For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
The Future of AI is Generative not Discriminative 5/26/2021Steve Omohundro
The deep learning AI revolution has been sweeping the world for a decade now. Deep neural nets are routinely used for tasks like translation, fraud detection, and image classification. PwC estimates that they will create $15.7 trillion/year of value by 2030. But most current networks are "discriminative" in that they directly map inputs to predictions. This type of model requires lots of training examples, doesn't generalize well outside of its training set, creates inscrutable representations, is subject to adversarial examples, and makes knowledge transfer difficult. People, in contrast, can learn from just a few examples, generalize far beyond their experience, and can easily transfer and reuse knowledge. In recent years, new kinds of "generative" AI models have begun to exhibit these desirable human characteristics. They represent the causal generative processes by which the data is created and can be compositional, compact, and directly interpretable. Generative AI systems that assist people can model their needs and desires and interact with empathy. Their adaptability to changing circumstances will likely be required by rapidly changing AI-driven business and social systems. Generative AI will be the engine of future AI innovation.
How can we use generative AI in learning products? A rapid introduction to generative AI. Presented at ED Games Expo 2023 at the U.S. Department of Education, September 22, 2023.
Exploring Opportunities in the Generative AI Value Chain.pdfDung Hoang
The article "Exploring Opportunities in the Generative AI Value Chain" by McKinsey & Company's QuantumBlack provides insights into the value created by generative artificial intelligence (AI) and its potential applications.
Chat GPT 4 can pass the American state bar exam, but before you go expecting to see robot lawyers taking over the courtroom, hold your horses cowboys – we're not quite there yet. That being said, AI is becoming increasingly more human-like, and as a VC we need to start thinking about how this new wave of technology is going to affect the way we build and run businesses. What do we need to do differently? How can we make sure that our investment strategies are reflecting these changes? It's a brave new world out there, and we’ve got to keep the big picture in mind!
Sharing here with you what we at Cavalry Ventures found out during our Generative AI deep dive.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
Understanding generative AI models A comprehensive overview.pdfStephenAmell4
Generative AI refers to a branch of artificial intelligence that focuses on enabling machines to generate new and original content. Unlike traditional AI systems that follow predefined rules and patterns, generative AI leverages advanced algorithms and neural networks to autonomously produce outputs that mimic human creativity and decision-making.
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
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
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
For many decades now, the software industry has attempted to bridge the productivity gap, develop higher quality code and manage the ever growing complexity of software-intensive systems. The results have been mixed, and as a result, a great majority of today's software is still written manually by human developers. This is about to change rapidly as recent developments in the field of Artificial Intelligence show promising results. While artists and designers have been taken by surprise by OpenAI’s DALL-E 2’s capabilities in designing unique art, ChatGPT has astonished the rest of the world with its capability of understanding human interaction. AI-assisted coding solutions such as Github’s Copilot and Replit’s Ghostwriter, among many others, are rapidly developing in a direction where AI generates new code that runs fast with high quality. Little is known about the true capabilities of AI programmers and their impact on the software development industry, education, and research. This talk sheds light on the current state of ChatGPT, large language models including GPT-4, AI-assisted coding, highlights the research gaps, and proposes a way forward.
Cascon 2016 Keynote: Disrupting Developer Productivity One Bot at a TimeMargaret-Anne Storey
Conversational bots have become a popular addition to many mainstream platforms and software engineering has adopted them at an almost dizzying pace across every phase of the development life cycle. Bots reportedly help developers become more productive by automating tedious tasks, by bringing awareness of important project or community activities, and by reducing interruptions. Developers "talk to" and "listen to" these bots in the same conversational channels they use to collaborate with and monitor each other. However, the actual impact these bots have on developer productivity and project quality is still unclear. In this talk, I will give an overview of how bots play a prominent role in software development and discuss the benefits and challenges that can arise from relying on these "new virtual team members". I will also explore how bots may influence other knowledge work domains and propose a number of future directions for practitioners and researchers to consider.
As presented on November 28, 2023 at the Christa McAuliffe Technology Conference. Please email me with any comments, questions, or suggestions. Maureen Yoder myoder@lesley.edu
The Future of AI is Generative not Discriminative 5/26/2021Steve Omohundro
The deep learning AI revolution has been sweeping the world for a decade now. Deep neural nets are routinely used for tasks like translation, fraud detection, and image classification. PwC estimates that they will create $15.7 trillion/year of value by 2030. But most current networks are "discriminative" in that they directly map inputs to predictions. This type of model requires lots of training examples, doesn't generalize well outside of its training set, creates inscrutable representations, is subject to adversarial examples, and makes knowledge transfer difficult. People, in contrast, can learn from just a few examples, generalize far beyond their experience, and can easily transfer and reuse knowledge. In recent years, new kinds of "generative" AI models have begun to exhibit these desirable human characteristics. They represent the causal generative processes by which the data is created and can be compositional, compact, and directly interpretable. Generative AI systems that assist people can model their needs and desires and interact with empathy. Their adaptability to changing circumstances will likely be required by rapidly changing AI-driven business and social systems. Generative AI will be the engine of future AI innovation.
How can we use generative AI in learning products? A rapid introduction to generative AI. Presented at ED Games Expo 2023 at the U.S. Department of Education, September 22, 2023.
Exploring Opportunities in the Generative AI Value Chain.pdfDung Hoang
The article "Exploring Opportunities in the Generative AI Value Chain" by McKinsey & Company's QuantumBlack provides insights into the value created by generative artificial intelligence (AI) and its potential applications.
Chat GPT 4 can pass the American state bar exam, but before you go expecting to see robot lawyers taking over the courtroom, hold your horses cowboys – we're not quite there yet. That being said, AI is becoming increasingly more human-like, and as a VC we need to start thinking about how this new wave of technology is going to affect the way we build and run businesses. What do we need to do differently? How can we make sure that our investment strategies are reflecting these changes? It's a brave new world out there, and we’ve got to keep the big picture in mind!
Sharing here with you what we at Cavalry Ventures found out during our Generative AI deep dive.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
Understanding generative AI models A comprehensive overview.pdfStephenAmell4
Generative AI refers to a branch of artificial intelligence that focuses on enabling machines to generate new and original content. Unlike traditional AI systems that follow predefined rules and patterns, generative AI leverages advanced algorithms and neural networks to autonomously produce outputs that mimic human creativity and decision-making.
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
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
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
For many decades now, the software industry has attempted to bridge the productivity gap, develop higher quality code and manage the ever growing complexity of software-intensive systems. The results have been mixed, and as a result, a great majority of today's software is still written manually by human developers. This is about to change rapidly as recent developments in the field of Artificial Intelligence show promising results. While artists and designers have been taken by surprise by OpenAI’s DALL-E 2’s capabilities in designing unique art, ChatGPT has astonished the rest of the world with its capability of understanding human interaction. AI-assisted coding solutions such as Github’s Copilot and Replit’s Ghostwriter, among many others, are rapidly developing in a direction where AI generates new code that runs fast with high quality. Little is known about the true capabilities of AI programmers and their impact on the software development industry, education, and research. This talk sheds light on the current state of ChatGPT, large language models including GPT-4, AI-assisted coding, highlights the research gaps, and proposes a way forward.
Cascon 2016 Keynote: Disrupting Developer Productivity One Bot at a TimeMargaret-Anne Storey
Conversational bots have become a popular addition to many mainstream platforms and software engineering has adopted them at an almost dizzying pace across every phase of the development life cycle. Bots reportedly help developers become more productive by automating tedious tasks, by bringing awareness of important project or community activities, and by reducing interruptions. Developers "talk to" and "listen to" these bots in the same conversational channels they use to collaborate with and monitor each other. However, the actual impact these bots have on developer productivity and project quality is still unclear. In this talk, I will give an overview of how bots play a prominent role in software development and discuss the benefits and challenges that can arise from relying on these "new virtual team members". I will also explore how bots may influence other knowledge work domains and propose a number of future directions for practitioners and researchers to consider.
As presented on November 28, 2023 at the Christa McAuliffe Technology Conference. Please email me with any comments, questions, or suggestions. Maureen Yoder myoder@lesley.edu
The training content covers:
- Basics of Artificial Intelligence
- Penetration of AI in our daily lives
- Few examples and Use cases
- A brief on how future with AI looks like
To Bot or Not: How Bots can Support Collaboration in Software Engineering (I...Margaret-Anne Storey
Abstract and video link below)
Presented at ICGSE 2016: Conference on Global Software Engineering (http://www.ics.uci.edu/~icgse2016/2_0cfp.html)
Video link: https://www.youtube.com/watch?v=BsgnLwPMqWM&feature=youtu.be&list=PLcm9UtazJCOLBwPaaHNn_htAjPAXIdRGr
Abstract:
Software development stakeholders require a constellation of tools to support their communication, collaboration and coordination activities. But poor tool integration can lead to gaps in knowledge flow, or worse, to an overabundance of shared communication and information. The software development community is witnessing the rise of "social bots" to integrate diverse development and communication tools and to address the challenge of information overload. A bot is a conversational user interface that can automate rote or tedious tasks. It may fetch or share information, extract and analyze data, detect and monitor events and activities in communication and social media, connect developers with each other or with other tools, or it may provide feedback on individual and collaborative development tasks. Some bots are emerging as important team members, providing support for individual and team task management and for the automation of dev-ops and customer support. However, the rapid adoption of bots and the platforms that support them brings possible drawbacks. Designing effective platforms for bots is challenging and bots may introduce alienation among stakeholders or lead to other technical challenges. In this talk, I will discuss the emerging role of bots in software development and describe some of the advantages and challenges that may lie ahead.
USECON Webinar 2017: Alina's Guests - Floor Drees from sektor5USECON
Everyone working in Artificial Intelligence (AI)/chatbots, has the opportunity to further develop technology which will affect the future of especially finance/payment, transport and health. The main question is how human-like‘ these solutions will need to be (if at all) in order to be adopted. And how will the future of employment look like?
USECON Webinar "Alina's Guests": Chatbots with Floor Drees from sektor5Alina Köhler
Everyone working in Artificial Intelligence (AI)/chatbots, has the opportunity to further develop technology which will affect the future of especially finance/payment, transport and health. The main question is how human-like‘ these solutions will need to be (if at all) in order to be adopted. And how will the future of employment look like?
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
This is an article about Generative AI. It discusses what it is and the different techniques used to create it. It also goes into the potential uses of Generative AI. Some of the important points from this article are that Generative AI is still in its early stages but has already shown promising results. It is also important to note that Generative AI can be used to create fake data that is indistinguishable from real data.
https://www.ltimindtree.com/wp-content/uploads/2023/01/DeepPoV-Generative-AI.pdf
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Produced by Nathan Benaich and Air Street Capital team
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017Carol Smith
Cognitive computing and machine learning are not new concepts, but they are new to most UX’ers. 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, we’ll look at examples of AI in use and discuss the relevancy of design work in the age of AI. Additionally, we’ll explore the ethical challenges inherent with the use of AI from the user’s perspective, specifically regarding trust and transparency.
This was presented at Fluxible 2017 in Kitchener-Waterloo, Ontario, Canada on 23 Sept 2017.
1.Wireless Communication System_Wireless communication is a broad term that i...JeyaPerumal1
Wireless communication involves the transmission of information over a distance without the help of wires, cables or any other forms of electrical conductors.
Wireless communication is a broad term that incorporates all procedures and forms of connecting and communicating between two or more devices using a wireless signal through wireless communication technologies and devices.
Features of Wireless Communication
The evolution of wireless technology has brought many advancements with its effective features.
The transmitted distance can be anywhere between a few meters (for example, a television's remote control) and thousands of kilometers (for example, radio communication).
Wireless communication can be used for cellular telephony, wireless access to the internet, wireless home networking, and so on.
This 7-second Brain Wave Ritual Attracts Money To You.!nirahealhty
Discover the power of a simple 7-second brain wave ritual that can attract wealth and abundance into your life. By tapping into specific brain frequencies, this technique helps you manifest financial success effortlessly. Ready to transform your financial future? Try this powerful ritual and start attracting money today!
Multi-cluster Kubernetes Networking- Patterns, Projects and GuidelinesSanjeev Rampal
Talk presented at Kubernetes Community Day, New York, May 2024.
Technical summary of Multi-Cluster Kubernetes Networking architectures with focus on 4 key topics.
1) Key patterns for Multi-cluster architectures
2) Architectural comparison of several OSS/ CNCF projects to address these patterns
3) Evolution trends for the APIs of these projects
4) Some design recommendations & guidelines for adopting/ deploying these solutions.
ER(Entity Relationship) Diagram for online shopping - TAEHimani415946
https://bit.ly/3KACoyV
The ER diagram for the project is the foundation for the building of the database of the project. The properties, datatypes, and attributes are defined by the ER diagram.
1. An Introduction
to Generative AI
Cori Faklaris
Assistant Professor, Dept. of Software and Information Systems
Charlotte AI Institute for Smarter Learning, UNC Charlotte Dubois Center, May 18, 2023
2. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 2
Key takeaways from this talk
● Generative AI tools are great for PRODUCTIVITY - they can be nifty shortcuts
to dispose of low-value tasks and / or to jumpstart creativity
● Generative AI tools should always be used - and taught to be used - with a
critical mind, because they are prone to mistakes and “hallucinations”
4. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 4
Lots of hype - and doom /gloom - around AI right now …
It’s difficult to know where to look or how to start to understand AI
We tend to be afraid of things that we don’t understand
#evilbrag
5. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 5
When you hear “AI,” think “statistical pattern-matching”
● Oracle describes AI this way:
AI has become a catchall term for
applications that perform complex tasks
that once required human input, such as
communicating with customers online or
playing chess.
The term is often used interchangeably
with … machine learning (ML) and deep
learning.
Text from What is Artificial Intelligence (AI)? Oracle, n.d. Retrieved May 16, 2023 from https://www.oracle.com/artificial-intelligence/what-is-ai/
Image from Pattern Recognition. GeeksforGeeks. Retrieved May 16, 2023 from https://www.geeksforgeeks.org/pattern-recognition-introduction/
The data is “tokenized” (= made
into “chunks” of words, punctuation
marks, pixels, etc.) during this
process - remember this for later
6. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 6
AI has been with us for years, whether “generative” or not
Google and other search engines
Social media recommendations
Conversational user interfaces such as Siri and Alexa
Sensor-informed driver assistants in cars and trucks
“Auto-complete” and “smart replies” for email and text messaging
Tiktok screenshots from J. D. Biersdorfer. 2022. The Latecomer’s Guide to TikTok. The New York Times. Retrieved May 16, 2023 from https://www.nytimes.com/2022/10/26/technology/personaltech/tiktok-guide-latecomers.html
ADAS images from Wikipedia contributors. 2023. Advanced driver-assistance system. Wikipedia, The Free Encyclopedia. Retrieved from https://en.wikipedia.org/w/index.php?title=Advanced_driver-assistance_system&oldid=1150142876
7. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 7
Now, AI can synthesize part or all of a creative work
● McKinsey defines generative AI as:
… Algorithms (such as ChatGPT) that can
be used to create new content, including
audio, code, images, text, simulations, and
videos.
Recent breakthroughs in the field have the
potential to drastically change the way we
approach content creation.
Text and image from What is generative AI? McKinsey. Retrieved May 16, 2023 from https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai
8. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 8
How Generative AI works (admittedly oversimplified)
The system generates text or images using its previously built model of the
statistical distributions of tokens (= “chunks” of words, punctuation marks,
pixels, etc.) created from its very large training dataset.
Image from Pattern Recognition. GeeksforGeeks. Retrieved May 16, 2023 from https://www.geeksforgeeks.org/pattern-recognition-introduction/
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
Doc
Chat
Image
9. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 9
How Generative AI works (admittedly oversimplified)
It might make mistakes or “hallucinate” based on the limitations of its
process, but the output still might look like what you wanted.
Ted Chiang’s analogy = “unreliable photocopier” or a “blurry JPEG”
Ted Chiang. 2023. ChatGPT Is a Blurry JPEG of the Web. The New Yorker. Retrieved May 10, 2023 from https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
Doc
Chat
Image
10. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 10
How Generative AI works (admittedly oversimplified)
Ted Chiang’s analogy = “unreliable photocopier” / blurry JPEG image
https://commons.wikimedia.org/wik
i/File:Blurry_eiffel.jpg - shared
under CC-SA 4.0 license
11. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 11
How Generative AI works (admittedly oversimplified)
We can ask it
questions - but a
very specific type
of question known
as prompts,
following this
structure:
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
“Here’s a fragment of text.
Tell me how this fragment might <continue on in
this language, or suggest a particular image>.
According to your model of the statistics of
<human language, or human-handled images>,
what <words, or pixels> are likely to come next?”
12. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 12
How Generative AI works (admittedly oversimplified)
The prompts are converted into tokens (= “chunks” of words, punctuation marks,
pixels, etc.), then the system analyzes what is likely to come next, based on the
tokens in its own dataset (as many as 32,000 in GPT-4!).
It then generates a tokenized output.
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
Vector of
probabilities from
own tokens
13. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 13
How Generative AI works (admittedly oversimplified)
With each output, it keeps re-analyzing the probabilities to decide next tokens.
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and shopped
Vector of
probabilities from
own tokens
14. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 14
HERE’S THE REALLY COOL PART!!!
Transformers (the “T in “GPT”) know how to direct attention to specific parts
of the input to guide their selection of the output - such as verb tenses, objects.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention Is All You Need. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/1706.03762
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and shopped
Vector of
probabilities from
own tokens
15. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 15
How Generative AI works (admittedly oversimplified)
The system can give you different answers to the same inputs:
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and bought
Vector of
probabilities from
own tokens
16. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 16
How Generative AI works (admittedly oversimplified)
The system can give you different answers to the same inputs:
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and clocked in
Vector of
probabilities from
own tokens
17. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 17
How Generative AI works (admittedly oversimplified)
The system can give you different answers to the same inputs:
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and danced
Vector of
probabilities from
own tokens
huh?
18. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 18
How Generative AI works (admittedly oversimplified)
“Hallucinations” - when the output doesn’t seem to make sense - are why it is
important not to accept everything it outputs at face value.
Murray Shanahan. 2022. Talking About Large Language Models. arXiv [cs.CL]. Retrieved from http://arxiv.org/abs/2212.03551
Bea Stollnitz. How generative language models work. Retrieved May 10, 2023 from https://bea.stollnitz.com/blog/how-gpt-works/
n tokens in 1 token out
She went to the store and danced
Vector of
probabilities from
own tokens
huh?
19. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 19
Examples of publicly available Generative AI tools
Crowdsourced list of
available AI tools:
https://bit.ly/UsefulLLMs
21. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 21
Use DALL-E 2 to create images for course slides
- Goal 1: Quickly
source visuals
that add interest
and reinforce
content
- Goal 2:
Demonstrate
limits of AI output
with limited inputs
or prompts
22. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 22
Use ChatGPT to create first draft of biography text
- Goal 1: Cut the
time spent on
low-value but
necessary job
tasks
- Goal 2: Goof
around with
fellow academics
on social media
23. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 23
Use BingChat to draft a grant proposal
- Goal 1: Overcome
“analysis
paralysis”, make
yourself laugh in
the process
- Goal 2:
Experiment with a
sequence of
prompts for
sophisticated
outputs
24. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 24
Assign students to
pick/use a tool, then
critique the output
- Goal 1: Give permission
and encouragement to
play around with new
tech
- Goal 2: Mentor class
members in how to think
critically use of AI tools
25. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 25
My syllabus policy on “Use of AI and Other Creative Tools”
In this course, students are permitted to use tools such as Stable Diffusion, DALL-E,
ChatGPT, and BingChat. In general, permitted use of such tools is consistent with permitted
use of non-AI assistants such as Grammarly, templating tools such as Canva, or images or
text sourced from the internet or others’ files.
No student may submit an assignment or work on an exam as their own that is entirely
generated by means of an AI tool.
If students use an AI tool or other creative tool to generate, draft, create, or compose any
portion of any assignment, they must (a) credit the tool, (b) identify what part of the work is
from the AI tool and what is from themselves, and (c) briefly summarize why they decided to
use the tool and include its output.
Cori Faklaris. 2023. Policy on Use of AI Tools for my course syllabus, version 1.0. Cori Faklaris’ blog – HeyCori. Retrieved May 16, 2023 from
https://blog.corifaklaris.com/2023/03/17/policy-on-use-of-ai-tools-for-my-course-syllabus-version-1-0/#.ZGPtWezMJqs
26. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 26
Some actual and/or realistic risks of using generative AI
● Violations of data privacy
○ Some students told me they do not feel comfortable giving up any data to such services, such
as may be required for creating an account. For these students, I created an alternate
assignment for Slide 24, using a search engine.
● Violations of intellectual property
○ Check the Terms of Service - will your inputs or prompts be used as training data?
● Violations of academic integrity
○ Do a spot check of outputs, using a search engine, to see if any are wholly from another work
○ Analyze submitted work using Open AI’s AI Text Classifier or the multi-service GPTZero
27. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 27
Humans’ #1 skill set will continue to be communication
Screenshot from
https://twitter.com/TheRealOllieLaw/status/
1656605938374307840?s=20
28. An Introduction to Generative AI | Cori Faklaris, Assistant Professor, Dept. of Software and Info. Systems | Page 28
Key takeaways
● Generative AI tools can be nifty
shortcuts to dispose of low-value tasks
and / or to jumpstart creativity.
● Generative AI tools should always be
used with your “thinking cap” on
because they are prone to mistakes
and “hallucinations.”
Thank you for listening!
Crowdsourced list of
available AI tools:
https://bit.ly/UsefulLLMs