Carol Smith presented on AI and machine learning at the Midwest UX 2017 conference in Cincinnati, Ohio. She discussed how AI systems exhibit intelligence by perceiving their environment and taking actions to achieve goals defined by their human programmers. She provided examples of AI applications such as self-driving cars, image recognition in Google Photos, and analyzing medical images to assist radiologists. Smith emphasized that AI systems are only as good as the data and training provided by experts, and that humans remain in control of defining the goals and oversight of AI.
Artificial Intelligence Introduction & Business usecasesVikas Jain
Â
Vikas Jain is a leading keynote speaker on artificial intelligence.
Develop AI Solution mindset to help business leaders & professionals from IT/non-IT Industry can use it to solve complex problems and grow their business.
Quantitative Ethics - Governance and ethics of AI decisionsNikita Lukianets
Â
Presented as a part of the conference "Robots and Artificial Intelligence: The new force awakens" held in Nice, France in March 2018. This presentation provides framework and strategies to approach ethical aspects in the development of the AI of tomorrow.
The main topics discussed:
1) Data is the new electricity
2) Artificial intelligence and the decision making
3) Ethical frameworks for artificial intelligence
AI, Machine Learning & Deep Learning Risk Management & Controls: Beyond Deep Learning and Generative Adversarial Networks: Model Risk Management in AI, Machine Learning & Deep Learning
Business growth principles in the new economy Ashish Bedekar
Â
A presentation I made @ Palava #Smartcity #startup accelerator on 19th April 2018. http://bit.ly/2qz5Xr2
#1 About me:
You may like to check out https://ashishbedekar.fyi.to/ecosystems which gives an overview of my profile, including LinkedIn recommendations
#2: Connect with me http://www.linkedin.com/in/ashishrbedekar | Twitter: @ashishrbedekar
#3 I believe in giving back to the community e.g
- Pro-bono startup advisor @Zone startup- an Indo-Canadian start-up Accelerator http://bit.ly/2o9XNqaÂ
- Pro-bono startup advisor@ Supercharger Fintech accelerator ( KL, HK) http://bit.ly/2ErcM6S
- Pro-bono startup advisor@ NIT Trichy- International biz competition- http://bit.ly/2AQxqYu
-Mentor of change- Govt. of India- Atal innovation mission http://bit.ly/2HMdWrV
-Member of IET- IoT India (The IET is one of the world's largest multi-discipline professional societies of engineers with more than 160,000 members in 127 countries)  http://bit.ly/2o9Pue9Â
-Mentor for startup boot camp-E- Cell- IIT Madras- one of Indiaâs leading engineering college-Â http://bit.ly/2G6nRMgÂ
Artificial Intelligence Introduction & Business usecasesVikas Jain
Â
Vikas Jain is a leading keynote speaker on artificial intelligence.
Develop AI Solution mindset to help business leaders & professionals from IT/non-IT Industry can use it to solve complex problems and grow their business.
Quantitative Ethics - Governance and ethics of AI decisionsNikita Lukianets
Â
Presented as a part of the conference "Robots and Artificial Intelligence: The new force awakens" held in Nice, France in March 2018. This presentation provides framework and strategies to approach ethical aspects in the development of the AI of tomorrow.
The main topics discussed:
1) Data is the new electricity
2) Artificial intelligence and the decision making
3) Ethical frameworks for artificial intelligence
AI, Machine Learning & Deep Learning Risk Management & Controls: Beyond Deep Learning and Generative Adversarial Networks: Model Risk Management in AI, Machine Learning & Deep Learning
Business growth principles in the new economy Ashish Bedekar
Â
A presentation I made @ Palava #Smartcity #startup accelerator on 19th April 2018. http://bit.ly/2qz5Xr2
#1 About me:
You may like to check out https://ashishbedekar.fyi.to/ecosystems which gives an overview of my profile, including LinkedIn recommendations
#2: Connect with me http://www.linkedin.com/in/ashishrbedekar | Twitter: @ashishrbedekar
#3 I believe in giving back to the community e.g
- Pro-bono startup advisor @Zone startup- an Indo-Canadian start-up Accelerator http://bit.ly/2o9XNqaÂ
- Pro-bono startup advisor@ Supercharger Fintech accelerator ( KL, HK) http://bit.ly/2ErcM6S
- Pro-bono startup advisor@ NIT Trichy- International biz competition- http://bit.ly/2AQxqYu
-Mentor of change- Govt. of India- Atal innovation mission http://bit.ly/2HMdWrV
-Member of IET- IoT India (The IET is one of the world's largest multi-discipline professional societies of engineers with more than 160,000 members in 127 countries)  http://bit.ly/2o9Pue9Â
-Mentor for startup boot camp-E- Cell- IIT Madras- one of Indiaâs leading engineering college-Â http://bit.ly/2G6nRMgÂ
Novi Sad AI is the first AI community in Serbia with goal of democratizing knowledge of AI. On our first event we talked about Belief networks, Deep learning and many more.
Machine Learning for Non-Technical People - Turing Fest 2019Britney Muller
Â
Machine Learning/AI is becoming more and more accessible and will free you up to work on higher level thinking.
ANYONE can come up with the next big ML/AI application.
What will you solve?
From Biology to Industry. A Bloggerâs Journey to Data Science.Shirin Elsinghorst
Â
What does blogging mean for Data Sciences?
What is Big Data today?
How to become a Data Scientist and what type of work results from this transformation?
Australian Legal Education in 2017: Taking Stock for an Uncertain FutureSally Kift
Â
This presentation was made to The Future of Legal Education Workshop hosted by Griffith University's Law Futures Centre on 1 November 2017. It suggests that Australian legal education research over the last decade has positioned us well for an uncertain future. While our Law Schools cannot afford to be complacent, especially given the increasing automation of legal work and the unbundling of legal services, the strong research and evidence base to which Australian legal educators may refer provides a degree of optimism for an uncertain future. Critically, this must be a joint endeavour that engages all branches of the legal profession and the Academy working together. Students and young lawyers in particular have a vital role to play in shaping the future of their professional education. In the absence of an #OLTphoenix, Australian legal education is well-placed to be self-sustaining and self-generating.
The abstract for the session was as follows:
In 2017, Australian legal education finds itself at a crossroads. In common with its disciplinary brethren, it is being impacted by the multitude challenges and volatile policy environment facing the Australian higher education sector more broadly. As for the rest of the Academy also, Law Schools are being squeezed on numerous fronts in their quest to fund pedagogical innovation. In the meantime, law students, who continue to bear a disproportionately high percentage of their degree costs, find themselves entering an extremely competitive job market with reduced employment opportunities. And of potentially even greater import, the disruptive innovation being felt in universities is also now impacting the legal services industry itself, so much so that the halcyon days of Priestleyâs dead hand (or light hand, depending on your perspective) finally look to be drawing to a close.
This presentation will review Australian legal educationâs pedagogical progress over the last decade through a scholarship lens and ask how is legal education positioned in 2017 for an uncertain future? In the absence of a national body such as the Office for Learning and Teaching (OLT), which was de-funded in mid-2016, is Australian legal education research and scholarship sufficiently mature to be self-sustaining and self-generating? At the risk of being overly optimistic, it will be suggested that, in an era of stackable credentials, the quality of Australian legal education generally ranks amongst the best in the world and is well-positioned to prepare its students to take their place, personally and professionally, as global citizens in complex and dynamic legal and other workplaces.
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017Carol Smith
Â
Cognitive computing and machine learning are not new concepts, but they are new to most UXâers. Carol Smith addresses questions about artificial intelligence (AI) such as:
- What are these terms and technologies and how do they work?
- How can we take advantage of these powerful systems to help our users?
- Should I be concerned that computers will take over the world soon? Spoiler: It is extremely unlikely.
Once this baseline understanding is established, weâll look at examples of AI in use and discuss the relevancy of design work in the age of AI. Additionally, weâll explore the ethical challenges inherent with the use of AI from the userâs perspective, specifically regarding trust and transparency.
This was presented at Fluxible 2017 in Kitchener-Waterloo, Ontario, Canada on 23 Sept 2017.
Designing AI for Humanity at dmi:Design Leadership Conference in BostonCarol Smith
Â
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 userâs 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.
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019Carol Smith
Â
How can we, as designers, create artificially intelligent systems that donât hurt humans? What should we think about to make these systems transparent? What information needs to be available to users to engender trust? This talk proposes a model for talking about the major decision points in building an AI.
Carol will tackle the biggest challenges inherent with AI including issues of ethics and the implications for your work. Wondering why you keep hearing about the Trolley Problem? Has someone claimed that your AI is nearly sentient? Bring your questions and curiosity for this engaging evening, and sheâll warn you before spoilers of The Good Place (Š2019 NBCUniversal Media, LLC).
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018Carol Smith
Â
This session focuses on the questions we need to ask to create good, ethical experiences for our users.
Information Architects must push toâŚ
- Keep people at the center of our work.
- Lead with our userâs goals.
- Ease of use, usability, findability, effectiveness, efficiencyâŚ
We must work to mature organizations approach
- Push back on âtechnology firstâ ideas.
- Lead on ethics - for our users, humanity.
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
Â
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.
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17Carol Smith
Â
What is machine learning? Is IA relevant in the age of AI? How can I take advantage of cognitive computing? Learn the basics of these concepts and the implications for your work in this presentation. Carol Smith provides examples of machine learning use and will discuss the challenges inherent in in AI.
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Chetan Khatri
Â
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 âAIâ
Learning Path
Career Path
Designing Trustable AI Experiences at World Usability Day in ClevelandCarol Smith
Â
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.
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in TorontoCarol Smith
Â
Artificially intelligent (AI) technologies are exciting and with them come a lot of new user experience research (UXR) responsibilities. How do we understand and clarify our users need for transparency, control, and access (and more) when the system is constantly changing?
These dynamic systems are already part of our everyday lives and quickly becoming part of our jobs. What are our responsibilities with regard to ethics and protecting users from bias?
Presented at Strive, June 7, 2019 in Toronto, Ontario, Canada. Strive is the 2019 UX Research Conference presented by the UX Research Collective Inc.
Tallk given at #SXSW2019 in the Intelligent Future track as part of the Interactive Festival. We explain 3 frameworks for MachineEthics and how they affect the supervised and unsupervised methods, and the data engineering discipline.
On March 26, 2015 Steve Omohundro gave a talk in the IBM Research 2015 Distinguished Speaker Series at the Accelerated Discovery Lab, IBM Research, Almaden.
Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating âarms racesâ in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial ârational drivesâ of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the âSafe-AI Scaffolding Strategyâ for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by the laws of physics, mathematical proof, and cryptographic complexity. âSmart contractsâ are a promising decentralized cryptographic technology used in Ethereum and other second-generation cryptocurrencies. They can express economic, legal, and political rules and will be a key component in governing autonomous technologies. If we are able to meet the challenges, AI and robotics have the potential to dramatically improve every aspect of human life.
Novi Sad AI is the first AI community in Serbia with goal of democratizing knowledge of AI. On our first event we talked about Belief networks, Deep learning and many more.
Machine Learning for Non-Technical People - Turing Fest 2019Britney Muller
Â
Machine Learning/AI is becoming more and more accessible and will free you up to work on higher level thinking.
ANYONE can come up with the next big ML/AI application.
What will you solve?
From Biology to Industry. A Bloggerâs Journey to Data Science.Shirin Elsinghorst
Â
What does blogging mean for Data Sciences?
What is Big Data today?
How to become a Data Scientist and what type of work results from this transformation?
Australian Legal Education in 2017: Taking Stock for an Uncertain FutureSally Kift
Â
This presentation was made to The Future of Legal Education Workshop hosted by Griffith University's Law Futures Centre on 1 November 2017. It suggests that Australian legal education research over the last decade has positioned us well for an uncertain future. While our Law Schools cannot afford to be complacent, especially given the increasing automation of legal work and the unbundling of legal services, the strong research and evidence base to which Australian legal educators may refer provides a degree of optimism for an uncertain future. Critically, this must be a joint endeavour that engages all branches of the legal profession and the Academy working together. Students and young lawyers in particular have a vital role to play in shaping the future of their professional education. In the absence of an #OLTphoenix, Australian legal education is well-placed to be self-sustaining and self-generating.
The abstract for the session was as follows:
In 2017, Australian legal education finds itself at a crossroads. In common with its disciplinary brethren, it is being impacted by the multitude challenges and volatile policy environment facing the Australian higher education sector more broadly. As for the rest of the Academy also, Law Schools are being squeezed on numerous fronts in their quest to fund pedagogical innovation. In the meantime, law students, who continue to bear a disproportionately high percentage of their degree costs, find themselves entering an extremely competitive job market with reduced employment opportunities. And of potentially even greater import, the disruptive innovation being felt in universities is also now impacting the legal services industry itself, so much so that the halcyon days of Priestleyâs dead hand (or light hand, depending on your perspective) finally look to be drawing to a close.
This presentation will review Australian legal educationâs pedagogical progress over the last decade through a scholarship lens and ask how is legal education positioned in 2017 for an uncertain future? In the absence of a national body such as the Office for Learning and Teaching (OLT), which was de-funded in mid-2016, is Australian legal education research and scholarship sufficiently mature to be self-sustaining and self-generating? At the risk of being overly optimistic, it will be suggested that, in an era of stackable credentials, the quality of Australian legal education generally ranks amongst the best in the world and is well-positioned to prepare its students to take their place, personally and professionally, as global citizens in complex and dynamic legal and other workplaces.
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017Carol Smith
Â
Cognitive computing and machine learning are not new concepts, but they are new to most UXâers. Carol Smith addresses questions about artificial intelligence (AI) such as:
- What are these terms and technologies and how do they work?
- How can we take advantage of these powerful systems to help our users?
- Should I be concerned that computers will take over the world soon? Spoiler: It is extremely unlikely.
Once this baseline understanding is established, weâll look at examples of AI in use and discuss the relevancy of design work in the age of AI. Additionally, weâll explore the ethical challenges inherent with the use of AI from the userâs perspective, specifically regarding trust and transparency.
This was presented at Fluxible 2017 in Kitchener-Waterloo, Ontario, Canada on 23 Sept 2017.
Designing AI for Humanity at dmi:Design Leadership Conference in BostonCarol Smith
Â
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 userâs 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.
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019Carol Smith
Â
How can we, as designers, create artificially intelligent systems that donât hurt humans? What should we think about to make these systems transparent? What information needs to be available to users to engender trust? This talk proposes a model for talking about the major decision points in building an AI.
Carol will tackle the biggest challenges inherent with AI including issues of ethics and the implications for your work. Wondering why you keep hearing about the Trolley Problem? Has someone claimed that your AI is nearly sentient? Bring your questions and curiosity for this engaging evening, and sheâll warn you before spoilers of The Good Place (Š2019 NBCUniversal Media, LLC).
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018Carol Smith
Â
This session focuses on the questions we need to ask to create good, ethical experiences for our users.
Information Architects must push toâŚ
- Keep people at the center of our work.
- Lead with our userâs goals.
- Ease of use, usability, findability, effectiveness, efficiencyâŚ
We must work to mature organizations approach
- Push back on âtechnology firstâ ideas.
- Lead on ethics - for our users, humanity.
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
Â
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.
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17Carol Smith
Â
What is machine learning? Is IA relevant in the age of AI? How can I take advantage of cognitive computing? Learn the basics of these concepts and the implications for your work in this presentation. Carol Smith provides examples of machine learning use and will discuss the challenges inherent in in AI.
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Chetan Khatri
Â
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 âAIâ
Learning Path
Career Path
Designing Trustable AI Experiences at World Usability Day in ClevelandCarol Smith
Â
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.
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in TorontoCarol Smith
Â
Artificially intelligent (AI) technologies are exciting and with them come a lot of new user experience research (UXR) responsibilities. How do we understand and clarify our users need for transparency, control, and access (and more) when the system is constantly changing?
These dynamic systems are already part of our everyday lives and quickly becoming part of our jobs. What are our responsibilities with regard to ethics and protecting users from bias?
Presented at Strive, June 7, 2019 in Toronto, Ontario, Canada. Strive is the 2019 UX Research Conference presented by the UX Research Collective Inc.
Tallk given at #SXSW2019 in the Intelligent Future track as part of the Interactive Festival. We explain 3 frameworks for MachineEthics and how they affect the supervised and unsupervised methods, and the data engineering discipline.
On March 26, 2015 Steve Omohundro gave a talk in the IBM Research 2015 Distinguished Speaker Series at the Accelerated Discovery Lab, IBM Research, Almaden.
Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating âarms racesâ in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial ârational drivesâ of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the âSafe-AI Scaffolding Strategyâ for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by the laws of physics, mathematical proof, and cryptographic complexity. âSmart contractsâ are a promising decentralized cryptographic technology used in Ethereum and other second-generation cryptocurrencies. They can express economic, legal, and political rules and will be a key component in governing autonomous technologies. If we are able to meet the challenges, AI and robotics have the potential to dramatically improve every aspect of human life.
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan KorsankeJan Korsanke
Â
/ My talk from the UXcamp Europe in Berlin. Please enjoy and feel free and don't hesitate to contact me if you have questions or want to talk about UX and AI
What is artificial intelligence, how do we create collaboration and whatâs gonna happen in the future?
Dev Dives: Train smarter, not harder â active learning and UiPath LLMs for do...UiPathCommunity
Â
đĽ Speed, accuracy, and scaling â discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Miningâ˘:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing â with little to no training required
Get an exclusive demo of the new family of UiPath LLMs â GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
đ¨âđŤ Andras Palfi, Senior Product Manager, UiPath
đŠâđŤ Lenka Dulovicova, Product Program Manager, UiPath
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
Â
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties â USA
Expansion of bot farms â how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks â Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Â
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navyâs 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 ATOâs (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Welocme to ViralQR, your best QR code generator.ViralQR
Â
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Â
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
Â
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Â
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Â
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/
1. AI and Machine Learning Demystified
Carol Smith @carologic
Midwest UX 2017, Cincinnati, Ohio
October 13, 2017
2. AI is when Machines
â Exhibit intelligence
â Perceive their environment
â Take actions/make decision to
maximize chance of success at a goal
NAOâs New Job as âConnieâ the concierge at Hilton Hotels
https://developer.softbankrobotics.com/us-en/showcase/nao-ibm-create-new-hilton-concierge
3. AI and ML Demystified / @carologic / MWUX2017
In the extremeâŚ
Google Search for âmovies with AIâ Copyrights as labeled.
4. âMost people working in AI have a healthy skepticism for the idea
of the singularity.
We know how hard it is to get even a little intelligence into a
machine, let alone enough to achieve recursive self-
improvement.â
â Toby Walsh
http://www.wired.co.uk/article/elon-musk-
artificial-intelligence-scaremongering
5. Remember: âWe can unplug the machines!â
Grady Booch, Scientist, philosopher, IBMâer https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
6. AI and ML Demystified / @carologic / MWUX2017
Cognitive computers are
⢠Made with algorithms
⢠Knowledgeable ONLY about what taught
⢠Control ONLY what we give them control of
⢠Aware of nuances and can continue to learn more
7. AI and ML Demystified / @carologic / MWUX2017
Cognitive computers (algorithms) canâŚ
⢠Do very boring work for you
⢠Often make better, more consistent decisions than humans
⢠Be efficient, wonât get tired
Q&A: Should artificial intelligence be legally required to explain itself?
By Matthew Hutson, May. 31, 2017. Interview with Sandra Wachter, data ethics researcher
at Univ. of Oxford and Alan Turing Institute.
http://www.sciencemag.org/news/2017/05/qa-should-artificial-intelligence-be-legally-required-explain-itself
8. AI and ML Demystified / @carologic / MWUX2017
Exhibit intelligence
- transfer human concepts and relationships
Photo by sunlightfoundation
https://www.flickr.com/photos/sunlightfoundation/2385174105
9. AI and ML Demystified / @carologic / MWUX2017
Dependent on Experts
⢠Subject Matter Experts (SMEâs) Availability
â Lawyers
â Machinists
â Insurance adjusters
â Physicians
⢠Usually not experienced in machine learning
â Need close collaboration with those making algorithms
10. AI and ML Demystified / @carologic / MWUX2017
Number Five âNeeds Inputâ
Short Circuit (1986 film) - Ally Sheedy and Number Five
https://en.wikipedia.org/wiki/Short_Circuit_(1986_film)
11. AI and ML Demystified / @carologic / MWUX2017
Content is annotated by experts
Image created by Angela Swindell,
Visual Designer, Watson Knowledge Studio
12. AI and ML Demystified / @carologic / MWUX2017
AI is taxonomies and ontologies coming to life
(NOT like humans learn)
Photo: https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
14. Only as good as data
and time spent improving it
Biased based on what it taught
15. AI and ML Demystified / @carologic / MWUX2017
Creating an AI requires
⢠Algorithms
⢠Documents
⢠Ground truth (annotation)
⢠Teaching
⢠Iteration
⢠Repeat
16. AI and ML Demystified / @carologic / MWUX2017
Supervised (by a human) Machine Learning
Watson Knowledge Studio
https://www.ibm.com/us-en/marketplace/supervised-machine-learning
17. AI and ML Demystified / @carologic / MWUX2017
Knowledge and Accuracy
⢠How important is
accuracy?
⢠Consider a reverse card
sorting exercise
Image: Gerry Gaffney. (2000) What is Card Sorting? Usability Techniques Series,
Information & Design. http://www.infodesign.com.au/usabilityresources/design/cardsorting.asp
18. AI and ML Demystified / @carologic / MWUX2017
Across industries â priority of accuracy varies
Higher Priority
90-99%+
Lower Priority
60-89% accuracy is acceptable
19. AI and ML Demystified / @carologic / MWUX2017
Goal is saving time
Machine learning creates
more highly trained specialists
Not an âall knowingâ being
20. AI and ML Demystified / @carologic / MWUX2017
Cancer Burden in Sub-Saharan Africa
Risk of getting cancer
and
Risk of Dying
~same
The Cancer Atlas http://canceratlas.cancer.org/the-burden/
21. AI and ML Demystified / @carologic / MWUX2017
What if we could reduce the burden?
⢠Bring taxonomies and ontologies to life
⢠Broaden access to evidence based medicine
⢠More informed treatment decisions
22. AI and ML Demystified / @carologic / MWUX2017
AI actions for success
⢠Example: Healthcare
â AI analyzes data (treatment options, similar patients)
â Goal: Provide quick, evidence based options
â Physician selects treatment for patients based on situation
⢠AI success is helping physician (not replacing)
23. AI and ML Demystified / @carologic / MWUX2017
Examples
of AI and Cognitive
Computing
24. AI and ML Demystified / @carologic / MWUX2017
Consider for each example
⢠What intelligence does the system need?
⢠What is the AI perceiving in their environment?
⢠What actions are taken to maximize chance
of success at goal?
25. AI and ML Demystified / @carologic / MWUX2017
Strategic Games
⢠1997 Chess, IBM
⢠2016 Go, Google
⢠Intelligence?
⢠Perception?
⢠Action/Decision?
Floor goban, 2007, By Goban1
https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
26. AI and ML Demystified / @carologic / MWUX2017
Understanding human speech
⢠Watson developed for quiz show Jeopardy!
⢠Won against champions in 2011 for $1 million
Video: âIBM's Watson Supercomputer Destroys Humans in Jeopardy!
Engadgetâ https://www.youtube.com/watch?v=WFR3lOm_xhE
Watson definition: https://en.wikipedia.org/wiki/Watson_(computer)
27. AI and ML Demystified / @carologic / MWUX2017
Decision Making: Self Driving (autonomous) vehicles
Junior, a robotic Volkswagen Passat, in a parking lot at Stanford University
24 October 2009, By: Steve Jurvetson
https://en.wikipedia.org/wiki/File:Hands-free_Driving.jpg
28. AI and ML Demystified / @carologic / MWUX2017
Image Recognition â Google Photos
Carolâs search for âcatsâ on her Google Photos account.
29. AI and ML Demystified / @carologic / MWUX2017
Sound recognition: Labeling of birdsongs
âComparison of machine learning methods applied to birdsong element classificationâ
by David Nicholson. Proceedings of the 15th Python in Science Conference (SCIPY 2016).
http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf
Photo by Gallo71 (Own work) [Public domain], via Wikimedia Commons https://commons.wikimedia.org/wiki/File%3ARbruni.JPG
30. AI and ML Demystified / @carologic / MWUX2017
Analyzing Text: Personality of @carologic (not quite)
Personality Insights applied to @Carologic on Twitter
IBM Watson Developer Cloud: https://personality-insights-livedemo.mybluemix.net/
31. AI and ML Demystified / @carologic / MWUX2017
Automating Repetitive Work
⢠Automated
Radiologist
highlights
possible
issues
⢠Radiologist
confirms
IBMâs Automated Radiologist Can Read Images and Medical Records,
MIT Technology Review
https://www.technologyreview.com/s/600706/ibms-automated-radiologist-can-read-images-and-medical-records/
32. AI and ML Demystified / @carologic / MWUX2017
88,000 retina images
⢠Watson knows what a
healthy eye looks like
⢠Glaucoma is the second
leading cause of
blindness worldwide
â50% of cases go
undetected
Seeing is preventing.
https://twitter.com/IBMWatson/status/844545761740292096
33. AI and ML Demystified / @carologic / MWUX2017
Chatbots for Easy ordering
⢠Order via text, email,
Facebook Messenger or
with a Slackbot
⢠Cognitive pieces:
âSpeech-to-text
âChat
âAPIâs in backend
Story: http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-
Button%E2%80%9D-Life-IBM-Watson
Photo: Easy Button from Staples: http://www.staples.com/Staples-Easy-Button/product_606396
34. AI and ML Demystified / @carologic / MWUX2017
Chatbots â not really AI, yet
⢠Mapping Q & A
âExpected language
âAppropriate automated
responses
âWhen to escalate
to a human
Images: https://www.pexels.com/photo/close-up-of-mobile-phone-248512/
https://www.amazon.com/Amazon-Echo-Bluetooth-Speaker-with-WiFi-Alexa/dp/B00X4WHP5E
https://www.ibm.com/watson/developercloud/doc/conversation/index.html
35. AI and ML Demystified / @carologic / MWUX2017
Optical character recognition (OCR)
⢠Used to be AI
⢠Now considered routine computing
Portable scanner and OCR (video)
https://en.wikipedia.org/wiki/File:Portable_scanner_and_OCR_(video).webm
36. AI and ML Demystified / @carologic / MWUX2017
Ethics in Design for AI
37. Humans teach what we feel is important⌠teach them to share our values.
Super knowing - not super doing
Grady Booch, Scientist, philosopher, IBMâer https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
38. AI and ML Demystified / @carologic / MWUX2017
How might weâŚ
⢠build systems that have ethical and moral foundation?â
⢠that are transparent to users?
⢠teach mercy and justice of law?
⢠extend and advance healthcare?
⢠increase safety in dangerous work?
Inspired by Grady Booch, Scientist, philosopher, IBMâer
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
40. AI and ML Demystified / @carologic / MWUX2017
Guiding Principles â Ethical AI
⢠Purpose
â Aid humans, not replace them
â Symbiotic relationship
â3 guiding principles for ethical AI, from IBM CEO Ginni Romettyâ
by Alison DeNisco. January 17, 2017, Tech Republic http://www.techrepublic.com/article/3-guiding-
principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
41. AI and ML Demystified / @carologic / MWUX2017
Transparency
⢠How was AI taught?
⢠What data was used?
⢠Humans remain in control of the system
â3 guiding principles for ethical AI, from IBM CEO Ginni Romettyâ
by Alison DeNisco. January 17, 2017, Tech Republic http://www.techrepublic.com/article/3-guiding-
principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
42. AI and ML Demystified / @carologic / MWUX2017
Skills
⢠Built with people in the industry
⢠Human workers trained
how to use tools to their advantage
â3 guiding principles for ethical AI, from IBM CEO Ginni Romettyâ
by Alison DeNisco. January 17, 2017, Tech Republic http://www.techrepublic.com/article/3-guiding-
principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
43. AI and ML Demystified / @carologic / MWUX2017
Regulations
⢠Almost everyone agrees they are necessary
⢠Who will create regulations?
⢠Enforce?
44. âWe often have
no way of knowing
when and why people
are biased.â
- Sandra Wachter
Q&A: Should artificial intelligence be legally required to explain itself?
By Matthew Hutson, May. 31, 2017. Interview with Sandra Wachter, data ethics researcher at Univ. of Oxford and Alan Turing Institute.
http://www.sciencemag.org/news/2017/05/qa-should-artificial-intelligence-be-legally-required-explain-itself
45. AI and ML Demystified / @carologic / MWUX2017
The EU General Data Protection Regulation (GDPR)
⢠Framework for transparency rights
and safeguards against automated decision-making
⢠Right to contest a completely automated decision
if it has legal or other significant effects on them
Q&A: Should artificial intelligence be legally required to explain itself?
By Matthew Hutson, May. 31, 2017. Interview with Sandra Wachter, data ethics researcher at Univ. of Oxford and Alan Turing Institute.
http://www.sciencemag.org/news/2017/05/qa-should-artificial-intelligence-be-legally-required-explain-itself
46. AI and ML Demystified / @carologic / MWUX2017
Regulations take forever
⢠Humans and algorithms arenât without bias
⢠ML has potential to make less biased decisions
⢠Algorithms trained with biased data
pick up and replicate biases, and develop new ones
Q&A: Should artificial intelligence be legally required to explain itself?
By Matthew Hutson, May. 31, 2017. Interview with Sandra Wachter, data ethics researcher at Univ. of Oxford and Alan Turing Institute.
http://www.sciencemag.org/news/2017/05/qa-should-artificial-intelligence-be-legally-required-explain-itself
47. AI and ML Demystified / @carologic / MWUX2017
How do we evolve the practice of UX
to deal with the new issues
these technologies bring
and the new information that is created?
48. AI and ML Demystified / @carologic / MWUX2017
Take Responsibility
⢠Create a code of conduct
â What do you value?
â What lines wonât your AI cross?
⢠Make your AI transparent
â How was it made and what does it do?
â How do you reduce bias?
⢠Keep humans in control
49. AI and ML Demystified / @carologic / MWUX2017
Donât fear AI - Explore AI
Try the tools
Pair with others
IBM Watson Developer Tools (free trials):
https://console.ng.bluemix.net/catalog/?category=watson
50. AI and ML Demystified / @carologic / MWUX2017
Go forth and create ethical AIâs
⢠Purpose: Intelligence and actions to maximize success
⢠Transparency: Code of Conduct
⢠Skills: How will humans learn to use it?
51. AI and ML Demystified / @carologic / MWUX2017
Contact Carol
LinkedIn: https://www.linkedin.com/in/caroljsmith
Twitter - @Carologic: https://twitter.com/carologic
Slides on Slideshare: https://www.slideshare.net/carologic
52. AI and ML Demystified / @carologic / MWUX2017
Additional Information
and Resources
53. AI and ML Demystified / @carologic / MWUX2017
Watson is a cognitive technology that can think like a human.
⢠Understand
⢠Analyze and interpret all kinds of data
⢠Unstructured text, images, audio and video
⢠Reason
⢠Understand the personality, tone, and emotion of content
⢠Learn
⢠Grow the subject matter expertise in your apps and systems
⢠Interact
⢠Create chat bots that can engage in dialog
https://www.ibm.com/watson/
54. AI and ML Demystified / @carologic / MWUX2017
More on Strategic Games
Graphic, Science Magazine: http://www.sciencemag.org/news/2016/03/update-why-week-s-
man-versus-machine-go-match-doesn-t-matter-and-what-does
55. AI and ML Demystified / @carologic / MWUX2017
The Job Question
⢠Make new economies
and opportunities â
potentially:
âCreate jobs
âEntire new fields
⢠Some jobs will be lost
âWhat can we do to
mitigate this?
Jobs that no longer exist
The Lector http://www.ranker.com/list/jobs-that-no-longer-exist/coy-jandreau
56. AI and ML Demystified / @carologic / MWUX2017
Tone Analyzer - Watson
IBM Watson Developer Cloud, Tone Analyzer
https://tone-analyzer-demo.mybluemix.net/
57. AI and ML Demystified / @carologic / MWUX2017
Optimistâs guide to the robot apocalypse - @sarahfkessler
âThe optimistâs guide to the robot apocalypseâ by Sarah Kessler. March 09, 2017. QZ.
@sarahfkessler https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
58. AI and ML Demystified / @carologic / MWUX2017
Additional Resources
⢠âHow IBM is Competing with Google in AI.â The Information. https://www.theinformation.com/how-ibm-is-
competing-with-google-in-ai?eu=2zIDMNYNjDp7KqL4YqAXXA
⢠âThe business case for augmented intelligenceâ https://medium.com/cognitivebusiness/the-business-case-for-
augmented-intelligence-36afa64cd675
⢠âComparison of machine learning methods applied to birdsong element classificationâ by David Nicholson.
Proceedings of the 15th Python in Science Conference (SCIPY 2016).
http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf
⢠âStaplesâ âEasy Buttonâ Comes to Life with IBM Watsonâ in Business Wire, October 25, 2016.
http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-
Button%E2%80%9D-Life-IBM-Watson
⢠âHow Staples Is Making Its Easy Button Even Easier With A.I.â by Chris Cancialosi, Forbes.
https://www.forbes.com/sites/chriscancialosi/2016/12/13/how-staples-is-making-its-easy-button-even-easier-
with-a-i/#4ae66e8359ef
⢠âInside Intel: The Race for Faster Machine Learningâ
http://www.intel.com/content/www/us/en/analytics/machine-learning/the-race-for-faster-machine-learning.html
59. AI and ML Demystified / @carologic / MWUX2017
More Resources
⢠âUpdate: Why this weekâs man-versus-machine Go match doesnât matter (and what does)â by Dana
Mackenzie. Science Magazine. Mar. 15, 2016 http://www.sciencemag.org/news/2016/03/update-why-week-s-
man-versus-machine-go-match-doesn-t-matter-and-what-does
⢠âFor IBMâs CTO for Watson, not a lot of value in replicating the human mind in a computer.â by Frederic
Lardinois (@fredericl), TechCrunch, Posted Feb 27, 2017. https://techcrunch.com/2017/02/27/for-ibms-cto-for-
watson-not-a-lot-of-value-in-replicating-the-human-mind-in-a-computer/
⢠âGoogle and IBM: We Want Artificial Intelligence to Help You, Not Replace Youâ Most Powerful Women by
Michelle Toh. Mar 02, 2017. Fortune. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
⢠âFacebook scales back AI flagship after chatbots hit 70% f-AI-lure rate - 'The limitations of automationââ by
Andrew Orlowski. Feb 22, 2017. The Register https://www.theregister.co.uk/2017/02/22/facebook_ai_fail/
⢠âMicrosoft is deleting its AI chatbot's incredibly racist tweetsâ by Rob Price. Mar. 24, 2016. Business Insider
UK. http://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3
Special Thanks: Soundtrack to 'Run Lola Run', 1998 German thriller film written and directed by Tom Tykwer, and
starring Franka Potente as Lola and Moritz Bleibtreu as Manni. Soundtrack by Tykwer, Johnny Klimek, and
Reinhold Heil
60. AI and ML Demystified / @carologic / MWUX2017
Even More Resources
⢠âIBMâs Automated Radiologist Can Read Images and Medical Recordsâ by Tom Simonite, February 4, 2016.
Intelligent Machines, MIT Technology Review. https://www.technologyreview.com/s/600706/ibms-automated-
radiologist-can-read-images-and-medical-records/
⢠âThe IBM, Salesforce AI Mash-Up Could Be a Stroke of Geniusâ by Adam Lashinsky, Mar 07, 2017. Fortune.
http://fortune.com/2017/03/07/data-sheet-ibm-salesforce/
⢠"Google can now tell you're not a robot with just one click" by Andy Greenberg. Dec. 3, 2014. Security: Wired.
https://www.wired.com/2014/12/google-one-click-recaptcha/
⢠âEssentials of Machine Learning Algorithms (with Python and R Codes)â by Sunil Ray, August 10, 2015.
Analytics Vidhya. https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/
⢠IBM on Machine Learning https://www.ibm.com/analytics/us/en/technology/machine-learning/
⢠âAt Davos, IBM CEO Ginni Rometty Downplays Fears of a Robot Takeoverâ by Claire Zillman, Jan 18, 2017.
Fortune. http://fortune.com/2017/01/18/ibm-ceo-ginni-rometty-ai-davos/
⢠âGoogle and IBM: We Want Artificial Intelligence to Help You, Not Replace Youâ by Michelle Toh. Mar 02,
2017. Fortune. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
61. AI and ML Demystified / @carologic / MWUX2017
Yes, even more resources
⢠Video: âIBM Watson Knowledge Studio: Teach Watson about your unstructured dataâ
https://www.youtube.com/watch?v=caIdJjtvX1s&t=6s
⢠âThe optimistâs guide to the robot apocalypseâ by Sarah Kessler, @sarahfkessler. March 09, 2017. QZ.
https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
⢠âAI Influencers 2017: Top 30 people in AI you should follow on Twitter" by Trips Reddy @tripsy, Senior
Content Manager, IBM Watson . February 10, 2017 https://www.ibm.com/blogs/watson/2017/02/ai-
influencers-2017-top-25-people-ai-follow-twitter/
⢠â3 guiding principles for ethical AI, from IBM CEO Ginni Romettyâ by Alison DeNisco. January 17, 2017, Tech
Republic http://www.techrepublic.com/article/3-guiding-principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
⢠"Transparency and Trust in the Cognitive Era" January 17, 2017 Written by: IBM THINK Blog
https://www.ibm.com/blogs/think/2017/01/ibm-cognitive-principles/
⢠"Ethics and Artificial Intelligence: The Moral Compass of a Machineâ by Kris Hammond, April 13, 2016.
Recode. http://www.recode.net/2016/4/13/11644890/ethics-and-artificial-intelligence-the-moral-compass-of-a-
machine
62. AI and ML Demystified / @carologic / MWUX2017
Last bit: I promise
⢠"The importance of human innovation in A.I. ethics" by John C. Havens. Oct. 03, 2015
http://mashable.com/2015/10/03/ethics-artificial-intelligence/#yljsShvAFsqy
⢠"Me, Myself and AI" Fjordnet Limited 2017 - Accenture Digital.
https://trends.fjordnet.com/trends/me-myself-ai
⢠"Testing AI concepts in user research" By Chris Butler, Mar 2, 2017. https://uxdesign.cc/testing-ai-
concepts-in-user-research-b742a9a92e55#.58jtc7nzo
⢠"CMU prof says computers that can 'see' soon will permeate our livesâ by Aaron Aupperlee. March
16, 2017. http://triblive.com/news/adminpage/12080408-74/cmu-prof-says-computers-that-can-
see-soon-will-permeate-our-lives
⢠âThe business case for augmented intelligenceâ by Nancy Pearson, VP Marketing, IBM Cognitive.
https://medium.com/cognitivebusiness/the-business-case-for-augmented-intelligence-
36afa64cd675#.qqzvunakw
63. AI and ML Demystified / @carologic / MWUX2017
Definition: Artificial Intelligence
⢠Artificial intelligence (AI) is intelligence exhibited by machines.
⢠In computer science, an ideal "intelligent" machine is a flexible rational agent that
perceives its environment and takes actions that maximize its chance of success
at some goal.[1] Colloquially, the term "artificial intelligence" is applied when a
machine mimics "cognitive" functions that humans associate with other human
minds, such as "learning" and "problem solving".[2]
⢠Capabilities currently classified as AI include successfully understanding human
speech,[4] competing at a high level in strategic game systems (such as Chess
and Go[5]), self-driving cars, and interpreting complex data.
Wikipedia: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
64. AI and ML Demystified / @carologic / MWUX2017
Definition: The Singularity
⢠If research into Strong AI produced sufficiently intelligent software, it might be able to reprogram
and improve itself. The improved software would be even better at improving itself, leading to
recursive self-improvement.[245] The new intelligence could thus increase exponentially and
dramatically surpass humans. Science fiction writer Vernor Vinge named this scenario
"singularity".[246] Technological singularity is when accelerating progress in technologies will
cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and
control, thus radically changing or even ending civilization. Because the capabilities of such an
intelligence may be impossible to comprehend, the technological singularity is an occurrence
beyond which events are unpredictable or even unfathomable.[246]
⢠Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in
digital technology) to calculate that desktop computers will have the same processing power as
human brains by the year 2029, and predicts that the singularity will occur in 2045.[246]
Wikipedia: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
65. AI and ML Demystified / @carologic / MWUX2017
Definition: Machine Learning
⢠Ability for system to take basic knowledge (does not mean simple or non-complex)
and apply that knowledge to new data
⢠Raises ability to discover new information. Find unknowns in data.
⢠https://en.wikipedia.org/wiki/Machine_learning
More Definitions:
⢠Algorithm: a process or set of rules to be followed in calculations or other problem-
solving operations, especially by a computer.
https://en.wikipedia.org/wiki/Algorithm
⢠Natural Language Processing (NLP):
https://en.wikipedia.org/wiki/Natural_language_processing