AI is the new ELECTRICITY - said Andrew Ng. There are two sides of the coin. There are a lot of nay-sayers for AI. At the end of the day, it will be Augmented Intelligence, Adaptive Intelligence, Automated Intelligence that will propel human intelligence forward - more than anything else. It will be a great time ahead. Whether it would be an "Eye(AI) Wash" as skeptics say or an "I wish" from them for starting late on the journey, only time will tell. It is a matter of when and how long, instead of an If. #ArtificialIntelligence #IntelligentTesting #QCoE #NextGenTesting #QualityFocusedDelivery #DigitalInnovation #ITIndustry #NewAgeIT #InnovativeTesting#AIFication #Automation #DigitalEconomy #Singularity #Transcendence #Futurism
From Human Intelligence to Machine IntelligenceNUS-ISS
This in an introductory talk to get ready for the AI era, and will talk about human intelligence, the model view of intelligence and machine/artificial intelligence. There will be some coverage of AI roots and subfields.
Unravel COVID-19 From a Systems Thinking LensNUS-ISS
COVID-19 pandemic has exposed the gaps in every countries' infrastructure and society. As we deal with one threat of the crisis, we are quickly overwhelmed by secondary consequences. The butterly effect of COVID-19 unveils the reality of system interdependence at multiple levels. Join us in understanding the complex nature of this interdependence through the lens of system thinking and discuss how might we manage this crisis together with fresh eyes.
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...Carol Smith
Artificially intelligent systems are becoming part of our everyday lives. This session will answer your questions about artificial intelligence, machine learning, and the ethical conflicts and the implications inherent in these technologies. Topics covered will include: discussions of bias in data; how to focus on the user experience; what is necessary to build a good cognitive computing systems; data needs; levels of accuracy; making safe and secure AI's; and discussions on ethics in AI and our role in leading those conversations. Carol will propose simple models for thinking about these systems and provide time for questions. You will walk away with an awareness of the weaknesses of AI and the knowledge of how these systems work.
Selected by the audience to be presented at ProductCamp Pittsburgh in September 2018
Computer vision is a prominent subset of artificial intelligence that can analyse and make sense of image and video data. Dr Tian Jing, Senior Lecturer & Consultant, Artificial Intelligence Practice will expand on recent advanced computer vision developments and key use cases in the new normal, such as social distancing in surveillance, hand hygiene monitoring in healthcare and more. This talk will also demonstrate examples of practice module projects of Intelligent Sensing Systems Graduate Certificate, offered by NUS-ISS in the past semesters.
Latest developments including hardware and algorithm updates presented at the London Deep Learning Lab meetup https://www.meetup.com/Deep-Learning-Lab/
How to Build Your Future in the Internet of Things Economy. Jennifer RigginsFuture Insights
FOWA London 2015
The trillion-dollar IoT economy will impact our lives so much more than even the Internet itself. From IoT protocols to hypermedia APIs to devices to new networks of communication, you need to learn how to overcome very arduous security, privacy, and just-too-soon barriers in order to build your own future in the IoT space. Jennifer's talk is a result of talking to dozens of Internet of Things influencers and experts - come along to learn about her findings!
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019Carol Smith
To design for inclusion we often must try out different ideas. In this interactive session you'll learn about all types of prototyping and how to get feedback on your ideas from your users. This session will briefly introduce a variety of prototypes and materials and evaluation methods for early learning.
Participants will have time to build a quick prototype and practice getting feedback on it. We'll cover designing for accessibility and inclusion even at the prototype stage. You'll have the information you need to launch your ideas as early as possible to learn from the experience and improve more quickly.
Presented at the Pittsburgh Inclusive Innovation Summit March 30, 2019 held at Point Park University.
From Human Intelligence to Machine IntelligenceNUS-ISS
This in an introductory talk to get ready for the AI era, and will talk about human intelligence, the model view of intelligence and machine/artificial intelligence. There will be some coverage of AI roots and subfields.
Unravel COVID-19 From a Systems Thinking LensNUS-ISS
COVID-19 pandemic has exposed the gaps in every countries' infrastructure and society. As we deal with one threat of the crisis, we are quickly overwhelmed by secondary consequences. The butterly effect of COVID-19 unveils the reality of system interdependence at multiple levels. Join us in understanding the complex nature of this interdependence through the lens of system thinking and discuss how might we manage this crisis together with fresh eyes.
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...Carol Smith
Artificially intelligent systems are becoming part of our everyday lives. This session will answer your questions about artificial intelligence, machine learning, and the ethical conflicts and the implications inherent in these technologies. Topics covered will include: discussions of bias in data; how to focus on the user experience; what is necessary to build a good cognitive computing systems; data needs; levels of accuracy; making safe and secure AI's; and discussions on ethics in AI and our role in leading those conversations. Carol will propose simple models for thinking about these systems and provide time for questions. You will walk away with an awareness of the weaknesses of AI and the knowledge of how these systems work.
Selected by the audience to be presented at ProductCamp Pittsburgh in September 2018
Computer vision is a prominent subset of artificial intelligence that can analyse and make sense of image and video data. Dr Tian Jing, Senior Lecturer & Consultant, Artificial Intelligence Practice will expand on recent advanced computer vision developments and key use cases in the new normal, such as social distancing in surveillance, hand hygiene monitoring in healthcare and more. This talk will also demonstrate examples of practice module projects of Intelligent Sensing Systems Graduate Certificate, offered by NUS-ISS in the past semesters.
Latest developments including hardware and algorithm updates presented at the London Deep Learning Lab meetup https://www.meetup.com/Deep-Learning-Lab/
How to Build Your Future in the Internet of Things Economy. Jennifer RigginsFuture Insights
FOWA London 2015
The trillion-dollar IoT economy will impact our lives so much more than even the Internet itself. From IoT protocols to hypermedia APIs to devices to new networks of communication, you need to learn how to overcome very arduous security, privacy, and just-too-soon barriers in order to build your own future in the IoT space. Jennifer's talk is a result of talking to dozens of Internet of Things influencers and experts - come along to learn about her findings!
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019Carol Smith
To design for inclusion we often must try out different ideas. In this interactive session you'll learn about all types of prototyping and how to get feedback on your ideas from your users. This session will briefly introduce a variety of prototypes and materials and evaluation methods for early learning.
Participants will have time to build a quick prototype and practice getting feedback on it. We'll cover designing for accessibility and inclusion even at the prototype stage. You'll have the information you need to launch your ideas as early as possible to learn from the experience and improve more quickly.
Presented at the Pittsburgh Inclusive Innovation Summit March 30, 2019 held at Point Park University.
Designing AI for Humanity at dmi:Design Leadership Conference in BostonCarol Smith
As design leaders we must enable our teams with skills and knowledge to take on the new and exciting opportunities that building powerful AI systems bring. Dynamic systems require transparency regarding data provenance, bias, training methods, and more, to gain user’s trust. Carol will cover these topics and challenge us as design leaders, to represent our fellow humans by provoking conversations regarding critical ethical and safety needs.
Presented at dmi:Design Leadership Conference in Boston in October 2018.
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
How can designers improve trust of cognitive systems? What can we do to make these systems transparent? What information needs to be transparent? The biggest challenges inherent with AI will be discussed, specifically the ethical conflicts and the implications for your work, along with the basics of these concepts so that you can strive for making great AI systems.
Designing Trustable AI Experiences at World Usability Day in ClevelandCarol Smith
How can designers improve trust of cognitive systems? What can we do to make these systems transparent? What information needs to be transparent? The biggest challenges inherent with AI will be discussed, specifically the ethical conflicts and the implications for your work, along with the basics of these concepts so that you can distinguish between simply smart systems and AI.
Presented at the World World Usability Day 2018 celebration in Cleveland, Ohio.
The Rationale for Continuous Delivery by Dave FarleyBosnia Agile
The production of software is a complex, collaborative process that stretches our ability as human beings to cope with its demands.
Many people working in software development spend their careers without seeing what good really looks like.
Our history is littered with inefficient processes creating poor quality output, too late to capitalise on the expected business value. How have we got into this state? How do we get past it? What does good really look like?
Continuous Delivery changes the economics of software development for some of the biggest companies in the world, whatever the nature of their software development, find out how and why.
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
Clipperton - AI - Deep Learning: From Hype to Maturity?Stephane Valorge
Paris, London, Berlin – September 2017 - Clipperton, a leading European corporate finance boutique focused on the High Tech and Media industries announces the release of a Research Paper covering the recent trends and evolution in the Artificial Intelligence industry, with a particular focus on the hottest topic of the last 18 months: Deep Learning.
Introduction To Artificial Intelligence Powerpoint Presentation SlidesSlideTeam
Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth. https://bit.ly/2V0reNa
London Futurists - The Future of AI & SustainabilityAlex Housley
Artificial intelligence (AI) is powering the fourth industrial revolution. Intelligent machines are tackling new cognitive tasks at scale, leading to enormous economic efficiency gains and disruption across the labour market. But what will be the net impact of AI on society and the ecological environment?
In this talk, Alex Housley, founder and CEO of open-source machine learning platform Seldon, explains how the collaborative approach to AI development helps transform industries and provides the macro-scale opportunities for AI to make the world a better and more sustainable place.
The event was chaired by David Wood. The camera was operated by Kiran Manam.
For more details about this event, see https://www.meetup.com/London-Futuris....
For more information about Seldon, see https://www.seldon.io/.
To apply to join the closed beta mentioned in the talk, visit bit.ly/deploy-beta.
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityEric Garland
In this presentation for the Intelligence Collaborative, I explore cognitive bias - social, decision, probability, and memory - and its effect distortion clear thinking about strategy and decision making. This is part of of my executive training course "Executive Mind Traps.
Designing AI for Humanity at dmi:Design Leadership Conference in BostonCarol Smith
As design leaders we must enable our teams with skills and knowledge to take on the new and exciting opportunities that building powerful AI systems bring. Dynamic systems require transparency regarding data provenance, bias, training methods, and more, to gain user’s trust. Carol will cover these topics and challenge us as design leaders, to represent our fellow humans by provoking conversations regarding critical ethical and safety needs.
Presented at dmi:Design Leadership Conference in Boston in October 2018.
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
How can designers improve trust of cognitive systems? What can we do to make these systems transparent? What information needs to be transparent? The biggest challenges inherent with AI will be discussed, specifically the ethical conflicts and the implications for your work, along with the basics of these concepts so that you can strive for making great AI systems.
Designing Trustable AI Experiences at World Usability Day in ClevelandCarol Smith
How can designers improve trust of cognitive systems? What can we do to make these systems transparent? What information needs to be transparent? The biggest challenges inherent with AI will be discussed, specifically the ethical conflicts and the implications for your work, along with the basics of these concepts so that you can distinguish between simply smart systems and AI.
Presented at the World World Usability Day 2018 celebration in Cleveland, Ohio.
The Rationale for Continuous Delivery by Dave FarleyBosnia Agile
The production of software is a complex, collaborative process that stretches our ability as human beings to cope with its demands.
Many people working in software development spend their careers without seeing what good really looks like.
Our history is littered with inefficient processes creating poor quality output, too late to capitalise on the expected business value. How have we got into this state? How do we get past it? What does good really look like?
Continuous Delivery changes the economics of software development for some of the biggest companies in the world, whatever the nature of their software development, find out how and why.
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
Clipperton - AI - Deep Learning: From Hype to Maturity?Stephane Valorge
Paris, London, Berlin – September 2017 - Clipperton, a leading European corporate finance boutique focused on the High Tech and Media industries announces the release of a Research Paper covering the recent trends and evolution in the Artificial Intelligence industry, with a particular focus on the hottest topic of the last 18 months: Deep Learning.
Introduction To Artificial Intelligence Powerpoint Presentation SlidesSlideTeam
Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth. https://bit.ly/2V0reNa
London Futurists - The Future of AI & SustainabilityAlex Housley
Artificial intelligence (AI) is powering the fourth industrial revolution. Intelligent machines are tackling new cognitive tasks at scale, leading to enormous economic efficiency gains and disruption across the labour market. But what will be the net impact of AI on society and the ecological environment?
In this talk, Alex Housley, founder and CEO of open-source machine learning platform Seldon, explains how the collaborative approach to AI development helps transform industries and provides the macro-scale opportunities for AI to make the world a better and more sustainable place.
The event was chaired by David Wood. The camera was operated by Kiran Manam.
For more details about this event, see https://www.meetup.com/London-Futuris....
For more information about Seldon, see https://www.seldon.io/.
To apply to join the closed beta mentioned in the talk, visit bit.ly/deploy-beta.
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityEric Garland
In this presentation for the Intelligence Collaborative, I explore cognitive bias - social, decision, probability, and memory - and its effect distortion clear thinking about strategy and decision making. This is part of of my executive training course "Executive Mind Traps.
The Mela Quiz was conducted as part of Thomso, the annual cultural fest of IIT Roorkee.
QM- Nikhil Arora
The link for audio/video for the quiz is attached below.
https://drive.google.com/drive/folders/1reazp5YRM-gh-Scq0hHkmZvxanViPIxP?usp=sharing
Written quiz for teams of two; conducted for the Karnataka Quiz Association.
Note: Presentation has answers immediately after questions; no gaps exist.
The Fresher's Quiz 2017 conducted by Thapar Quizzing Club on 5th September, 2017.
Contributed by - Abhinav Choudhary, Mokshlakshmi Bhan, Omisha Sharma, Rajenki Das and Soham Banerjee.
Total 48 questions with some extra 3 questions for tie breakers.
Webinar on AI in IoT applications KCG Connect Alumni Digital Series by RajkumarRajkumar R
The Artificial Intelligence in IoT Applications. Take your first step towards a bright future with our renowned alumnus,
Prof R. Raj Kumar on AI for IoT Applications.
He is an award wining author of the book, ‘India 2030’.
To get access to the webinar kindly contact your respective department heads.
Looking forward to having you on the webinar.
.
.
.
#KCGCollege #KCGStudentlife #KCGConnect #Education #EmergingTechnologies #ArtificialIntelligence #IoT #MachineLearning #BlockChain #ElectricVehicle #QuantumTechnology #CAD
this is the presentation about the artificial intelligence . this will help people to understand about the artificial intelligence . this is developed for students to learn something about the artificial intelligence.the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
The AI Platform Business Revolution: Matchmaking, Empathetic Technology, and ...Steve Omohundro
Popular media is full of stories about self-driving cars, video deepfakes, and robot citizens. But this kind of popular artificial intelligence is having very little business impact. The actual impact of AI on business is in automating business processes and in creating the "AI Platform Business Revolution". Platform companies create value by facilitating exchanges between two or more groups. AI is central to these businesses for matchmaking between producers and consumers, organizing massive data flows, eliminating malicious content, providing empathetic personalization, and generating engagement through gamification. The platform structure creates moats which generate outsized sustainable profits. This is why platform businesses are now dominating the world economy. The top five companies by market cap, half of the unicorn startups, and most of the biggest IPOs and acquisitions are platforms. For example, the platform startup ByteDance is now worth $75 billion based on three simple AI technologies.
In this talk we survey the current state of AI and show how it will generate massive business value in coming years. A recent McKinsey study estimates that AI will likely create over 70 trillion dollars of value by 2030. Every business must carefully choose its AI strategy now in order to thrive over coming decades. We discuss the limitations of today's deep learning based systems and the "Software 2.0" infrastructure which has arisen to support it. We discuss the likely next steps in natural language, machine vision, machine learning, and robotic systems. We argue that the biggest impact will be created by systems which serve to engage, connect, and help individuals. There is an enormous opportunity to use this technology to create both social and business value.
Algorithm Marketplace and the new "Algorithm Economy"Diego Oppenheimer
Talk by Diego Oppenheimer CEO of Algorithmia.com at Data Day Texas 2016.
Peter Sondergaard VP of Research for Gartner recently said the next digital gold rush is "How we do something with data not just what you do with it". During this talk we will cover a brief history of the different algorithmic advances in computer vision, natural language processing, machine learning and general AI and how they are being applied to Big Data today. From there we will talk about how algorithms are playing a crucial part in the next Big Data revolution, new opportunities that are opening up for startups and large companies alike as well as a first look into the role Algorithm Marketplaces will play in this space.
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Chetan Khatri
What is Data Science?
What is Machine Learning, Deep Learning, and AI?
Motivation
Philosophy of Artificial Intelligence (AI)
Role of AI in Daily life
Use cases/Applications
Tools & Technologies
Challenges: Bias, Fake Content, Digital Psychography, Security
Detect Fake Content with “AI”
Learning Path
Career Path
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
Artificial intelligence (AI, also machine intelligence, MI) is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal.
Impact of Generative AI in Cybersecurity - How can ISO/IEC 27032 help?PECB
Generative AI offers great opportunities for innovation in various industries. Hence, by adopting ISO/IEC 27032, you can enhance your cybersecurity resilience and efficiently address the risks associated with generative AI.
Amongst others, the webinar covers:
• AI & Privacy
• Generative AI, Models & Cybersecurity
• AI & ISO/IEC 27032
Presenters:
Christian Grafenauer
Anonymization expert, privacy engineer, data protection officer, LegalTech researcher (GDPR, Blockchain, AI) Christian Grafenauer is an accomplished privacy engineer, anonymization expert, and computer science specialist, currently serving as the project lead for anonymity assessments at techgdpr. With an extensive background as a senior architect in Blockchain for IBM and years of research in the field since 2013, Christian co-founded privacy by Blockchain design to explore the potential of Blockchain technology in revolutionizing privacy and internet infrastructure. As a dedicated advocate for integrating legal and computer science disciplines, Christian’s expertise in anonymization and GDPR compliance enables innovative AI applications, ensuring a seamless fusion of technology and governance, particularly in the realm of smart contracts. In his role at techgdpr, he supports technical compliance, Blockchain, and AI initiatives, along with anonymity assessments. Christian also represents consumer interests as a member of the national Blockchain and DTL standardization committee at din (German standardization institute) in ISO/TC 307.
Akin Johnson
Akin J. Johnson is a renowned Cybersecurity Expert, known for his expertise in protecting digital systems from potential threats. With over a decade of experience in the field, Akin has developed a deep understanding of the ever-evolving cyber landscape.
Akin is an advocate for cybersecurity awareness and frequently shares his knowledge through speaking engagements, workshops, and publications. He firmly believes in the importance of educating individuals and organizations on the best practices for safeguarding their digital assets.
Lucas Falivene
Lucas is a highly experienced cybersecurity professional with a solid base in business, information systems, information security, and cybersecurity policy-making. A former Fulbright scholar with a Master of Science degree in Information Security Policy and Management at Carnegie Mellon University (Highest distinction) and a Master's degree in Information Security at the University of Buenos Aires (Class rank 1st). Lucas has participated in several trainings conducted by the FBI, INTERPOL, OAS, and SEI/CERT as well as in the development of 4 cyber ISO national standards.
Date: July 26, 2023
YouTube Link: https://youtu.be/QPDcROniUcc
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.
Innovations in Testing
Testing and Quality Engineering Innovations, Disruptive Tools, Techniques and Processes needed for success in the new digital age
PREFACE 2
1. WHY IS QUALITY IMPORTANT? 3
2. INTELLIGENT TESTING SKILLS - PRIMARY NEED OF THE HOUR FOR DIGITAL INNOVATION 8
3. INTELLIGENT TESTING SKILLS NEEDED FOR THE NEXT GENERATION - UPSKILL OR RETIRE 20
4. TOP TIPS - HOW TO ESTABLISH A SUCCESSFUL TCOE / QCOE (TESTING / QUALITY CENTRE OF EXCELLENCE) 27
5. ARTIFICIAL INTELLIGENCE (AI) IS THE NEW ELECTRICITY! IS THERE ANYTHING ARTIFICIAL OR INTELLIGENT ABOUT IT? 35
6. IMPACTS OF DEVOPS ON TESTING 44
7. HOW TO RUN EFFICIENT API TESTING FOR IOT, WEB AND MOBILE APP INTERFACES? 48
8. "CROWD SOURCED TESTING" – A NEW WAVE IN DIGITAL REVOLUTION - A POINT-OF-VIEW 51
WHAT NEXT?9. NOUVEAU SKILL NEEDS FOR TESTING – FOR NEW SOFTWARE DRIVEN BUSINESSES 55
10. HOW DIGITAL INNOVATION IMPACTS TESTING AND COMMUNICATIONS INDUSTRIES? – A POV 58
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/
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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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
2. • Progress of AI and Robotics
• What’s the need for Artificial Intelligence?
• What will happen at singularity?
• Some AI Concepts
High level Intro to AI
• Is it an Intelligent Activity?
• Are we testing at the heights of
Augmented General Intelligence?
• AI in Testing - Is it augmented or Artificial
/ Is anything artificial about it?
• How will AI evolve Testing?
• Some Examples of AI Testing
AI in Testing
Agenda
3. - ANDREW NG
Founder of Coursera, Stanford Adjunct Professor
Ex. Chief AI Scientist of BAIDU
5. Source : https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/
A Good Explanation of Progress of AI
E a r l y A I
Basic Turing Test Style
Use of Memory and Knowledge
Post John McCarthy’s Conceptualization
Basic Robotics and Degrees of Freedom
D e e p L e a r n i n g
Rapid Infrastructure Growth
Advanced Algorithms
Big Data Explosion
Quantum Computing
M a c h i n e L e a r n i n g
Algorithms Centric
Statistics Driven
Supervised and Unsupervised Learning
6. Perhaps the greatest
Computer Scientist ever
predicting on Machine
Intelligence
We have clearly passed
the TURING TEST
We are seeing Leaps and
Bounds in advances of
Technology!
Let’s hear!
8. https://youtu.be/zatL4uFRpC0
Fast Learning – Download and Fly an helicopter
Can AI Take us to this stage?
How about Fast Testing – Hey – Can I test this brand new “thing” in 2 minutes?
9. From a Leader in AI – AI or an Algorithm Writing itself
10. Top Human World Champions Royally defeated by AI!
2011
2016
1996/97
IBM’s
Deep Blue
IBM
Watson
Google
Deepmind
AlphaGo won 60–0 rounds on two public Go websites
including 3 wins against World Go champion Ke Jie.
11. But... AI is not without controversies though!
Facebook Researchers shut down an AI
engine at the Facebook AI Research Lab
(FAIR), discovering that the AI created
its own unique language undecipherable
by humans - Simultaneous glimpse of
both the awesome and horrifying
potential of AI
Elon Musk - “AI isotentially more
Dangerous than Nukes”
sets up a $1 billion (£770M) OpenAI.org to try
and promote safe development of AI
Vladimir Putin -
“Whoever masters AI will rule the world!”
ISAAC ASIMOV’s Laws of Robotics
Law 1: A tool must not be unsafe to use.
Law 2: A tool must perform its function
efficiently unless this would harm the user. The
safety of the user is paramount.
Law 3: A tool must remain intact during its use
unless its destruction is required for its use or for
safety.
15. AI Startups are taking it to next Level – in all areas
Source: https://www.cbinsights.com/research-ai-100
Bots Automobile
Computer
Vision
Core /
Functional AI
Commerce IIoT/IOT
Healthcare Fintech Robotics
Analytics
Cyber
Security
Sales &
Marketing
17. “ Let’s get to TESTING
• How is AI helping
Testing?
• How can we test
better with AI?
• How can we test AI
systems Better?
17
18. “Be a yardstick of
QUALITY. Some
people aren't used
to an environment
where EXCELLENCE
is expected”
18
Steve Jobs
19. Business Agility - Some Statistics
19
Google - refactors code by
50% each month*
Netflix - 5 Billion+ API
Calls per Day (and
increasing daily)
~75% of Corporates to
have bi-modal IT
~63% all projects are not
aligned to Business
Strategy
~79% organizations using
CI/CD/DevOps practices in
one form or the other
52% of Fortune 500
companies have
disappeared from the list
& Average S&P500 span
reduces from 61 Years to
17 Years in 60 years
In 2020, 100 million
consumers will shop via
augmented reality
By 2020, 30% web
browsing will be done
without a screen
by 2022 - $1 Trillion a year
to be saved through IoT
Source: Gartner, Inc. Top Strategic Predictions for 2017 and Beyond: Surviving the Storm Winds of Digital Disruption, 14-Oct-2016
* - Google runs on ~2 Billion LOC Source: CA Workshop on Modern Software Factory
Source: CB Insights
* AR Market $143 Billion by 2020 - HW/SW/Apps/Consulting & SI
20. Is the Testing Industry ready for testing the
following innovations?
21
21. Tip of the Iceberg seen in 2016
2016 A Year in Review – Software Failures
22Source: Tricentis Software Fails 2016 Report - https://www.tricentis.com/wp-content/uploads/2017/01/20161231SoftwareFails2016.pdf
Over 4.4 Billion
people got affected by
a Software Fail (Up
from 4.3 Billion in
2015) > 50% Global
Population
$1,062,106,142,949
- Assets Affected (Up
from $4.2 Billion in
2015)
315 years, 6 months,
2 weeks, 6 days, 16
hours, & 26 minutes -
Accumulated time-
lost due to Bugs
2.66 Billion Mobile
Phones impacted
with Malware
12% Year on Year
Increase in impactful
Software Bugs
British Airways lost
$20 Billion (3%) in
Market Cap within a
few days after a failed
software upgrade
More Than 21
Million Automobile
recalls as a result of
Glitches / Bugs
$5.7 Billion Impact
in Failed Government
Software Projects due
to Bugs
2.2 Billion people live on less than $2 a day
22. One School of Thought on Testing – By Tricentis
Source: TRICENTIS webinar on Future of Testing
WhereAIcanhelp
Legacy
Firms
Bi-model Firms
Technology Leaders
25. Some Algorithms making Machine Think!
Source: https://futurism.com/predicting-2017-the-rise-of-synthetic-intelligence/ - Some of the artificial intelligence (AI) algorithms currently helping machines think. Credit: CIO Journal/Narrative Science
26. Approaches used for AI, Machine Learning and Deep Learning
Reinforcement Learning
• Passive Reinforcement
Regression Algorithms
• Linear Regression
• Gaussian Process
Supervised Learning
• Neural Networks
Unsupervised Learning
• Independent Component
Analysis
• Principle Component
Analysis
Natural Language
Understanding
• Morphological, , semantic,
syntactic , Discourse
analysis
Natural Language
Generation
• Deep planning
• Syntactic generation
Clustering Algorithms
• K-Means Clustering
• KPCA – Kernel Analysis
Statistical Algorithms
• Support Vector Machines
• K-Nearest Neighbor
• Native Bayes Classifier
• Maximum Entropy Classifier
Pattern Recognition
• Statistical , Syntactic
approach
• Template Matching
• Neural Networks
Other Techniques
• Spanning Trees and Graphs
• Neural Network – Multi-
Level Perceptron's
Other Techniques
• Labeling
• Hidden Markov Model
• Maximum Entropy MM
Other Techniques
• Conditional Random Fields
• Parsing Algorithms
28. What are the feasibilities
with AI Driven Testing?
30
Automated Defect
Detection
Automated
Exploratory
Testing
Test Coverage
Heat map
Self Healing
Automation
Predictive
Modeling
Self Adjusting
Regression
Pattern
Recognition
Risk & Coverage
Optimization
Diagnostic,
Prescriptive and
Predictive Analysis
Deep Learning
Root-Cause
Analysis
Sentiment Analysis
29. 31
AI Models Algorithms
Application Under
Test
Designer Developer Business UserTesterBots / Agents
AI Engine
Testing Outcomes
Test Cases
Production
Logs
Requirements
Defect Logs Source Code
Traceability
Matrix
Root Cause
Analysis
Test Data
Specifications
Functional
Logic
Sample AI Model for Testing
Historical & Real-time Data
31. Example: Candy Crush Saga’s AI Strategy
https://www.youtube.com/watch?v=wHlD99vDy0s
• Use of AI engine for continuous Feedback Loop
• Use of BOTS to perform Testing
• Continuous Feedback Loop
• Deep Artificial Neural Network
• Use of Monte Carlo Tree Simulation
• Use of Advanced Automation by BOTS
• Hybrid Test team (150-200+ Testers) with unique skills
• Use of Data Scientists for Domain Knowledge, Fun (using
historic info and user behavior, Game Balancing)
• Regular Crash Testing, Performance Testing, Regression
Testing
• Regular Upgrade of AI Bot for Testing
v
Since John McCarthy invented AI in 1956 – Progressed by Marvin Minsky Etc.
Ray Kurzweil – Highlights that Singularity will happen by 2045
https://youtu.be/zatL4uFRpC0
Fast Learning – Download and Fly an helicopter – Can AI be so advanced that we can scan an image and learn faster, deeper and efficiently?
Let’s hear it from one of the leaders in the AI Space – AI or an Algorithm Writing Code – Watch out Developers and Testers!
Garry Kasparov
Lee Seoul
Ken Jennings and Randy Burr
Google DeepMind's AlphaGo won 60–0 rounds on two public Go websites including 3 wins against world Go champion Ke Jie.
AI induced Algorithms have been winning a tough game of Texas Hold’em poker where majority of the information is hidden – against world’s leading Poker Players as well.
AI is definitely not without controversies – It could potentially start the WW3 soon and a lot of countries are embarking on hegemony and superiority of AI – Just like the Cold-war era SPACE RACE that resulted in a lot of brilliant inventions, discoveries and humankind’s progress. But will the new AI war be different – Let’s wait and see..
AI is definitely not without controversies – It could potentially start the WW3 soon and a lot of countries are embarking on hegemony and superiority of AI – Just like the Cold-war era SPACE RACE that resulted in a lot of brilliant inventions, discoveries and humankind’s progress. But will the new AI war be different – Let’s wait and see..
Google is using machine learning and deep learning principles in a simple method. Let’s see a video and try it out!
Take it to next level – How can you easily integrate globally. Language will no longer be a barrier.
A perfectionist of sorts, Steve Jobs quoted - “Be a yardstick of quality. Some people aren't used to an environment where excellence is expected”
Without a focus on quality, simplicity and efficiency, APPLE wouldn’t have become the most valuable company on earth, a brilliant turn around from a company that was almost dead before Jobs 2.0 began.
Source: CA Workshop on Modern Software Factory
Source: Gartner, Inc. Top Strategic Predictions for 2017 and Beyond: Surviving the Storm Winds of Digital Disruption, 14-Oct-2016
While the defects and bugs are making a dramatic impact, the world is leaping ahead. Business is expecting agility in business delivery...
Take these for some stats
Google – which supposedly has a single code repository, refactors code by upwards of 50% each month. They have ~2 Billion LOC (and counting). Even taking a 75-95% test coverage taken up by empowered teams (as claimed by some of the engineers in published artefacts), this is a humongous testing effort. If you have a backlog of code to be verified, it could be a disaster exceeding the size of a titanic by all means. When the Cyclomatic complexity of testing is so huge, how can you test the entire code base and application flawlessly? This is a brilliant example of how one can run an efficient test strategy.
Take NetFlix that currently has over 5 Billion API Calls per day (up from Billion+ a few years ago). How would you do effective Load, Stress, Performance Testing and ensure Availability , Redundancy and Reliability of service is not impacted?
A lot of firms are moving towards a bi-modal IT (doing a transformation while running the legacy apps running) and doing continuous delivery and Testing all the time, leveraging all the fancy words such as Agile, DevOps DevQAOps etc. etc.
Additionally, nearly 41% of Global corporate workload is shifting to cloud, to ease out on Capital Expense and controlled Operational Expense strategies.
By some means, Augmented Reality, Gestural Computing, IoT is expected to take the world by storm. How are we going to test all these permutations?
AR Market $143 Billion by 2020 - HW/SW/Apps/Consulting & SI
If you take the Gartner’s Hype Cycle for Emerging Technologies for 2017 – You see a pattern. Some are in the slope of enlightenment but majority in the curve of inflated expectations and disillusionment. For the technologies emerging stronger, we need to have some solid test approach / strategy to deliver high quality outcomes
Artificial Intelligence
Internet of Things (or Everything)
Machine Learning / Deep Learning
AR/VR & Wearables
Block Chain
Drones & Vehicles
Gestural Computing
Connected Devices
Human Augmentation
Robotics
Algorithms
Smart Assistants
Are we ready for these?
Carrying on Quality - Some statistics or a tip of the ice-berg
Over 4.4 billion people got affected by a software fail – which is greater than 50% of Human Population. It is almost a number similar to the people not having access to a Toilet – But less than the number of mobile phones in use in the world!.
More than a $Trillion worth of assets affected and a cumulative impact of 315 years.
A leading airlines lost 3% market cap due t a botched software upgrade infested with bugs
Broadly speaking – New Age Test Innovation focuses on the following needs with Intelligent Testing
Rapid High Quality and Innovative Test Delivery
Test Suite Creation and Optimization (Risk Coverage )
Useful Automation – Test Smart, Self-Healing, Script less, Purposeful
Predictive and Cognitive Testing – Foresee issues reduce reactive time, resolve rapidly
Rapid Impactful Defect Finding - Intelligent Defect Detection, Pattern Analysis, Predictive Modeling
Intelligent Environment Provisioning
Management with Intelligent Metrics and Dashboard
Are we capable of building intelligent automated frameworks and leverage cognitive models to optimize our test strategy and test suites to do proactive application health analytics via rapid defect finding and scale up rapidly to do niche and special areas of testing? That remains the key
https://www.linkedin.com/pulse/ai-software-testing-jason-arbon
Explore user experience, by analyzing text from social media feeds (sentiment analysis) to spot feedback trends about what has already been released
Cluster similar bugs together by data visualization heat mapping, for easier attack by Development (via the Pareto Approach, theorizing that bugs like to nest together)
Reduce test cases that can be determined to be unnecessary before execution?
Predict if specific follow-up DevOps sprints require specific tests cases to be run, vs. being omitted because there’s no chance that the problem got addressed yet.
Reviewing specifications tell us what a program should do and how it should work. I.’s pattern matching helps us eliminate unneeded “too close’ test cases by seeing which ones are too similar. As we mentioned earlier, this may mean focusing on boundary value analysis (edge cases, literally), emphasizing state transition, or ensuring all-pairs testing.
Exploration testing session logs, via pattern recognition of verbose logging, seek activity patterns of specific warnings tracking to specific user actions, modules, forms, etc.
Known product issues, once analyzed, can have A.I. cluster similar bugs through pattern recognition, suggesting likely duplicates. Bugs from automated test cases can be auto-run on previous builds to find the causal build to help pinpoint root cause code changes.
Discussions with knowledgeable personnel (product owners, developers or Marketing, etc.) may determine code danger areas. White box-driven test design targets the actual revised code, hunting for specific code level problems. Factors may include the coder, change date, functions referenced, or specific non-standard notations. A.I. pattern-matching techniques help pinpoint applicable code based on your search parameters.
End user analysis applies to two different areas. The first is studying the frequency of specific user feedback words to help the most popular concerns bubble to the top of a list for further research. The second is end user usage analysis, where log file statistics (based on A.I. pattern searching) show how much time each type of user spends in different program areas on different actions. Early focus on these heat mapped areas concentrate attention where the most user time is spent.
Test suite optimization - Identifies duplicate/similar and unique test cases
Predicting the next - To help predict the key parameters of software testing processes based on historical data.
Log Analytics - Identifies hotspots and automatically execute test cases
Traceability - Identifies complex scenarios from the requirements traceability matrix (RTM) and extract keywords to achieve test coverage
Customer sentiment Analytics - Analyzes data from social media and provides an interactive visualization of feedback trends
Defect analytics - Identifies high-risk areas in the application which helps in risk-based prioritization of regression test cases
Its benefits include:
Improved quality – Prediction, prevention, and automation using self-learning algorithms
Faster time to market – Significant reduction in efforts with complete E2E test coverage
Cognitively – Scientific approach for defect localization, aiding early feedback with unattended execution
Traceability – Missing test coverage against requirement as well as, identifying dead test cases for changed or redundant requirement
One integrated platform – Adaptable to client technology landscape, built on open source stack
Leave the exhaustive testing to AI. Leave tapping every button, inputting obvious valid and invalid data into text fields, etc. to the machines.
Focus on the qualitative aspects of software testing that is specific to their specific app and customer.
Focus on creative and business-specific test inputs and validations. Be more creative and think of email address values that a machine with access to thousands of possible email test inputs wouldn’t think to try. Verify that cultural- or domain-specific and expectations are met. Think of test cases that will break the machine processing for your specific app (e.g., negative prices, disconnecting the network at the worst possible time, or simulating possible errors).
Record these human decisions in a way that later helps to train the bots. Schematized records of input and outputs are better than English text descriptions in paragraph form