGPT infringes this patent.
3. 3
Main Objectives
Develop a sequence transduction neural network that relies on attention-based encoder and decoder components, as
opposed to recurrent neural networks, for improved performance in various transduction tasks, such as machine
translation.
Achieve faster training and inference times by leveraging the parallelization capabilities of attention-based networks,
which mitigates the sequential nature and resource-intensive workloads associated with recurrent neural networks.
Improve the accuracy of the sequence transduction neural network by effectively learning dependencies between
distant positions in input and output sequences through the use of attention mechanisms, particularly self-attention.
Achieve state-of-the-art results in machine translation tasks with reduced training and inference times compared to
conventional machine translation neural networks.
Enable the sequence transduction neural network to perform well on various tasks without task-specific tuning by
leveraging the attention mechanism.
Technology Innovation
The patented technology describes a sequence transduction neural network system that relies on attention-based
encoder and decoder components instead of recurrent neural networks. The system is implemented on one or more
computers and storage devices. The encoder neural network receives an input sequence and generates encoded
representations for each input. It consists of a sequence of encoder subnetworks, each with an encoder self-attention
sub-layer.
The decoder neural network receives the encoded representations and generates an output sequence. The decoder
operates auto-regressively, generating output positions conditioned on the encoded representations and preceding
network outputs. It also consists of a sequence of decoder subnetworks with an encoder-decoder attention sub-layer
and a decoder self-attention sub-layer.
The system is designed to improve the performance of various transduction tasks, such as machine translation, by
leveraging the parallelization capabilities of attention-based networks, effectively learning dependencies between
distant positions in input and output sequences, and performing well on various tasks without task-specific tuning.
Potential Products/Services
Neural Machine Translation: A translation service that efficiently translates text between different languages,
providing faster and more accurate translations compared to conventional machine translation systems.
Speech Recognition: A system that accurately converts spoken language into written text, benefiting transcription
services, voice assistants, and real-time captioning applications.
Natural Language Processing: A system that can generate summaries, answer questions, or perform sentiment
analysis on text data. This could be applied to areas like news summarization, customer service chatbots, or
sentiment analysis for market research.
Computer-Assisted Medical Diagnosis: A system that analyzes electronic medical records and predicts suitable
treatments for patients, assisting healthcare professionals in providing personalized and efficient care.
Image Processing: A system that can generate textual descriptions for images or generate images based on a given
textual context. This technology could be applied in areas like image captioning for accessibility, content generation
for social media, or visual storytelling.
Automated Video Transcription: A system that extracts audio from video files and converts it into text, making it
easier to search, analyze, and share video content.
Language Modeling: A system that can generate realistic and coherent text based on a given prompt, which could
be used for content creation, advertising, or even creative writing assistance.
4. 4
Sentiment Analysis: A system that can determine the sentiment or emotion behind a given text, allowing businesses
to gauge customer satisfaction, detect potential public relations issues, or monitor social media trends.
Code Generation: A system that can understand natural language descriptions of software requirements and
generate corresponding code, improving the efficiency of software development processes.
Personal Assistants and Chatbots: AI-driven personal assistants or chatbots that can understand and respond to
user queries in a more human-like manner, providing a better user experience in customer support or general
information retrieval.
These applications can be provided as standalone products or integrated into existing services, enhancing their
capabilities and improving user experiences.
Key Industry Players
Neural Machine Translation:
Google Translate (Google)
Microsoft Translator (Microsoft)
DeepL Translator (DeepL)
Speech Recognition:
Nuance Communications
Google Speech-to-Text (Google)
Amazon Transcribe (Amazon)
Natural Language Processing:
OpenAI
IBM Watson (IBM)
Google Cloud Natural Language (Google)
Computer-Assisted Medical Diagnosis:
Zebra Medical Vision
Aidoc
PathAI
Image Processing:
Google Cloud Vision (Google)
Amazon Rekognition (Amazon)
Microsoft Azure Cognitive Services (Microsoft)
Automated Video Transcription:
Rev.com
Otter.ai
Trint
Language Modeling:
OpenAI (GPT-3)
Google AI (BERT)
Hugging Face (Transformers)
Sentiment Analysis:
Brandwatch
Lexalytics
MonkeyLearn
Code Generation:
OpenAI Codex
5. 5
GitHub Copilot (GitHub)
Kite
Personal Assistants and Chatbots:
Amazon Alexa (Amazon)
Google Assistant (Google)
Microsoft Cortana (Microsoft)
These companies and their products represent some of the key players in their respective areas. They offer a variety
of applications and services using the latest advancements in artificial intelligence and machine learning.
Competitive Advantages
Neural Machine Translation: Developing a more accurate and faster translation service could provide a competitive
edge against Google Translate, Microsoft Translator, and DeepL. This could be achieved by optimizing the neural
network architecture, incorporating more language pairs, and improving context understanding.
Speech Recognition: To compete with Nuance Communications, Google Speech-to-Text, and Amazon Transcribe, a
speech recognition system would need to offer higher accuracy, lower latency, better noise cancellation, and support
for a broader range of languages and accents.
Natural Language Processing: An NLP system that can outperform OpenAI, IBM Watson, and Google Cloud
Natural Language would need to be more versatile, capable of understanding complex language structures, and have
a better ability to handle domain-specific knowledge or jargon.
Computer-Assisted Medical Diagnosis: To be competitive against Zebra Medical Vision, Aidoc, and PathAI, a
computer-assisted medical diagnosis system should offer higher accuracy in predicting treatments, seamless
integration with existing healthcare systems, and a focus on data privacy and security.
Image Processing: A system that can rival Google Cloud Vision, Amazon Rekognition, and Microsoft Azure
Cognitive Services would need to provide more accurate image recognition, better contextual understanding, and
possibly offer real-time image analysis capabilities.
Automated Video Transcription: To compete with Rev.com, Otter.ai, and Trint, a video transcription system should
offer faster and more accurate transcriptions, support for multiple languages, and possibly even include real-time
transcription capabilities.
Language Modeling: To surpass OpenAI (GPT-3), Google AI (BERT), and Hugging Face (Transformers), a
language modeling system should be able to generate more coherent, contextually accurate, and creative text, while
using fewer computational resources.
Sentiment Analysis: A sentiment analysis system that can outperform Brandwatch, Lexalytics, and MonkeyLearn
would need to have better accuracy in detecting subtle emotions, be able to process a larger volume of text, and
support multiple languages.
Code Generation: In order to compete with OpenAI Codex, GitHub Copilot, and Kite, a code generation system
should be able to understand a broader range of software requirements, generate more efficient and error-free code,
and support a wider array of programming languages and frameworks.
Personal Assistants and Chatbots: To compete against Amazon Alexa, Google Assistant, and Microsoft Cortana, AI-
driven personal assistants or chatbots would need to demonstrate superior natural language understanding, more
personalized responses, and better integration with various platforms and services.
By focusing on these competitive advantages, the proposed applications, products, or services can differentiate
themselves from existing industry players, providing users with enhanced capabilities and improved user
experiences.
6. 6
Metaverse Case Study
Meta Patent US11302063 3D conversations in an artificial reality environment
(https://patents.google.com/patent/US11302063)
A 3D conversation system can facilitate 3D conversations in an augmented reality environment, allowing
conversation participants to appear as if they are face-to-face. The 3D conversation system can accomplish this with
a pipeline of data processing stages, which can include calibrate, capture, tag and filter, compress, decompress,
reconstruct, render, and display stages. Generally, the pipeline can capture images of the sending user, create
intermediate representations, transform the representations to convert from the orientation the images were taken
from to a viewpoint of the receiving user, and output images of the sending user, from the viewpoint of the receiving
user, in synchronization with audio captured from the sending user. Such a 3D conversation can take place between
two or more sender/receiving systems and, in some implementations can be mediated by one or more server systems.
In various configurations, stages of the pipeline can be customized based on a conversation context.
Main Objectives
Enhance communication: Improve the quality of communication during video calls by providing a more immersive,
3D representation of participants, making it feel closer to an in-person experience.
Improve non-verbal communication: Enable better understanding of body language and context by presenting users
in a 3D space rather than the traditional 2D representation, allowing for more accurate interpretation of non-verbal
cues.
Enable spatial interactions: Allow users to move relative to each other in the virtual environment, mimicking the
spatial dynamics of face-to-face interactions, which can be crucial for effective communication.
Reduce intrusive technology: Minimize the distractions caused by the limitations of flat panel displays and 2D video
calling, promoting a more natural and engaging communication experience.
Efficient data processing pipeline: Implement a pipeline of data processing stages that enable the capture,
transformation, and rendering of images in real-time or with low latency (e.g., 100 ms or less) for seamless 3D
conversation experiences.
Scalability: Facilitate 3D conversations between two or more sender/receiver systems, with the potential to be
mediated by one or more server systems, ensuring the scalability of the technology for various use cases and group
sizes.
Adaptability: Utilize conversation context, such as available resources, capture/display capabilities, user settings,
and camera positions, to dynamically perform pipeline stages on different systems, optimizing the 3D conversation
experience based on the specific context.
By achieving these objectives, the patented invention aims to revolutionize video calling and bring users a more
immersive and authentic communication experience that closely resembles in-person interactions.
Technology Innovation
Obtain capture data, including color images, depth images, and audio, from one or more capture devices of an
artificial reality system.
Associate calibration data with the capture data, specifying position information for the capture devices.
Compress the capture data into a first version and transmit it to a receiving artificial reality system.
The receiving system decompresses the first version into a second version, containing color data, depth data, and
audio data.
Generate a 3D representation using the second version of the capture data, based on the depth data.
7. 7
Render one or more 2D images from the 3D representation at viewpoints determined for the receiving user,
including color based on the color data.
Output the audio data synchronized with the display of the 2D images.
Additional aspects of the technology involve projecting light from a wearable projection system into the user's eye,
selecting capture devices based on various factors (e.g., viewpoint, compute capability, bandwidth, battery level, or
display capabilities), assigning capture device identifiers, associating calibration data with camera identifiers,
compressing capture data based on its type, and filtering portions of the capture data to distinguish between
background areas and the sending user.
Potential Products/Services
Remote collaboration tools: The technology can be used to create more immersive remote collaboration tools for
businesses, allowing teams to work together more effectively, even when they are physically apart. By providing a
3D representation of participants and enabling spatial interactions, the technology can help recreate the in-person
experience during virtual meetings, workshops, or brainstorming sessions.
Telemedicine: The technology can be applied to the field of telemedicine, enabling healthcare providers to consult
with patients and other professionals in a more immersive and interactive environment. This could enhance
communication, aid in diagnosis, and improve the overall telemedicine experience for both patients and healthcare
providers.
Virtual events: The technology can be used to create more engaging virtual events, such as conferences, trade
shows, or concerts. By providing a 3D environment with spatial interactions, attendees can have more authentic
experiences, interact with each other and the event content more naturally, and form deeper connections.
Online education: The technology can enhance online learning platforms by providing a more immersive and
interactive environment for students and teachers. This could improve student engagement, facilitate better
communication between teachers and students, and support more effective collaborative learning experiences.
Virtual therapy and counseling: The technology can be applied to virtual therapy and counseling sessions,
enabling therapists and clients to have more authentic and effective communication in a 3D space. This could help
build rapport, improve non-verbal communication, and lead to more successful therapy outcomes.
Social networking: The technology can be used to create more immersive social networking platforms, allowing
users to engage with friends, family, and new connections in a more authentic and interactive 3D environment. This
could help foster deeper connections and make virtual interactions feel closer to real-life experiences.
Gaming and entertainment: The technology can be integrated into gaming and entertainment platforms, enabling
players to communicate and interact with each other in a more immersive and engaging 3D environment. This could
enhance multiplayer gaming experiences and promote more authentic social interactions within virtual worlds.
In summary, the patented technology for 3D conversations in an augmented reality environment can be applied to
various applications, products, and services, including remote collaboration tools, telemedicine, virtual events,
online education, virtual therapy, social networking, and gaming and entertainment. By providing a more immersive
and interactive communication experience, the technology has the potential to revolutionize the way people connect
and interact in the digital world.
Key Industry Players
Remote collaboration tools:
Microsoft (HoloLens, Microsoft Mesh)
Spatial
Cisco (Webex)
Zoom
Telemedicine:
8. 8
Teladoc Health
Amwell
Doctor On Demand
MDLive
Virtual events:
VirBELA
Hopin
vFairs
6Connex
Online education:
Coursera
Udacity
edX
Google (Google Classroom)
Virtual therapy and counseling:
Talkspace
BetterHelp
Headspace (AR/VR integration)
Calm (AR/VR integration)
Social networking:
Facebook (Meta, Horizon Workrooms)
Snapchat (AR/VR integration)
Twitter (AR/VR integration)
LinkedIn (AR/VR integration)
Gaming and entertainment:
Sony (PlayStation VR)
Oculus (Meta)
Valve (Valve Index)
HTC (Vive)
These key players have the potential to develop and implement the patented technology for 3D conversations in an
augmented reality environment in their respective fields, which can help revolutionize various applications, products,
and services.
Competitive Advantages
Remote collaboration tools: Compared to Microsoft (HoloLens, Microsoft Mesh), Spatial, Cisco (Webex), and
Zoom, the patented technology offers a more authentic face-to-face experience with improved non-verbal
communication and spatial interactions. This can lead to better collaboration, increased productivity, and reduced
miscommunication among teams working remotely.
Telemedicine: When compared to Teladoc Health, Amwell, Doctor On Demand, and MDLive, the patented
technology can provide a more immersive and interactive environment for healthcare consultations. This can result
in improved communication between healthcare providers and patients, better diagnostic accuracy, and a more
satisfying telemedicine experience for both parties.
Virtual events: The patented technology can offer a more engaging virtual event experience compared to VirBELA,
Hopin, vFairs, and 6Connex. By providing a 3D environment with spatial interactions, attendees can have more
authentic experiences, interact more naturally with each other and the event content, and build deeper connections
with other participants.
9. 9
Online education: Compared to Coursera, Udacity, edX, and Google (Google Classroom), the patented technology
can improve online learning platforms by creating a more immersive and interactive environment for students and
teachers. This can lead to better student engagement, more effective communication between teachers and students,
and enhanced collaborative learning experiences.
Virtual therapy and counseling: When compared to Talkspace, BetterHelp, Headspace (AR/VR integration), and
Calm (AR/VR integration), the patented technology can facilitate more authentic and effective communication
between therapists and clients in a 3D space. This can help build rapport, improve non-verbal communication, and
lead to more successful therapy outcomes.
Social networking: The patented technology can offer a more immersive social networking experience compared to
Facebook (Meta, Horizon Workrooms), Snapchat (AR/VR integration), Twitter (AR/VR integration), and LinkedIn
(AR/VR integration). By enabling users to engage with others in a more authentic and interactive 3D environment,
the technology can help foster deeper connections and make virtual interactions feel closer to real-life experiences.
Gaming and entertainment: Compared to Sony (PlayStation VR), Oculus (Meta), Valve (Valve Index), and HTC
(Vive), the patented technology can be integrated into gaming and entertainment platforms to provide a more
immersive and engaging 3D environment for communication and interaction. This can enhance multiplayer gaming
experiences and promote more authentic social interactions within virtual worlds.
In summary, the patented technology for 3D conversations in an augmented reality environment offers competitive
advantages in various applications, products, and services when compared to key industry players. By providing a
more immersive, interactive, and authentic communication experience, the technology has the potential to
revolutionize how people connect and interact in the digital world.
Web3 based FinTech Case Study
nChain Patent US10776761 Virtual currency system
(https://patents.google.com/patent/US10776761)
A plurality of nodes implemented by computing devices in a network include sender and recipient nodes. The sender
node sends, to the validation node, a request to transfer an amount of virtual currency from a sender account
(associated with transaction receipts) to a recipient account. The request includes first copies of the receipts or
references thereto. The validation node requests second copies of the receipts from at least two of the nodes, and
receives the second copies from fewer than all of the nodes. The validation node determines whether the first copies
have been tampered with by comparing the first and second copies to one another. When tampering has not occurred,
at least one new receipt is generated indicating the amount has been transferred. Then, the at least one new receipt is
forwarded to fewer than all of the nodes for storage.
Main Objectives
Traditional ecommerce relies on financial intermediaries like banks and card associations, which adds transaction
costs, delays, risks, and operational constraints for merchants. These intermediaries also require strict know-your-
customer (KYC) policies, which may impede sales conversions and negatively impact the customer experience.
Alternative payment technologies, such as e-wallets, virtual currencies, and pre-paid debit cards, have been
developed to address some of these challenges. However, they still lack one or more of the four attributes of
traditional face-to-face cash transactions: direct transmission, irreversibility, price stability, and functionally (or
effectively) unlimited liquidity. This patented invention implements a virtual currency system designed to replicate
the four attributes of face-to-face cash transactions in the digital world. By leveraging a network with a ring
topology, a virtual currency mint, and various nodes, it enables efficient, secure, and user-friendly transactions in the
ecommerce space.
Technology Innovation
This patented invention addresses the four attributes of face-to-face cash transactions in the digital world: direct
transmission, irreversibility, price stability, and effectively unlimited liquidity.
Direct transmission: The invention uses a distributed hash table (DHT) for locating and routing transaction requests
between the sender and recipient nodes. The sender node identifies the recipient node's network address by looking
up the key value in the DHT and directly routes the transaction request to the recipient node for processing.
10. 10
Irreversibility: Once the new transaction receipt has been routed to the storage node or forwarded by the validation
computing device, the transaction becomes irreversible. This feature enhances the security and integrity of the
transactions in the virtual currency network.
Price stability: While the patent description does not directly address price stability, the invention's focus on secure
and efficient transactions contributes to overall trust in the virtual currency. A trusted and reliable network may help
support price stability in the long run.
Functionally (or effectively) unlimited liquidity: The invention supports a distributed network of nodes and
computing devices, where none of the devices store copies of all the transaction receipts within the network. This
decentralized approach enables the network to scale effectively and accommodate a large volume of transactions,
thereby providing a high level of liquidity.
Furthermore, the invention's methods enhance the security and efficiency of the virtual currency transactions. It
utilizes a series of validation steps, such as comparing first and second copies of transaction receipts, verifying
signatures, and employing handshake identifiers for joining nodes in the ring-shaped overlay network. These
security measures help create a more efficient, secure, and user-friendly solution for merchants and customers in the
e-commerce space.
Potential Products/Services
E-commerce platforms: The virtual currency system can be integrated into e-commerce platforms, allowing for
secure and efficient transactions between buyers and sellers. By utilizing the system's direct transmission,
irreversibility, and price stability, these platforms can create a seamless and secure shopping experience for users.
Peer-to-peer (P2P) payment services: The virtual currency system can be used to develop P2P payment services
that enable users to send and receive money directly, quickly, and securely. These services can provide an
alternative to traditional banking and payment systems, especially in regions with limited access to traditional
financial infrastructure.
Remittance services: The virtual currency system can be applied to create cost-effective and efficient remittance
services for international money transfers. The system's direct transmission and irreversibility features can help
reduce transaction fees and processing times associated with cross-border payments.
Micropayment solutions: The virtual currency system can facilitate micropayments for digital content and services,
such as pay-per-view articles, in-app purchases, or tipping content creators. The system's effectively unlimited
liquidity and price stability features make it suitable for handling small transactions with minimal fees.
Digital wallets and payment gateways: The virtual currency system can be incorporated into digital wallets and
payment gateways, allowing users to store and manage their virtual currency securely. Merchants can also use these
payment gateways to accept virtual currency payments from customers, expanding their customer base and
providing an alternative payment method.
Decentralized finance (DeFi) platforms: The virtual currency system can be employed to develop DeFi platforms
that offer various financial services such as lending, borrowing, and staking. The system's attributes can contribute
to the stability and security of these platforms, attracting users and fostering growth in the DeFi space.
In summary, the patented invention can be applied to various applications, products, and services in the fintech
space, including e-commerce platforms, P2P payment services, remittance services, micropayment solutions, digital
wallets, payment gateways, and DeFi platforms. By leveraging the four attributes of face-to-face cash transactions,
this virtual currency system can create efficient, secure, and user-friendly solutions for both merchants and
customers in the digital world.
Key Industry Players
E-commerce platforms:
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Amazon
eBay
Shopify
Alibaba Group
Rakuten
Peer-to-peer (P2P) payment services:
PayPal (Venmo)
Square Inc. (Cash App)
Zelle
TransferWise (Wise)
Revolut
Remittance services:
Western Union
MoneyGram
Ria Money Transfer
Remitly
WorldRemit
Micropayment solutions:
Coil
Brave Software (Brave Browser and Basic Attention Token)
Flattr
SatoshiPay
BitPay
Digital wallets and payment gateways:
Apple Pay
Google Pay
Samsung Pay
Coinbase Commerce
Stripe
Decentralized finance (DeFi) platforms:
MakerDAO
Compound
Aave
Uniswap
Synthetix
These key players have the potential to integrate the virtual currency system into their existing products and services
or develop new solutions leveraging the technology. Collaboration or competition among these companies will help
drive innovation and adoption of the virtual currency system across various industries and markets.
Competitive Advantages
E-commerce platforms: Integrating the virtual currency system into existing e-commerce platforms can provide a
more secure, efficient, and faster transaction process. This can help platforms like Amazon, eBay, Shopify, Alibaba
Group, and Rakuten differentiate themselves from competitors and offer a unique selling proposition.
Peer-to-peer (P2P) payment services: By adopting the virtual currency system, P2P payment services like PayPal
(Venmo), Square Inc. (Cash App), Zelle, TransferWise (Wise), and Revolut can offer users the benefits of direct
transmission, irreversibility, and price stability. This can help them stand out from traditional banking services and
attract more users, especially in areas with limited access to financial infrastructure.
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Remittance services: The virtual currency system can help remittance services like Western Union, MoneyGram,
Ria Money Transfer, Remitly, and WorldRemit reduce transaction fees and processing times associated with cross-
border payments. This can make them more competitive against other remittance providers and attract more
customers seeking cost-effective and efficient international money transfer solutions.
Micropayment solutions:
Micropayment solutions like Coil, Brave Software (Brave Browser and Basic Attention Token), Flattr, SatoshiPay,
and BitPay can benefit from the virtual currency system's effectively unlimited liquidity and price stability features.
This can enable them to handle small transactions with minimal fees, making them more appealing to users and
content creators.
Digital wallets and payment gateways:
Incorporating the virtual currency system into digital wallets and payment gateways like Apple Pay, Google Pay,
Samsung Pay, Coinbase Commerce, and Stripe can provide users with a secure and efficient way to store and
manage their virtual currency. Merchants can also benefit from accepting virtual currency payments, expanding their
customer base, and offering an alternative payment method that may attract new customers.
Decentralized finance (DeFi) platforms:
DeFi platforms like MakerDAO, Compound, Aave, Uniswap, and Synthetix can leverage the virtual currency
system's attributes to enhance the stability and security of their platforms. This can help them attract more users and
foster growth in the DeFi space, ultimately making their platforms more competitive within the market.
By leveraging the virtual currency system's four attributes, these key industry players can differentiate themselves
from competitors and offer unique, efficient, and secure solutions that attract more users and drive innovation in
their respective markets.