Self-learning machines can analyze big data from business & from digitized real world (IoT) rapidly and objectively in a trusted way using Blockchain than human beings (AI) to create additional value (Big Data).
Self-learning machines can analyze big data from business & from digitized real world (IoT) rapidly and objectively in a trusted way using Blockchain than human beings (AI) to create additional value (Big Data).
1. Blockchain/Big Data/AI/IoT:
Blockchain Components
Blockchain Reference Architecture
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Blockchain Use Cases
Blockchain 3.0
Emerging Blockchain Technology
Big Data Introduction
Big Data Analysis Flow
Big Data Use Cases
IoT Introduction
IoT Use Cases
IoT Analytics
Challenges of IoT Big Data Analytics Applications
Artificial Intelligence Overview
Artificial Intelligence Revolution
Deep Learning Introduction
Deep Learning Use Cases
Automated Skin Cancer Classification
Automated Diabetic Retinopathy Classification
Portable Ultrasound Devices
Big Data in IoT & Deep Learning
The Fourth Industrial Revolution?
AI Investment
IoT Startups by Industry & Patents
AI Startups by Industry & Patents
Blockchain Startups by Industry & Patents
Blockchain + IoT Integration
Blockchain + IoT Use Cases: IIoT & SCM
Blockchain + AI Integration
Blockchain + AI Integration Demo
Blockchain + Big Data Integration
Blockchain + Big Data + AI+ IoT Integration Example
Contents
Blockchain Components
Blockchain Reference Architecture
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Blockchain Use Cases
Blockchain 3.0
Emerging Blockchain Technology
Big Data Introduction
Big Data Analysis Flow
Big Data Use Cases
IoT Introduction
IoT Use Cases
IoT Analytics
Challenges of IoT Big Data Analytics Applications
Artificial Intelligence Overview
Artificial Intelligence Revolution
Deep Learning Introduction
Deep Learning Use Cases
Automated Skin Cancer Classification
Automated Diabetic Retinopathy Classification
Portable Ultrasound Devices
Big Data in IoT & Deep Learning
The Fourth Industrial Revolution?
AI Investment
Blockchain ICO
IoT Startups by Industry & Patents
AI Startups by Industry & Patents
Blockchain Startups by Industry & Patents
Blockchain + IoT Integration
Blockchain + IoT Use Cases: IIoT & SCM
Blockchain + AI Integration
Blockchain + AI Integration Demo
Blockchain + Big Data Integration
Blockchain + Big Data + AI+ IoT Integration
Xanadu based Blockchain + Big Data + AI+ IoT Integration
Xanadu Functionality
Xanadu based Big Data Archive
Xanadu Performance BMT
Xanadu Commodity Storage System Use Case
Xanadu Cloud Computing Use Case
Xanadu + Hadoop + Deep Learning Integration Demo
Xanadu based Medical CBIR System
Xanadu based Medical CBIR System Demo for Diabetic Retinopathy Diagnosis
Advantage of Xanadu + Blockchain Integration
Xanadu + Blockchain Integration Demo
Internet of Things (IoT) patents can provide insights regarding the state of the art and technical details of the IoTinnovations. Following patent analysis is based on TechIPm’s patent research for the most promising IoT startups that are listed in CB Insights’ 2017 The Industrial IoT: 125+ Startups Report (https://www.cbinsights.com/research/top-startups-iiot/).
Blockchain Seoul 2018 Seminar
Blockchain Components
Blockchain Reference Architecture
Example of Blockchain + Big Data + AI+ IoT Integration System
Xanadu based Blockchain + Big Data + AI+ IoT Integration
Xanadu Functionality
Xanadu based Big Data Archive
Xanadu Performance BMT
Xanadu Commodity Storage System Use Case
Xanadu Cloud Computing Use Case
Xanadu + Hadoop + Deep Learning Integration Demo
Xanadu based Medical CBIR System
Xanadu based Medical CBIR System Demo for Diabetic Retinopathy Diagnosis
Xanadu based Medical CBIR System Demo for Chest X-ray Diagnosis
Xanadu + Blockchain Integration Demo
Advantage of Xanadu + Blockchain Integration
Xanadu + Blockchain Integration Implementation
Xanadu for Decentralized Cloud Storage
The Fourth Industrial Revolution?
Blockchain Components
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Big Data Use Cases
Big Data Analysis Flow
Artificial Intelligence Revolution
Deep Learning Introduction
Future of AI
Blockchain Innovation Checkpoint
AI Innovation Checkpoint
AI Innovation Frontline: Emotion AI
AI Innovation Frontline: AI Chatbot
AI Innovation Frontline: 3D Recognition
Block Innovation Frontline: DeFi
Block Innovation Frontline: Issues with Public Chain
Blockchain + AI: Blockchain for AI Business Cases
Blockchain + AI: AI for Blockchain Business Cases
Example of Blockchain + AI + Big Data Integration System
Business Model Canvas
Blockchain Business Model Canvas
Fourth Industrial Revolution & Data Economy
AI/Blockchain/IoT/Big Data Introduction
AI/Blockchain/IoT Technology Innovation Insights from Patents
AI/Blockchain/IoT Technology Innovation Frontline
AI/Blockchain/IoT Technology Innovation vs. Privacy Protection
AI/Blockchain/IoT Business Strategy & BM Development
Startup Strategy
AI + Blockchain + IoT Technology Convergence Introduction
AI + Blockchain + IoT Convergence System Development Demo
AI + Blockchain + IoT Convergence System for Digital New Deal
Self-learning machines can analyze big data from business & from digitized real world (IoT) rapidly and objectively in a trusted way using Blockchain than human beings (AI) to create additional value (Big Data).
1. Blockchain/Big Data/AI/IoT:
Blockchain Components
Blockchain Reference Architecture
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Blockchain Use Cases
Blockchain 3.0
Emerging Blockchain Technology
Big Data Introduction
Big Data Analysis Flow
Big Data Use Cases
IoT Introduction
IoT Use Cases
IoT Analytics
Challenges of IoT Big Data Analytics Applications
Artificial Intelligence Overview
Artificial Intelligence Revolution
Deep Learning Introduction
Deep Learning Use Cases
Automated Skin Cancer Classification
Automated Diabetic Retinopathy Classification
Portable Ultrasound Devices
Big Data in IoT & Deep Learning
The Fourth Industrial Revolution?
AI Investment
IoT Startups by Industry & Patents
AI Startups by Industry & Patents
Blockchain Startups by Industry & Patents
Blockchain + IoT Integration
Blockchain + IoT Use Cases: IIoT & SCM
Blockchain + AI Integration
Blockchain + AI Integration Demo
Blockchain + Big Data Integration
Blockchain + Big Data + AI+ IoT Integration Example
Contents
Blockchain Components
Blockchain Reference Architecture
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Blockchain Use Cases
Blockchain 3.0
Emerging Blockchain Technology
Big Data Introduction
Big Data Analysis Flow
Big Data Use Cases
IoT Introduction
IoT Use Cases
IoT Analytics
Challenges of IoT Big Data Analytics Applications
Artificial Intelligence Overview
Artificial Intelligence Revolution
Deep Learning Introduction
Deep Learning Use Cases
Automated Skin Cancer Classification
Automated Diabetic Retinopathy Classification
Portable Ultrasound Devices
Big Data in IoT & Deep Learning
The Fourth Industrial Revolution?
AI Investment
Blockchain ICO
IoT Startups by Industry & Patents
AI Startups by Industry & Patents
Blockchain Startups by Industry & Patents
Blockchain + IoT Integration
Blockchain + IoT Use Cases: IIoT & SCM
Blockchain + AI Integration
Blockchain + AI Integration Demo
Blockchain + Big Data Integration
Blockchain + Big Data + AI+ IoT Integration
Xanadu based Blockchain + Big Data + AI+ IoT Integration
Xanadu Functionality
Xanadu based Big Data Archive
Xanadu Performance BMT
Xanadu Commodity Storage System Use Case
Xanadu Cloud Computing Use Case
Xanadu + Hadoop + Deep Learning Integration Demo
Xanadu based Medical CBIR System
Xanadu based Medical CBIR System Demo for Diabetic Retinopathy Diagnosis
Advantage of Xanadu + Blockchain Integration
Xanadu + Blockchain Integration Demo
Internet of Things (IoT) patents can provide insights regarding the state of the art and technical details of the IoTinnovations. Following patent analysis is based on TechIPm’s patent research for the most promising IoT startups that are listed in CB Insights’ 2017 The Industrial IoT: 125+ Startups Report (https://www.cbinsights.com/research/top-startups-iiot/).
Blockchain Seoul 2018 Seminar
Blockchain Components
Blockchain Reference Architecture
Example of Blockchain + Big Data + AI+ IoT Integration System
Xanadu based Blockchain + Big Data + AI+ IoT Integration
Xanadu Functionality
Xanadu based Big Data Archive
Xanadu Performance BMT
Xanadu Commodity Storage System Use Case
Xanadu Cloud Computing Use Case
Xanadu + Hadoop + Deep Learning Integration Demo
Xanadu based Medical CBIR System
Xanadu based Medical CBIR System Demo for Diabetic Retinopathy Diagnosis
Xanadu based Medical CBIR System Demo for Chest X-ray Diagnosis
Xanadu + Blockchain Integration Demo
Advantage of Xanadu + Blockchain Integration
Xanadu + Blockchain Integration Implementation
Xanadu for Decentralized Cloud Storage
The Fourth Industrial Revolution?
Blockchain Components
Blockchain Platforms: Ethereum
Blockchain Platforms: Hyperledger
Big Data Use Cases
Big Data Analysis Flow
Artificial Intelligence Revolution
Deep Learning Introduction
Future of AI
Blockchain Innovation Checkpoint
AI Innovation Checkpoint
AI Innovation Frontline: Emotion AI
AI Innovation Frontline: AI Chatbot
AI Innovation Frontline: 3D Recognition
Block Innovation Frontline: DeFi
Block Innovation Frontline: Issues with Public Chain
Blockchain + AI: Blockchain for AI Business Cases
Blockchain + AI: AI for Blockchain Business Cases
Example of Blockchain + AI + Big Data Integration System
Business Model Canvas
Blockchain Business Model Canvas
Fourth Industrial Revolution & Data Economy
AI/Blockchain/IoT/Big Data Introduction
AI/Blockchain/IoT Technology Innovation Insights from Patents
AI/Blockchain/IoT Technology Innovation Frontline
AI/Blockchain/IoT Technology Innovation vs. Privacy Protection
AI/Blockchain/IoT Business Strategy & BM Development
Startup Strategy
AI + Blockchain + IoT Technology Convergence Introduction
AI + Blockchain + IoT Convergence System Development Demo
AI + Blockchain + IoT Convergence System for Digital New Deal
Energy IIoT - Industrial Internet of Things (IIoT) in Decentralized Digital O...crlima10
This presentation introduces the framework for an Industrial Internet of Things (IIoT) convergence towards edge/fog computing. It also defines new industry concepts of "Decentralized Digital Oilfield -DDOF" with semi-autonomous intelligent IIoT operation technology (OT), enabled by Blockchain.
What we got covered?
1) What Is Industrial IoT
2) Application of Industrial IOT
3) Machine To Machine (M2M)
4) Benefits of Industrial IoT
5) Vendors in Industrial IoT
6) Features of Industrial IoT
Interplay of Big Data and IoT - StampedeCon 2016StampedeCon
Big Data and IoT are changing the world. The big question is how Big Data and IoT are related? This presentation explores the synergy of Big Data and IoT. We will anatomize Big Data and IoT separately, in terms of what, which, why, where, when, who, how and how much. We then analyze the relationship between IoT and Big Data, specifically the drilldown of how the 4Vs of Big Data (Volume, Variety, Velocity and Value) intersect with the 4Cs of IoT (Connectivity, Collection, Context and Cognition). We will dive deep to the matrix chart of the 1-to-1 mapping of individual aspects. Case studies and best practices will be discussed to further dissect the interlock in real-world business solutions.
IoT–smart contracts in data trusted exchange supplied chain based on block ch...IJECEIAES
Internet of Things (IoT) assumes a critical part in the advancement of different fields. The IoT data trusted exchange in recent year extend of uses influence an awesome request and increasing scale. In such a platform, exchange the data sets that they require and specialist organization can search. However, the enough trust as the third-party mediators for data exchange in centralized infrastructure cannot provide. This paper proposes a blockchain for IoT data trusted exchange based on decentralized solution. In particular, the fundamental standards of blockchain in verify manner, individuals can communicate with each other without a confided in mediator intermediary. Blockchain enable us to have a distributed, digital ledger. IoT (Internet of Things) sensor devices (zigbee) utilizing blockchain technology to assert public availability of temperature records, tracking location shipment, humidity, preventing damage, data immutability. The sensor devices looking the temperature, location, damage of each parcel during the shipment to completely guarantee directions. In blockchain all data is got moved from one position to another, where a smart contract assesses against the product attributes. Ethereum blockchain and smart contracts atlast it gets through knowledge a design to be copied and presents its decentralized distributed digital ledger, auditable, transparent, features visually.
1. IoT Innovation Insights from Patents
2. IoT Frontiers Insights from Patents
3. IoT Strategy Perspectives from Patents
4. IoT Innovation Exploiting Patents
5. IoT Patent Strategy
6. IoT Startup Patent Strategy
7. IoT for Business Growth Insight from Patents
8. Artificial Intelligence Innovation Insight from Patents
9. Big Data Innovation Insight from Patents
10. IoT + AI+ Big Data Integration Strategy Insight from Patents
Internet of Things & Hardware Industry Report 2016Bernard Moon
Overview of industry trends and insights of Fortune 500 companies and startups' activities in the Internet of Things (IoT) and hardware space. We cover connected home, wearables, healthcare, robotics & drones, and industrial IoT.
IoT, or the Internet of things, and the travel industry are an excellent combination. IoT refers to everyday common items that have inbuilt internet connectivity to improve their utility. In this slideshow, you will get to know about internet of things and the travel industry.
Smart dust, machine learning, and augmented reality are just a few technologies arriving within the next few years. As our devices become more intelligent, how will we keep up? We'll all learn new ways to see and interact with our digital environment.
What Is The Artificial Intelligence Of Things? When AI Meets IoTBernard Marr
When Internet of Things (IoT) and Artificial Intelligence (AI) combine you get AIoT—basically having a machine learning algorithm that can make sense of the data that internet of things devices gather. There are many practical examples of AIoT in use today from smart retail to fleet management to autonomous vehicles and smart delivery robots.
Each year Wing surveys the IoT landscape through our IoT Startup State of the Union. We do this to understand what is happening beyond the headlines, and share these insights with our community. This year, we expanded our data set to 3670 deals, across 68 IoT sub-categories, between 2013 and 2017.
Patents are a good information resource for obtaining the state of the art of deep learning for digital twin technology innovation insights. Patents that specifically describe the major digital twin technologies/applications are a good indicator of the digital twin technology innovations in a specific innovation entity. To find the digital twin technology innovation status, patent applications in the USPTO as of September 15, 2021 that specifically describe the major technologies/applications in digital twin are searched and reviewed. 190 published patent applications that are related to the key digital twin technology innovation are selected for detail analysis.
Following figure shows the digital twin patent application landscape with respect to the innovation entity. As shown in the figure, the key digital twin innovation entities are General Electric, Siemens, Johnson Controls Technology, IBM, Toyota, CohesionIB, Honeywell, Philips, Rockwell Automation Technologies, and PTC.
Artificial Intelligence and IoT @ BoschPavlin Dobrev
Presentation about Bosch vision of Artificial Intelligence #AI http://bosch-ai.com and Internet of Things #IoT http://iot.bosch.com at Software University (softuni.bg) event
An AIoT is not a simple AI+IoT but uses artificial intelligence, Internet of Things and other technologies. It is based on big data and cloud computing. It uses semiconductor as the algorithm carrier, network security technology as the implementation guarantee, and 5G as the catalyst, knowledge and intelligence for integration.
Evolution of Internet of Things (IoT) Ecosystem - Potential in IndiaJayanth Kolla
This is India's first, and one of the world's first market-specific industry analysis report on Internet of Things (IoT) domain.
This report evaluates the global developments in the IoT space. And, delves deeper into the current state, growth potential and future outlook of IoT ecosystem evolution in India. This report assesses India as a potential market and innovation hub for IoT based products and solutions.
This is the Executive Summary and ToC of the full report
Self-learning machines can analyze big data from business & from digitized real world (IoT) rapidly and objectively in a trusted way using Blockchain than human beings (AI) to create additional value (Big Data).
New IoT Product/Service Development
Even though the IoT is getting a huge attention recently the concept of interconnected billions of devices is not new and has been under development for over 10 years. Thus, there are a large number of related patented technologies that can be exploited for developing new products/services, and thus, new business for the emerging IoT market.
Energy IIoT - Industrial Internet of Things (IIoT) in Decentralized Digital O...crlima10
This presentation introduces the framework for an Industrial Internet of Things (IIoT) convergence towards edge/fog computing. It also defines new industry concepts of "Decentralized Digital Oilfield -DDOF" with semi-autonomous intelligent IIoT operation technology (OT), enabled by Blockchain.
What we got covered?
1) What Is Industrial IoT
2) Application of Industrial IOT
3) Machine To Machine (M2M)
4) Benefits of Industrial IoT
5) Vendors in Industrial IoT
6) Features of Industrial IoT
Interplay of Big Data and IoT - StampedeCon 2016StampedeCon
Big Data and IoT are changing the world. The big question is how Big Data and IoT are related? This presentation explores the synergy of Big Data and IoT. We will anatomize Big Data and IoT separately, in terms of what, which, why, where, when, who, how and how much. We then analyze the relationship between IoT and Big Data, specifically the drilldown of how the 4Vs of Big Data (Volume, Variety, Velocity and Value) intersect with the 4Cs of IoT (Connectivity, Collection, Context and Cognition). We will dive deep to the matrix chart of the 1-to-1 mapping of individual aspects. Case studies and best practices will be discussed to further dissect the interlock in real-world business solutions.
IoT–smart contracts in data trusted exchange supplied chain based on block ch...IJECEIAES
Internet of Things (IoT) assumes a critical part in the advancement of different fields. The IoT data trusted exchange in recent year extend of uses influence an awesome request and increasing scale. In such a platform, exchange the data sets that they require and specialist organization can search. However, the enough trust as the third-party mediators for data exchange in centralized infrastructure cannot provide. This paper proposes a blockchain for IoT data trusted exchange based on decentralized solution. In particular, the fundamental standards of blockchain in verify manner, individuals can communicate with each other without a confided in mediator intermediary. Blockchain enable us to have a distributed, digital ledger. IoT (Internet of Things) sensor devices (zigbee) utilizing blockchain technology to assert public availability of temperature records, tracking location shipment, humidity, preventing damage, data immutability. The sensor devices looking the temperature, location, damage of each parcel during the shipment to completely guarantee directions. In blockchain all data is got moved from one position to another, where a smart contract assesses against the product attributes. Ethereum blockchain and smart contracts atlast it gets through knowledge a design to be copied and presents its decentralized distributed digital ledger, auditable, transparent, features visually.
1. IoT Innovation Insights from Patents
2. IoT Frontiers Insights from Patents
3. IoT Strategy Perspectives from Patents
4. IoT Innovation Exploiting Patents
5. IoT Patent Strategy
6. IoT Startup Patent Strategy
7. IoT for Business Growth Insight from Patents
8. Artificial Intelligence Innovation Insight from Patents
9. Big Data Innovation Insight from Patents
10. IoT + AI+ Big Data Integration Strategy Insight from Patents
Internet of Things & Hardware Industry Report 2016Bernard Moon
Overview of industry trends and insights of Fortune 500 companies and startups' activities in the Internet of Things (IoT) and hardware space. We cover connected home, wearables, healthcare, robotics & drones, and industrial IoT.
IoT, or the Internet of things, and the travel industry are an excellent combination. IoT refers to everyday common items that have inbuilt internet connectivity to improve their utility. In this slideshow, you will get to know about internet of things and the travel industry.
Smart dust, machine learning, and augmented reality are just a few technologies arriving within the next few years. As our devices become more intelligent, how will we keep up? We'll all learn new ways to see and interact with our digital environment.
What Is The Artificial Intelligence Of Things? When AI Meets IoTBernard Marr
When Internet of Things (IoT) and Artificial Intelligence (AI) combine you get AIoT—basically having a machine learning algorithm that can make sense of the data that internet of things devices gather. There are many practical examples of AIoT in use today from smart retail to fleet management to autonomous vehicles and smart delivery robots.
Each year Wing surveys the IoT landscape through our IoT Startup State of the Union. We do this to understand what is happening beyond the headlines, and share these insights with our community. This year, we expanded our data set to 3670 deals, across 68 IoT sub-categories, between 2013 and 2017.
Patents are a good information resource for obtaining the state of the art of deep learning for digital twin technology innovation insights. Patents that specifically describe the major digital twin technologies/applications are a good indicator of the digital twin technology innovations in a specific innovation entity. To find the digital twin technology innovation status, patent applications in the USPTO as of September 15, 2021 that specifically describe the major technologies/applications in digital twin are searched and reviewed. 190 published patent applications that are related to the key digital twin technology innovation are selected for detail analysis.
Following figure shows the digital twin patent application landscape with respect to the innovation entity. As shown in the figure, the key digital twin innovation entities are General Electric, Siemens, Johnson Controls Technology, IBM, Toyota, CohesionIB, Honeywell, Philips, Rockwell Automation Technologies, and PTC.
Artificial Intelligence and IoT @ BoschPavlin Dobrev
Presentation about Bosch vision of Artificial Intelligence #AI http://bosch-ai.com and Internet of Things #IoT http://iot.bosch.com at Software University (softuni.bg) event
An AIoT is not a simple AI+IoT but uses artificial intelligence, Internet of Things and other technologies. It is based on big data and cloud computing. It uses semiconductor as the algorithm carrier, network security technology as the implementation guarantee, and 5G as the catalyst, knowledge and intelligence for integration.
Evolution of Internet of Things (IoT) Ecosystem - Potential in IndiaJayanth Kolla
This is India's first, and one of the world's first market-specific industry analysis report on Internet of Things (IoT) domain.
This report evaluates the global developments in the IoT space. And, delves deeper into the current state, growth potential and future outlook of IoT ecosystem evolution in India. This report assesses India as a potential market and innovation hub for IoT based products and solutions.
This is the Executive Summary and ToC of the full report
Self-learning machines can analyze big data from business & from digitized real world (IoT) rapidly and objectively in a trusted way using Blockchain than human beings (AI) to create additional value (Big Data).
New IoT Product/Service Development
Even though the IoT is getting a huge attention recently the concept of interconnected billions of devices is not new and has been under development for over 10 years. Thus, there are a large number of related patented technologies that can be exploited for developing new products/services, and thus, new business for the emerging IoT market.
Contents
I. AI, Blockchain, IoT, and Their Convergence Technology Innovation Status
II. AI, Blockchain, IoT Convergence Use Case System Implementation Examples
1. Blockchain-based Privacy-Preserving Federated Learning System
2. Blockchain-based Decentralized IoT & AI Data Marketplace
3. Blockchain-based Trustworthy AI & IoT Systems
4. Blockchain-based Decentralized Parallel Edge Machine Learning
5. Predictive Maintenance Platform for Industrial Machine using Industrial IoT
6. AI+Blockchain System for Car Sharing Service
7. Connected Autonomous Vehicle Communication Management System
8. 5G-based AI+Blockchain+IoT Edge Computing System
https://www.learntek.org/blog/top-10-technology-trends-in-2019/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
Xanadu Functionality
Xanadu based Big Data Archive
Xanadu Performance BMT
Xanadu Commodity Storage System Use Case
Xanadu Cloud Computing Use Case
Xanadu + Hadoop + Deep Learning Integration Demo
Xanadu based Medical CBIR System
Xanadu based Medical CBIR System Demo for Diabetic Retinopathy Diagnosis
Xanadu based Medical CBIR System Demo for Chest X-ray Diagnosis
Xanadu + Blockchain Integration Demo
Advantage of Xanadu + Blockchain Integration
Xanadu + Blockchain Integration Implementation
Xanadu for Decentralized Cloud Storage
1. New Patent Development Opportunity Analysis
2. New Patent Preparation & Prosecution Strategy
3. Strategic Patent Development Exploiting Existing Patents
4. Monetization Exploiting Strategically Packaged Patent Portfolio
5. Development of Strategically Packaged Patent Portfolio Best Practice
6. Methodology for Developing Strategically Packaged Patent Portfolio
IoT Solutions - Dashboarding Real-Time Data | Internet of Things | IoT Techno...Edureka!
** IoT Certification Training: https://www.edureka.co/iot-certification-training **
This edureka live PPT on "IoT Solutions" will help you learn the visualization of real-time sensor data from your Raspberry Pi to a cloud-based dashboard.
This IoT tutorial PPT helps you to learn the following topics:
1. Perception layer
2. Application layer
3. IoT ecosystem
4. Data visualization
5. Hands-on
Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV
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Top 10 Emerging Technologies in the World.pdfUmair Sheikh
Top 10 Emerging Technologies 2022 consists of Top emerging technologies and top technological trends and Top Latest Emerging Technologies in year 2021 and 2022
** Edureka IoT Training: https://www.edureka.co/iot-certification-training**
This Edureka tutorial video on "Iot Technology" will help you grasp the outline of Internet of Things, and let you relate to how it is revolutionizing the world today. This IoT tutorial helps you learn the following topics:
1. Vision of IoT
2. “Things” in IoT
3. IoT Technology Stack
4. IoT Ecosystem
5. IoT Demo – Media Center using Raspberry Pi
6. Prospects & Scopes
Based on the IoT innovation analysis and insights for the future IoT innovation/business directions, the IoT products/services innovation and patent portfolios development strategy can be developed by exploiting the system evolution principle (e.g. TRIZ) for each subsystem and the system as a whole and scenario planning methodology.
Existing patents can be exploited for the development of the disruptive IoT products/services using the “Blue Ocean Patent Strategy.” The basic principle in the Blue Ocean Patent Strategy is to exploit patents to achieve the value innovation by using the patented technologies to create new values, and thus, to provide new products/services. The exploitation of existing patented technologies not only allows the low cost IoT product/service development but also provides the protection against competitors’ infringement. Existing patents can also be exploited for the development of a new IoT startup.
With the invention of new Li-fi technology, you will soon find light bulbs of your car, light lamps in your room, lights in subway, flashlight of your mobile and any other light source are providing you internet access at very high speed.Li-fi technology is the another milestone in the history of information technology. You have got the idea that Li-Fi Technology is something light. Yes, Li-fi technology or light-fidelity technology transmits data wirelessly at high speeds with the use of light emitting diodes.
Gilbert + Tobin published a collection of insights across a range of topical issues in innovation including blockchain, robotics and automation, data and the internet of things as well as managing IP in a digital world. http://bit.ly/1TervxV
Similar to Blockchain Based 4th Industrial Revolution Key Technologies Integration Use Cases (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
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.
Represented by ChatGPT, Artificial Intelligence (AI) has become increasingly important in business over the past few years, and it has the potential to revolutionize many industries. One way to maximize the business value of AI is through patents. This webinar is designed to explore the strategy and practical ways to maximize the business value creation of AI utilizing patents.
Agenda
The state of the art AI innovation
AI innovation insight from patents
Commercial utilization of AI patents
Financial utilization of AI patents
AI patent development considering future technology/market evolution
IPwe SIAM platform for maximizing AI business value creation utilizing patents
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 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
KVA 한국기업·기술가치평가협회 주관으로 열린 웹3.0기반 메타버스 응용을 위한 NFT 가치개발과 가치평가 특강
내용:
메타버스, 웹3, NFT에 대한 기본을 이해하고 웹3 기반 메타버스 응용을 위한 NFT 가치개발에 대한 동향과 전망을 알아보고 NFT 수익화를 위한 NFT 지적재산(IP) 개발과 NFT 가치평가에 대해 알아본다.
세부내용:
기본과정 (1시간)
메타버스의 이해
웹3의 이해
NFT의 이해
고급과정 (1시간)
NFT 웹3 기반 메타버스 응용을 위한 가치개발
웹3 기반 메타버스 응용 NFT 지적재산 개발
웹3 기반 메타버스 응용 NFT에 의한 수익화
웹3 기반 메타버스 응용 NFT의 가치평가
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.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.