This document provides an introduction to artificial intelligence (AI) and how it can simplify daily life. It defines AI as the simulation of human intelligence by machines, including abilities like problem-solving, rational thinking, and acting like humans. The document discusses examples of AI like Alexa and Siri, the history of AI, applications of AI in medicine, telecommunications and gaming. It also outlines advantages of AI like reducing human error and disadvantages like potential job losses. The conclusion is that continued development of AI by engineers will change the world and help solve problems humans cannot.
Intelligence: “The capacity to learn and solve problems.”
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Till now we have discussed in brief about Artificial Intelligence.
We have discussed some of its principles, its applications, its achievements etc.
The ultimate goal of institutions and scientists working of AI is to solve majority of the problems or to achieve the tasks which we humans directly can’t accomplish.
It is for sure that development in this field of computer science will change the complete scenario of the world. Now it is the responsibility of creamy layer of engineers to develop this field.
Presentación sobre inteligencia artificial. Los neofito dueños del sitio quieren hacerse millonarios a costa del esfuerzo de los usuarios. Lo malo es que no le dan ni un solo peso al usuario que sube sus trabajos. Sin embargo ellos les cobra a los demás U$s 100 por mes.
machines will be capable, within 20 years, of doing any work a man can do." Two years later, MIT researcher Marvin Minsky predicted, "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."
(artificial intelligence innovator Herbert Simon.1965
Intelligence: “The capacity to learn and solve problems.”
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Till now we have discussed in brief about Artificial Intelligence.
We have discussed some of its principles, its applications, its achievements etc.
The ultimate goal of institutions and scientists working of AI is to solve majority of the problems or to achieve the tasks which we humans directly can’t accomplish.
It is for sure that development in this field of computer science will change the complete scenario of the world. Now it is the responsibility of creamy layer of engineers to develop this field.
Presentación sobre inteligencia artificial. Los neofito dueños del sitio quieren hacerse millonarios a costa del esfuerzo de los usuarios. Lo malo es que no le dan ni un solo peso al usuario que sube sus trabajos. Sin embargo ellos les cobra a los demás U$s 100 por mes.
machines will be capable, within 20 years, of doing any work a man can do." Two years later, MIT researcher Marvin Minsky predicted, "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."
(artificial intelligence innovator Herbert Simon.1965
Contents:
Introduction
History
Definition
Examples
New Related Literature
Advantage
Disadvantage
Summary
Conclusion
HISTORY
The idea of AI as far back as ancient Greece. Greek myths speak of Hephaestus, a blacksmith who created mechanical servants.
Fast forward to 1935, when the earliest substantial work in this field was done by Alan Turing, a logician and compter pioneer.
-TURING MACHINE
1951: Christopher Strachey wrote the first successful AI program
- COMPUTER CHECKERS PROGRAM
1956: John McCarthy coined the term Artificial Intelligence
1963: ANALOGY, a program created by Thomas Evans, proved that computers can solve IQ test analogy problems
1967: First successful knowledge-based program in science and mathematics
1972: SHRDLU created by Terry Winograd
- Robot arm responded to commands
1987: Marvin Minsky publishes The Society of Mind, which portrays the brain as a series of cooperating agents
1997: A chess program, Deep Blue, beats the current world chess champion, Gary Kasparov
2000’s: Interactive robot smart toys are made commercially available
Define an Artificial Intelligence……. ?
EXAMPLES
1. Google Maps and Ride-Hailing Applications
2. Face Detection and Recognition
3. Text Editors or Autocorrect
4. Chatbots
5. Online-Payments
NEWS RELATED LITERATURE
ADVANTAGE
THE FUTURE OF ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON SOCIETY.pdfSyedZakirHussian
Artificial Intelligence (AI) is the talk of the town! It’s no longer just the stuff of science fiction, but a rapidly evolving technology that’s changing our world in ways we couldn’t have imagined just a few short years ago. From Siri and Alexa to self-driving cars and smart homes, AI is already playing a significant role in our daily lives. But what does the future hold for this cutting-edge technology? How will it continue to impact our society?
In this blog, we’ll be exploring the future of Artificial Intelligence and its impact on society. From advancements in healthcare and employment to privacy and security concerns, we’ll take a deep dive into the many ways AI is shaping our world. And, because we believe that life is too short to be serious all the time, we’ll also sprinkle in a bit of humor to keep things interesting. So, buckle up, and let’s go on a journey to the future!
The advancements in AI are nothing short of remarkable, and it’s exciting to think about what the future holds. But it’s important to remember that with great power comes great responsibility. As we move forward with AI, it’s essential to consider the potential impact on society and to develop responsible practices to ensure that this technology is used for the greater good. We hope this blog will provide a valuable resource for those interested in learning more about the future of Artificial Intelligence and its impact on society.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Contents:
Introduction
History
Definition
Examples
New Related Literature
Advantage
Disadvantage
Summary
Conclusion
HISTORY
The idea of AI as far back as ancient Greece. Greek myths speak of Hephaestus, a blacksmith who created mechanical servants.
Fast forward to 1935, when the earliest substantial work in this field was done by Alan Turing, a logician and compter pioneer.
-TURING MACHINE
1951: Christopher Strachey wrote the first successful AI program
- COMPUTER CHECKERS PROGRAM
1956: John McCarthy coined the term Artificial Intelligence
1963: ANALOGY, a program created by Thomas Evans, proved that computers can solve IQ test analogy problems
1967: First successful knowledge-based program in science and mathematics
1972: SHRDLU created by Terry Winograd
- Robot arm responded to commands
1987: Marvin Minsky publishes The Society of Mind, which portrays the brain as a series of cooperating agents
1997: A chess program, Deep Blue, beats the current world chess champion, Gary Kasparov
2000’s: Interactive robot smart toys are made commercially available
Define an Artificial Intelligence……. ?
EXAMPLES
1. Google Maps and Ride-Hailing Applications
2. Face Detection and Recognition
3. Text Editors or Autocorrect
4. Chatbots
5. Online-Payments
NEWS RELATED LITERATURE
ADVANTAGE
THE FUTURE OF ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON SOCIETY.pdfSyedZakirHussian
Artificial Intelligence (AI) is the talk of the town! It’s no longer just the stuff of science fiction, but a rapidly evolving technology that’s changing our world in ways we couldn’t have imagined just a few short years ago. From Siri and Alexa to self-driving cars and smart homes, AI is already playing a significant role in our daily lives. But what does the future hold for this cutting-edge technology? How will it continue to impact our society?
In this blog, we’ll be exploring the future of Artificial Intelligence and its impact on society. From advancements in healthcare and employment to privacy and security concerns, we’ll take a deep dive into the many ways AI is shaping our world. And, because we believe that life is too short to be serious all the time, we’ll also sprinkle in a bit of humor to keep things interesting. So, buckle up, and let’s go on a journey to the future!
The advancements in AI are nothing short of remarkable, and it’s exciting to think about what the future holds. But it’s important to remember that with great power comes great responsibility. As we move forward with AI, it’s essential to consider the potential impact on society and to develop responsible practices to ensure that this technology is used for the greater good. We hope this blog will provide a valuable resource for those interested in learning more about the future of Artificial Intelligence and its impact on society.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
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Topics covered:
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UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
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What you will learn during the webinar:
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- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
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Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
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Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
4. Introduction
Artificial Intelligence : Artificial Intelligence (AI) is
the simulation of human intelligence by machines.
1. The ability to solve problem.
2. The ability to act rationally.
3. The ability to act like humans.
The central principles of AI include :
1. Reasoning, knowledge, planning, learning and communication.
2. Perception and the ability to move and manipulate objects.
3. It is the science and engineering of
4. making intelligent machines, especially intelligent computer programs.
• Intelligence: “The capacity to learn and
solve problems.”
5. Introduction to
Artificial
Intelligence
• Artificial Intelligence (AI) refers
to the ability of machines to
perform tasks that typically require
human intelligence, such as visual
perception, speech recognition,
decision-making, and language
translation.
• AI has become increasingly
popular in recent years due to
advancements in machine learning
algorithms, big data processing
capabilities, and the availability of
powerful computing resources.
6. Example of A.I.
• Alexa and Siri, Amazon and Apple’s digital
voice assistants, are much more than a
convenient tool—they are very real
applications of artificial intelligence that is
increasingly integral to our daily life. They
both rely on natural language generation
and processing and machine learning,
forms of artificial intelligence, in order to
effectively operate and perform better
over time.
9. Need of Artificial
Intelligence
• There’s no doubt in the
fact that technology has
made our life better. From
music recommendations,
map directions, mobile
banking to fraud
prevention, AI and other
technologies have taken
over. There’s a fine line
between advancement and
destruction. There’s always
two sides to a coin, and that
is the case with AI as well.
12. Application of AI in
Gaming
• A majority of the video games —whether they’re
featuring racing-car games, shooting games, or
strategy games – they all have different
components that are powered by AI or related
applications.
• Physicist Willy Higinbotham created the first
video game in 1958.
• The main objective of utilizing AI in
gaming is to deliver a realistic gaming
experience for players to battle against
each other on a virtual platform.
13. Artificial Intelligence Advantages & Disadvantages
Disadvantages
• High Costs
• AI has no creativity
• Make Humans Lazy
• AI will grow uncontrollably, and eventually
wipe out humanity
Advantages
• Reduction in Human Error
• Digital assistants minimizes the need for
human resources.
• AI has helped in coming up with new
inventions.
• AI can provide accurate work with greater
responsibility
15. Future Scope of AI
• Looking at the features and its wide application
we may definitely stick to artificial intelligence.
Seeing at the development of AI is that is it that
the future world is becoming artificial.
• Biological intelligence is fixed, because it is an old,
mature paradigm but the new paradigm of non-
biological computation and intelligence is growing
exponentially.
• The Memory capacity of the human brain is
probably of the order often thousand million
binary digits.But most of this is probably used in
remembering visual impressions, and other
comparatively wasteful ways.
• Hence we can say that as natural intelligence is
limited and volatile too world may now depend
upon computers for smooth working.
16.
17. Conclusion :
Till now we have discussed in brief about Artificial Intelligence.
We have discussed some of its principles, its applications, its achievements etc.
The ultimate goal of institutions and scientists working of AI is to solve majority of the problems or to
achieve the tasks which we humans directly can’t accomplish.
It is for sure that development in this field of computer science will change the complete scenario of the
world. Now it is the responsibility of creamy layer of engineers to develop this field.