AI, Knowledge Representation and Graph Databases - Key Trends in Data ScienceOptum
Knowledge Representation is a key focus for most modern AI texts. Many AI experts feel that over half of their work is understanding how to find the right knowledge structures to build intelligent agents that can continuously learn and respond to changing events in their world. In 2012, a paper published by Google started a consolidation of the many diverse forms of knowledge representation into a single general-purpose structure called a labeled property graph.
This talk will describe the key events behind this movement and show how a new generation of data scientist will be needed to build and maintain corporate knowledge graphs that contain a uniform, normalized and highly connected data sets for used by researchers and intelligent agents. We will also discuss the challenges of transferring siloed project-knowledge to reusable structures.
Overview of structured search technology. Using the structure of a document to create better search results for document search and retrieval.
How both search precision and recall is improved when the structure of a document is used.
How a keyword match in a title of a document can be used to boost the search score.
Case studies with the eXist native XML database.
Steps to set up a pilot project.
How software developers need to manage metadata and data dictionaries to make software integration faster and more cost effective. This presentation is a general overview of the concepts around data semantics for college-level students. This presentation was originally created for a seminar at Carleton College.
What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases.
Talk by George Anadiotis. Connected Data London Meetup June 29th 2020.
Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in instilling the “best tool for the job” mindset.
After relational, key-value, document, and columnar, the latest link in this evolutionary proliferation of data structures is graph. Graph analytics, Graph AI, Knowledge Graphs and Graph Databases have been making waves, included in hype cycles for the last couple of years.
The Year of the Graph marked the beginning of it all before the Gartners of the world got in the game. The Year of the Graph is a term coined to convey the fact that the time has come for this technology to flourish.
The eponymous article that set the tone was published in January 2018 on ZDNet by domain expert George Anadiotis. George has been working with, and keeping an eye on, all things Graph since the early 2000s. He was one of the first to note the continuing rise of Graph Databases, and to bring this technology in front of a mainstream audience.
The Year of the Graph has been going strong since 2018. In August 2018, Gartner started including Graph in its hype cycles. Ever since, Graph has been riding the upward slope of the Hype Cycle.
The need for knowledge on these technologies is constantly growing. To respond to that need, the Year of the Graph newsletter was released in April 2018. In addition, a constant flow of graph-related news and resources is being shared on social media.
To help people make educated choices, the Year of the Graph Database Report was released. The report has been hailed as the most comprehensive of its kind in the market, consistently helping people choose the most appropriate solution for their use case since 2018.
The report, articles, news stream, and the newsletter have been reaching thousands of people, helping them understand and navigate this landscape. We’ll talk about the Year of the Graph, the different shapes, forms, and applications for graphs, the latest news and trends, and wrap up with an ask me anything session.
Social media monitoring with ML-powered Knowledge GraphGraphAware
Ever wondered how can be ML used to build Knowledge Graph for allowing businesses to successfully differentiate and compete today? We will show how Computer Vision, NLP/U, knowledge enrichment and graph-native algorithms fit together to build powerful insights from various unstructured data sources.
About the speakers:
Vlasta Kus - Lead Data Scientist at GraphAWare - Machine Learning, Deep Learning and Natural Language Processing expert.
Background in particle physics research at CERN. 10+ years of experience in software development (C/C++, Java, Python) and statistical data analysis.
Neo4j certified professional.
Specialised in using Machine Learning for building Knowledge Graphs (Hume @ GraphAware).
Golven Leroy - Student - I am a engineering student who is interested in everything graph. I love travelling and good food, especially when it is cheese-related and accompanied by good wine. Wannabe Gyro Gearloose, early-age spiderman fan, and beatmaker in my free time.
NODES 2019 - Neo4j Online Developer Expo & Summit - 10th October 2019
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2Connected Data World
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Parts 1 & 2
AI, Knowledge Representation and Graph Databases - Key Trends in Data ScienceOptum
Knowledge Representation is a key focus for most modern AI texts. Many AI experts feel that over half of their work is understanding how to find the right knowledge structures to build intelligent agents that can continuously learn and respond to changing events in their world. In 2012, a paper published by Google started a consolidation of the many diverse forms of knowledge representation into a single general-purpose structure called a labeled property graph.
This talk will describe the key events behind this movement and show how a new generation of data scientist will be needed to build and maintain corporate knowledge graphs that contain a uniform, normalized and highly connected data sets for used by researchers and intelligent agents. We will also discuss the challenges of transferring siloed project-knowledge to reusable structures.
Overview of structured search technology. Using the structure of a document to create better search results for document search and retrieval.
How both search precision and recall is improved when the structure of a document is used.
How a keyword match in a title of a document can be used to boost the search score.
Case studies with the eXist native XML database.
Steps to set up a pilot project.
How software developers need to manage metadata and data dictionaries to make software integration faster and more cost effective. This presentation is a general overview of the concepts around data semantics for college-level students. This presentation was originally created for a seminar at Carleton College.
What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases.
Talk by George Anadiotis. Connected Data London Meetup June 29th 2020.
Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in instilling the “best tool for the job” mindset.
After relational, key-value, document, and columnar, the latest link in this evolutionary proliferation of data structures is graph. Graph analytics, Graph AI, Knowledge Graphs and Graph Databases have been making waves, included in hype cycles for the last couple of years.
The Year of the Graph marked the beginning of it all before the Gartners of the world got in the game. The Year of the Graph is a term coined to convey the fact that the time has come for this technology to flourish.
The eponymous article that set the tone was published in January 2018 on ZDNet by domain expert George Anadiotis. George has been working with, and keeping an eye on, all things Graph since the early 2000s. He was one of the first to note the continuing rise of Graph Databases, and to bring this technology in front of a mainstream audience.
The Year of the Graph has been going strong since 2018. In August 2018, Gartner started including Graph in its hype cycles. Ever since, Graph has been riding the upward slope of the Hype Cycle.
The need for knowledge on these technologies is constantly growing. To respond to that need, the Year of the Graph newsletter was released in April 2018. In addition, a constant flow of graph-related news and resources is being shared on social media.
To help people make educated choices, the Year of the Graph Database Report was released. The report has been hailed as the most comprehensive of its kind in the market, consistently helping people choose the most appropriate solution for their use case since 2018.
The report, articles, news stream, and the newsletter have been reaching thousands of people, helping them understand and navigate this landscape. We’ll talk about the Year of the Graph, the different shapes, forms, and applications for graphs, the latest news and trends, and wrap up with an ask me anything session.
Social media monitoring with ML-powered Knowledge GraphGraphAware
Ever wondered how can be ML used to build Knowledge Graph for allowing businesses to successfully differentiate and compete today? We will show how Computer Vision, NLP/U, knowledge enrichment and graph-native algorithms fit together to build powerful insights from various unstructured data sources.
About the speakers:
Vlasta Kus - Lead Data Scientist at GraphAWare - Machine Learning, Deep Learning and Natural Language Processing expert.
Background in particle physics research at CERN. 10+ years of experience in software development (C/C++, Java, Python) and statistical data analysis.
Neo4j certified professional.
Specialised in using Machine Learning for building Knowledge Graphs (Hume @ GraphAware).
Golven Leroy - Student - I am a engineering student who is interested in everything graph. I love travelling and good food, especially when it is cheese-related and accompanied by good wine. Wannabe Gyro Gearloose, early-age spiderman fan, and beatmaker in my free time.
NODES 2019 - Neo4j Online Developer Expo & Summit - 10th October 2019
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2Connected Data World
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Parts 1 & 2
All major cloud service providers now have some ML offering. The startup costs are low-to-no. They provide seamless leverage of cloud resources for scale-ups = $’s.
Open source ML options are now common making the creation of very large models now possible. Open data sets are proliferating.
Presented at CF Machine Learning
Ordinary people included anyone who is not a Geek like myself. This book is written for ordinary people. That includes manager, marketers, technical writers, couch potatoes and so on.
Data Science and Analytics for Ordinary People is a collection of blogs I have written on LinkedIn over the past year. As I continue to perform big data analytics, I continue to discover, not only my weaknesses in communicating the information, but new insights into using the information obtained from analytics and communicating it. These are the kinds of things I blog about and are contained herein.
The Enterprise Knowledge Graph is a disruptive platform that combines emerging Big Data and Graph technologies to reinvent knowledge management inside organizations. This platform aims to organize and distribute the organization’s knowledge, and making it centralized and universally accessible to every employee. The Enterprise Knowledge Graph is a central place to structure, simplify and connect the knowledge of an organization. By removing complexity, the knowledge graph brings more transparency, openness and simplicity into organizations. That leads to democratized communications and empowers individuals to share knowledge and to make decisions based on comprehensive knowledge. This platform can change the way we work, challenge the traditional hierarchical approach to get work done and help to unleash human potential!
Graph Databases and Graph Data Science in Neo4jijtsrd
The contents include what graph databases are, their uses, notations, structure, what is neo4j, its components, what is Graph Data Science and GDS algorithms and their types in Neo4j. It contains an overview of all the features provided by neo4j like querying, visualization, remote access, etc. It will also include information about Neo4j Aura, Sandbox, Desktop, Browser and Bloom. The various tiers of maturity of GDS algorithms and their types will also be explained along with an example of each of the type of algorithms. Akanksha Junawane | Y. L. Puranik "Graph Databases and Graph Data Science in Neo4j" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42358.pdf Paper URL: https://www.ijtsrd.comcomputer-science/other/42358/graph-databases-and-graph-data-science-in-neo4j/akanksha-junawane
Reflected Intelligence: Real world AI in Digital TransformationTrey Grainger
The goal of most digital transformations is to create competitive advantage by enhancing customer experience and employee success, so giving these stakeholders the ability to find the right information at their moment of need is paramount. Employees and customers increasingly expect an intuitive, interactive experience where they can simply type or speak their questions or keywords into a search box, their intent will be understood, and the best answers and content are then immediately presented.
Providing this compelling experience, however, requires a deep understanding of your content, your unique business domain, and the collective and personalized needs of each of your users. Modern artificial intelligence (AI) approaches are able to continuously learn from both your content and the ongoing stream of user interactions with your applications, and to automatically reflect back that learned intelligence in order to instantly and scalably deliver contextually-relevant answers to employees and customers.
In this talk, we'll discuss how AI is currently being deployed across the Fortune 1000 to accomplish these goals, both in the digital workplace (helping employees more efficiently get answers and make decisions) and in digital commerce (understanding customer intent and connecting them with the best information and products). We'll separate fact from fiction as we break down the hype around AI and show how it is being practically implemented today to power many real-world digital transformations for the next generation of employees and customers.
Relationship Between Big Data & AI
Human intelligence builds up on what we read, observe, learn, sense and experience. It's our ability to store large amount of data, accumulated over years and co-relating a few data points to answer a certain question, that makes us intelligent.
Similarly for machines to replicate human intelligence, they'll need to absorb large amount of data to make an intelligent decision............... (read more)
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...Connected Data World
Do you want to learn how to use the low-hanging fruit of knowledge graphs — schema.org and JSON-LD — to annotate content and improve your SEO with semantics and entities? This hands-on workshop with one of the leading Semantic SEO practitioners will help you get started.
Graph intelligence: the future of data-driven investigationsConnected Data World
RDF and graph databases are on the rise. The performances, flexibility, and scalability of these systems are attracting a large number of organizations struggling with complex and connected data. While the graph approach offers several advantages, finding insights into the enormous volume of data remains a challenge.
In this presentation, we will introduce Graph Intelligence, an advanced combination of human and computer-based intelligence to find insights faster in complex connected datasets. We will explain why we believe this approach is the future for teams of investigators fighting financial crime, national security threats or cyber attacks.
From this presentation, you will learn:
The nature and benefits of the Graph Intelligence approach
How to build a platform leveraging graph technology
Real-life examples of money laundering and financial crimes detection and investigation
My presentation today about ChatGPT, Open AI, conversational AI, and the Future Of Work. Includes survey data from the audience. Presented at our Constellation Research Execution Network monthy Office Hours of CIOs, CDOs, and other CXOs.
Artificial Intelligence (AI) is quickly moving from a science-fiction concept to reality where machines now have the capability to perform tasks commonly associated with humans. We are starting to see our society transformed because of AI, so having a better understanding of what it is and what it is capable of doing is essential. AI helps power Amazon’s Alexa personal assistant, Google’s Deep Dream neural network, various marketing initiatives, health applications, the aviation industry, and much more. In this webinar:
- Discover what Artificial Intelligence (AI) is and how it is becoming a “machine trait.”
- Gain an appreciation of AI pioneers like John McCarthy, Alan Turing, Marvin Minsky et al.
- Learn how AI works and explore some applications that could play a role in your library.
- Reflect on the future of AI and the implications for libraries and society in general.
- Special Guest, Owen Cegielski from STEM School and Academy in Highlands Ranch, Colorado, will discuss various AI projects.
All major cloud service providers now have some ML offering. The startup costs are low-to-no. They provide seamless leverage of cloud resources for scale-ups = $’s.
Open source ML options are now common making the creation of very large models now possible. Open data sets are proliferating.
Presented at CF Machine Learning
Ordinary people included anyone who is not a Geek like myself. This book is written for ordinary people. That includes manager, marketers, technical writers, couch potatoes and so on.
Data Science and Analytics for Ordinary People is a collection of blogs I have written on LinkedIn over the past year. As I continue to perform big data analytics, I continue to discover, not only my weaknesses in communicating the information, but new insights into using the information obtained from analytics and communicating it. These are the kinds of things I blog about and are contained herein.
The Enterprise Knowledge Graph is a disruptive platform that combines emerging Big Data and Graph technologies to reinvent knowledge management inside organizations. This platform aims to organize and distribute the organization’s knowledge, and making it centralized and universally accessible to every employee. The Enterprise Knowledge Graph is a central place to structure, simplify and connect the knowledge of an organization. By removing complexity, the knowledge graph brings more transparency, openness and simplicity into organizations. That leads to democratized communications and empowers individuals to share knowledge and to make decisions based on comprehensive knowledge. This platform can change the way we work, challenge the traditional hierarchical approach to get work done and help to unleash human potential!
Graph Databases and Graph Data Science in Neo4jijtsrd
The contents include what graph databases are, their uses, notations, structure, what is neo4j, its components, what is Graph Data Science and GDS algorithms and their types in Neo4j. It contains an overview of all the features provided by neo4j like querying, visualization, remote access, etc. It will also include information about Neo4j Aura, Sandbox, Desktop, Browser and Bloom. The various tiers of maturity of GDS algorithms and their types will also be explained along with an example of each of the type of algorithms. Akanksha Junawane | Y. L. Puranik "Graph Databases and Graph Data Science in Neo4j" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42358.pdf Paper URL: https://www.ijtsrd.comcomputer-science/other/42358/graph-databases-and-graph-data-science-in-neo4j/akanksha-junawane
Reflected Intelligence: Real world AI in Digital TransformationTrey Grainger
The goal of most digital transformations is to create competitive advantage by enhancing customer experience and employee success, so giving these stakeholders the ability to find the right information at their moment of need is paramount. Employees and customers increasingly expect an intuitive, interactive experience where they can simply type or speak their questions or keywords into a search box, their intent will be understood, and the best answers and content are then immediately presented.
Providing this compelling experience, however, requires a deep understanding of your content, your unique business domain, and the collective and personalized needs of each of your users. Modern artificial intelligence (AI) approaches are able to continuously learn from both your content and the ongoing stream of user interactions with your applications, and to automatically reflect back that learned intelligence in order to instantly and scalably deliver contextually-relevant answers to employees and customers.
In this talk, we'll discuss how AI is currently being deployed across the Fortune 1000 to accomplish these goals, both in the digital workplace (helping employees more efficiently get answers and make decisions) and in digital commerce (understanding customer intent and connecting them with the best information and products). We'll separate fact from fiction as we break down the hype around AI and show how it is being practically implemented today to power many real-world digital transformations for the next generation of employees and customers.
Relationship Between Big Data & AI
Human intelligence builds up on what we read, observe, learn, sense and experience. It's our ability to store large amount of data, accumulated over years and co-relating a few data points to answer a certain question, that makes us intelligent.
Similarly for machines to replicate human intelligence, they'll need to absorb large amount of data to make an intelligent decision............... (read more)
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...Connected Data World
Do you want to learn how to use the low-hanging fruit of knowledge graphs — schema.org and JSON-LD — to annotate content and improve your SEO with semantics and entities? This hands-on workshop with one of the leading Semantic SEO practitioners will help you get started.
Graph intelligence: the future of data-driven investigationsConnected Data World
RDF and graph databases are on the rise. The performances, flexibility, and scalability of these systems are attracting a large number of organizations struggling with complex and connected data. While the graph approach offers several advantages, finding insights into the enormous volume of data remains a challenge.
In this presentation, we will introduce Graph Intelligence, an advanced combination of human and computer-based intelligence to find insights faster in complex connected datasets. We will explain why we believe this approach is the future for teams of investigators fighting financial crime, national security threats or cyber attacks.
From this presentation, you will learn:
The nature and benefits of the Graph Intelligence approach
How to build a platform leveraging graph technology
Real-life examples of money laundering and financial crimes detection and investigation
My presentation today about ChatGPT, Open AI, conversational AI, and the Future Of Work. Includes survey data from the audience. Presented at our Constellation Research Execution Network monthy Office Hours of CIOs, CDOs, and other CXOs.
Artificial Intelligence (AI) is quickly moving from a science-fiction concept to reality where machines now have the capability to perform tasks commonly associated with humans. We are starting to see our society transformed because of AI, so having a better understanding of what it is and what it is capable of doing is essential. AI helps power Amazon’s Alexa personal assistant, Google’s Deep Dream neural network, various marketing initiatives, health applications, the aviation industry, and much more. In this webinar:
- Discover what Artificial Intelligence (AI) is and how it is becoming a “machine trait.”
- Gain an appreciation of AI pioneers like John McCarthy, Alan Turing, Marvin Minsky et al.
- Learn how AI works and explore some applications that could play a role in your library.
- Reflect on the future of AI and the implications for libraries and society in general.
- Special Guest, Owen Cegielski from STEM School and Academy in Highlands Ranch, Colorado, will discuss various AI projects.
Host:
Bart Raynaud - https://www.linkedin.com/in/bart-raynaud-160a0318/
Title: AI: Past, Present, and Future
Abstract: In 1956, the term "Artificial Intelligence" was coined for a workshop at Dartmouth. Since then there has been waxing and waning enthusiasm and investment, so called "AI Winters" after hype, did not live up to reality. In late 2022, with the release of ChatGPT, and over 100 million users in just 60 days, there is a new wave of hype, investment, excitement, and increased fears of AI use by 'bad actors' for misinformation and other harms to society. What are the future trajectories as this technology is tamed and becomes routine? Are we about to enter a 'golden age' of service in business and society, as technology comes to the service sector, as it came to agriculture and manufacturing in the past?
Bio: Jim Spohrer is a retired industry executive (Apple, IBM). In the 1970's, after graduating MIT with a degree in physics, he worked at an AI startup doing speech recognition with mathematical models. In the 1980's, after completing his PhD in Computer Science/AI & Cognitive Science at Yale, he moved to California to join Apple and work on AI for Education. In the late 1990's, he joined IBM as CTO of the Venture Capital Relations group during the internet investment boom, and later started IBM Research's service research area, led IBM Global University Programs, and led IBM's open source AI efforts. Jim's most recent co-authored book, "Service in the AI Era" was published in late 2022.
Host:
Bart Raynaud (The Terraces of Los Gatos) https://www.linkedin.com/in/bart-raynaud-160a0318/
Title: AI: Past, Present, and Future
Abstract: In 1956, the term "Artificial Intelligence" was coined for a workshop at Dartmouth. Since then there has been waxing and waning enthusiasm and investment, so called "AI Winters" after hype, did not live up to reality. In late 2022, with the release of ChatGPT, and over 100 million users in just 60 days, there is a new wave of hype, investment, excitement, and increased fears of AI use by 'bad actors' for misinformation and other harms to society. What are the future trajectories as this technology is tamed and becomes routine? Are we about to enter a 'golden age' of service in business and society, as technology comes to the service sector, as it came to agriculture and manufacturing in the past?
Bio: Jim Spohrer is a retired industry executive (Apple, IBM). In the 1970's, after graduating MIT with a degree in physics, he worked at an AI startup doing speech recognition with mathematical models. In the 1980's, after completing his PhD in Computer Science/AI & Cognitive Science at Yale, he moved to California to join Apple and work on AI for Education. In the late 1990's, he joined IBM as CTO of the Venture Capital Relations group during the internet investment boom, and later started IBM Research's service research area, led IBM Global University Programs, and led IBM's open source AI efforts. Jim's most recent co-authored book, "Service in the AI Era" was published in late 2022.
Benefiting from Semantic AI along the data life cycleMartin Kaltenböck
Slides of 1 hour session of Martin Kaltenböck (CFO and Managing Partner of Semantic Web Company / PoolParty Software Ltd) on 19 March 2019 in Boston, US at the Enterprise Data World 2019, with its title: Benefiting from Semantic AI along the data life cycle.
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas?
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas? This slides will discuss the brief history of the current interesting technologies and their development to society and mankind.
Mindgrub CEO Todd Marks explains the benefits of using tablets and smart phones in the classroom. He touches on eLearning with statistics to support the idea of mobile gaming in the education system.
How AI is going to change the world _M.Mujeeb Riaz.pdfMujeeb Riaz
How AI is going to change the world?
"AI: The Future of Our World“
"AI and its Transformative Impact on the World: Understanding the Potential of Chatbots and Conversational AI"
What is Artificial Intelligence and how it works?
What are Chatbots?
What Is ChatGPT?
Difference between chatGPT 3 and chatGPT 4?
Is Jasper artificial intelligence?
What is Character AI and how it works?
How chatGPT is going to change the world?
Why we are calling ChatGPT the future?
IIPGH Webinar 1: Getting Started With Data Scienceds4good
In this webinar for ICT Professionals Ghana, we explore the concepts of data science and its motivations as a recent specialization. creating the background for how Artificial Intelligence relates to Machine Learning and to Deep Learning. We further discuss the data science technology stack and the opportunities that exist in the space.
Machine Learning for Marketers - CTAConf 2019Britney Muller
Explore CTAConf's Marketing IQ theme with a layer of AI.
You don't have to be a data scientist to think of the next genius ML application!!! ANYONE CAN!
Machine Learning is power at your fingertips! Learn more about how you can apply Machine Learning to your day to day life here.
What’s attractive in Rakuten Technology Conference 2017. (English Version)Rakuten Group, Inc.
Here is what's attractive in Rakuten Technology Conference 2017 which will be held in Rakuten Crimson House.
This includes photos of our previous conference and this year's guest speakers.
Please feel the atmosphere and participate with your friends and family.
We are looking forward to seeing you.
URL: https://professionalschool.eitdigital.eu/generative-ai-essentials
Course on Generative Al
Description:
Generative AI is a world-changing power tool that is getting better by the day. So now is the time to get truly inspired, climb up the learning curve, and unleash more of your creative potential.
Learning Topics:
* Inspiration: What is Generative AI in the context of AI's history, present, and future
* Climbing Up: Ways to accelerate your learning trajectory
* Unleashing Creativity: Ways to stay future-ready in the AI era
What You'll Take Away:
By the end of this session, you'll understand the importance of upskilling with today's generative AI tools to get more work done, both faster and at higher quality, as well as some pitfalls to avoid, all within the broader context of the past, present, and future of Artificial Intelligence (AI) and Intelligence Augmentation (IA).
Learning Topics
Inspiration: What is Generative AI in the context of AI's history, present, and future.
Climbing Up: Ways to accelerate your learning trajectory.
Unleashing Creativity: Ways to stay future-ready in the AI era.
Deep dive into ChatGPT's features.
Techniques for basic and advanced prompting and real-world applications.
Talk at SRI for Post Industrial Forum
June 28, 2023 5pm-8pm
https://post-industrial.institute/forum/
Frode Odegard invitation
https://www.linkedin.com/in/odegard/
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
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!
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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.
2. Ǹdéwonu!
Uche Ogbuji
AI dev since early 90s
Data-centric since mid 90s
Freelance dev, architect &
writer. Let’s talk!
Twitter: @uogbuji
E-mail: uche@ogbuji.net
2
10. Heard this one before?
Knowledge
representation
60s—70s—80s?
Conceptual
graphs
80s—90s
10
RDF
90s—
Linked Data
00s—
Semantic
networks
50s—60s
Knowledge
graphs
10s—
11. Expect magical thinking
▹ Dateline this week: BP invests $5M in
Belmont, AI startup
▹ Special knowledge graph tech to be fed
geo info, project histories etc.
▹ BlahBlah buzzword. ML. NLP.
CogComp.
Hey presto! targeting 10X speedups in
subsurface exploration
11