The document summarizes a presentation given by Prof. Dr. David Asirvatham on AI and future jobs. The presentation discusses how AI will impact various jobs and industries in the coming years and decades. It notes that many existing jobs will be automated or replaced by machines, but that AI will also create new types of jobs and work. The presentation emphasizes that acquiring new technological skills will be important for workers to adapt and ensure they are not left behind as AI disruption occurs. It concludes that AI will significantly change how people live and work, with humans needing to work together with machines.
Artificial intelligence (AI) currently being used by insurance companies has failed to remove gender bias from the profession’s claims, underwriting and marketing processes.
A Chartered Insurance Institute (CII) report tells insurers they must tackle these gender biases. The report found that the datasets used to train the algorithms which support AI systems are rooted in outdated gender concepts. Algorithms learn by being trained on historic data but the report notes more and more of that data is now unstructured, coming from text, audio, video and sensors.
Yet the report warns embedded in that historic data are decisions based upon historic biases, particularly around gender. The report concluded insurance firms need to prepare a structured response to this issue, starting with visible leadership on tackling gender bias in AI.
Digital Disruption, Artificial Intelligence and the Future of JobsAbraham Samuel
This presentation was given at the HR-Tech Conference in Dubai in May 2018. It discusses the impact of artificial intelligence on the future of jobs:
- Digital Transformation: Hype or reality
- The impact of AI and Robotics in the workspace
- What jobs are likely to get displaced
- Can we retool our competencies to stay relevant
- How can HR leverage Digital Transformation
It contains video content too and would, therefore, be best viewed by downloading it and watching it as a PowerPoint Presentation.
How artificial intelligence will change in 2050 venkat vajradhar - mediumvenkatvajradhar1
This article discusses how artificial intelligence may change and advance between now and 2050. It outlines how AI is already integrated into many aspects of daily life through voice assistants, online recommendations, and other applications. The article then explores how AI could potentially revolutionize industries like entertainment, medicine, cybersecurity, transportation, and care for elderly individuals by 2050 through more advanced machine learning, personalized healthcare, improved security systems, fully autonomous vehicles, and assistive technologies.
Still, consider The Terminator combined with The Matrix, also robotic process robotization must be the state when the bias rise to rule humankind with brutal power If device literacy seems like the origin of a grim dystopian fate. Fortunately, robotic process robotization (RPA) includes nothing except perhaps for the performance part. There aren’t indeed any robots included in this robotization software.
IRJET- Managing Social Complaint using Mobile Application with Real-time Trac...IRJET Journal
This document describes a mobile application that allows citizens to register social complaints with local government agencies in real-time. The app classifies complaints by department and uses GPS to pinpoint the exact location. All complaint data is stored securely in Google's Firebase database. The goal is to streamline the complaint registration process and make government response more efficient and transparent. Key features include user registration, complaint registration with photo upload, location tracking, and an admin module to monitor complaints. The architecture utilizes secure AES encryption, Android Studio for development, Google Maps API for locations, and Firebase for real-time cloud database storage and synchronization across devices.
Emerging technologies such as Artificial Intelligence, IIoT and Blockchain are threatening to take away millions of conventional jobs over the next three decades. They have the potential to create even more jobs for he future. But the structural changes in job markets would be painful and would vary from country to country. This presentation suggests a macro model for India to be ready to face the challenges.
The document describes an upcoming two-day workshop on how artificial intelligence is transforming business, hosted by the Confederation of Indian Industry and facilitated by DataMites. The workshop will take place on February 20-21, 2019 in Chennai, India and will be presented by AI expert Ashok Kumar Adinarayanan. The document provides an agenda and overview of topics that will be covered, including the evolution and history of AI, machine learning applications, case studies of AI transforming industries like banking and healthcare.
The document summarizes a presentation given by Prof. Dr. David Asirvatham on AI and future jobs. The presentation discusses how AI will impact various jobs and industries in the coming years and decades. It notes that many existing jobs will be automated or replaced by machines, but that AI will also create new types of jobs and work. The presentation emphasizes that acquiring new technological skills will be important for workers to adapt and ensure they are not left behind as AI disruption occurs. It concludes that AI will significantly change how people live and work, with humans needing to work together with machines.
Artificial intelligence (AI) currently being used by insurance companies has failed to remove gender bias from the profession’s claims, underwriting and marketing processes.
A Chartered Insurance Institute (CII) report tells insurers they must tackle these gender biases. The report found that the datasets used to train the algorithms which support AI systems are rooted in outdated gender concepts. Algorithms learn by being trained on historic data but the report notes more and more of that data is now unstructured, coming from text, audio, video and sensors.
Yet the report warns embedded in that historic data are decisions based upon historic biases, particularly around gender. The report concluded insurance firms need to prepare a structured response to this issue, starting with visible leadership on tackling gender bias in AI.
Digital Disruption, Artificial Intelligence and the Future of JobsAbraham Samuel
This presentation was given at the HR-Tech Conference in Dubai in May 2018. It discusses the impact of artificial intelligence on the future of jobs:
- Digital Transformation: Hype or reality
- The impact of AI and Robotics in the workspace
- What jobs are likely to get displaced
- Can we retool our competencies to stay relevant
- How can HR leverage Digital Transformation
It contains video content too and would, therefore, be best viewed by downloading it and watching it as a PowerPoint Presentation.
How artificial intelligence will change in 2050 venkat vajradhar - mediumvenkatvajradhar1
This article discusses how artificial intelligence may change and advance between now and 2050. It outlines how AI is already integrated into many aspects of daily life through voice assistants, online recommendations, and other applications. The article then explores how AI could potentially revolutionize industries like entertainment, medicine, cybersecurity, transportation, and care for elderly individuals by 2050 through more advanced machine learning, personalized healthcare, improved security systems, fully autonomous vehicles, and assistive technologies.
Still, consider The Terminator combined with The Matrix, also robotic process robotization must be the state when the bias rise to rule humankind with brutal power If device literacy seems like the origin of a grim dystopian fate. Fortunately, robotic process robotization (RPA) includes nothing except perhaps for the performance part. There aren’t indeed any robots included in this robotization software.
IRJET- Managing Social Complaint using Mobile Application with Real-time Trac...IRJET Journal
This document describes a mobile application that allows citizens to register social complaints with local government agencies in real-time. The app classifies complaints by department and uses GPS to pinpoint the exact location. All complaint data is stored securely in Google's Firebase database. The goal is to streamline the complaint registration process and make government response more efficient and transparent. Key features include user registration, complaint registration with photo upload, location tracking, and an admin module to monitor complaints. The architecture utilizes secure AES encryption, Android Studio for development, Google Maps API for locations, and Firebase for real-time cloud database storage and synchronization across devices.
Emerging technologies such as Artificial Intelligence, IIoT and Blockchain are threatening to take away millions of conventional jobs over the next three decades. They have the potential to create even more jobs for he future. But the structural changes in job markets would be painful and would vary from country to country. This presentation suggests a macro model for India to be ready to face the challenges.
The document describes an upcoming two-day workshop on how artificial intelligence is transforming business, hosted by the Confederation of Indian Industry and facilitated by DataMites. The workshop will take place on February 20-21, 2019 in Chennai, India and will be presented by AI expert Ashok Kumar Adinarayanan. The document provides an agenda and overview of topics that will be covered, including the evolution and history of AI, machine learning applications, case studies of AI transforming industries like banking and healthcare.
Driven by the rapid progress in Artificial Intelligence (AI) research, intelligent machines are gaining the ability to learn, improve and make calculated decisions in ways that will enable them to perform tasks previously thought to rely solely on human experience, creativity, and ingenuity. As a result, we will in the near future see large parts of our lives influenced by AI.
AI innovation will also be central to the achievement of the United Nations' Sustainable Development Goals (SDGs) and will help solving humanity's grand challenges by capitalizing on the unprecedented quantities of data now being generated on sentiment behavior, human health, commerce, communications, migration and more.
With large parts of our lives being influenced by AI, it is critical that government, industry, academia and civil society work together to evaluate the opportunities presented by AI, ensuring that AI benefits all of humanity. Responding to this critical issue, ITU and the XPRIZE Foundation organized AI for Good Global Summit in Geneva, 7-9 June, 2017 in partnership with a number of UN sister agencies. The Summit aimed to accelerate and advance the development and democratization of AI solutions that can address specific global challenges related to poverty, hunger, health, education, the environment, and others.
The Summit provided a neutral platform for government officials, UN agencies, NGO's, industry leaders, and AI experts to discuss the ethical, technical, societal and policy issues related to AI, offer reccommendations and guidance, and promote international dialogue and cooperation in support of AI innovation.
Please visit the AI for Good Global Summit page for more resources: https://www.itu.int/en/ITU-T/AI/Pages/201706-default.aspx
If you would like to speak, partner or sponsor the 2018 edition of the summit, please contact: ai@itu.int
The document discusses how artificial intelligence will impact the future of work. It notes that by 2030, Gartner predicts that 80% of today's project management tasks will be eliminated as AI takes over. It also lists the top 10 jobs that are likely to be adopted by companies using AI and other emerging technologies by 2022. The document emphasizes skills like analytical thinking, active learning, and emotional intelligence as important for the future of work as jobs change. It provides references to additional reports on AI, automation, and the future of jobs.
Impact of Artificial Intelligence in IT IndustryAnand SFJ
https://sfjbstraining.com/product/artificial-intelligence-course
Artificial Intelligence transforms traditional computer methods but also has an impact on various industries. Software which makes Artificial Intelligence relatively more important in this sector.
Artificial Intelligence (AI): Applications in agricultureadityak702
The document discusses the history and applications of artificial intelligence (AI) in agriculture. It defines AI as the theory and development of computer systems able to perform tasks normally requiring human intelligence. The timeline of AI highlights important developments from 1950 to present day. The document outlines different types of AI and discusses 20 applications of AI in agriculture, including decision support systems, precision agriculture, robotics, and use of sensors, machine learning and computer vision. It predicts that AI will have a large impact on agriculture by helping 70 million Indian farmers and adding $9 billion to farmer incomes by 2020.
The future of artificial intelligence in manufacturing industriesusmsystems
For large industries such as gaming, banking, retail, commerce, and government. AI is widely used and slow in the manufacturing sector, facilitating industrial automation. AI-powered machines show an easy path to the future by providing some benefits — providing new opportunities, increasing production capacity and bringing machine technology closer to human interaction.
The document discusses various applications and implications of artificial intelligence (AI). It describes how AI is being used in healthcare to help patients, in agriculture to improve crop yields more sustainably, and in banking for customer support and fraud detection. Autonomous vehicles are also discussed as an area being revolutionized by AI. The document outlines advantages like reduced human error but also disadvantages such as unemployment. It concludes that while AI promises many benefits, its development also raises concerns about risks that must be addressed.
The document discusses the business case for applied artificial intelligence. It covers how AI can enhance enterprises and how to build successful AI ventures. Specifically, it notes that global AI business value is forecast to reach $3.9 trillion by 2022. It then discusses how to introduce AI in enterprises, including defining objectives and benefits. It also outlines challenges of AI introduction. Additionally, it provides a framework for successful AI startups with factors around value creation, implementation, and competitive positioning. The document concludes by discussing implementation aspects like machine learning canvases and technical debts, as well as ethical considerations around issues like bias, privacy, and accountability.
5 Important Artificial Intelligence Predictions (For 2019) Everyone Should ReadBernard Marr
Artificial intelligence (AI), machine learning and deep learning have made huge strides in 2018. In this post we look at some of the key AI predictions for 2019, where is will be used, how it will make the biggest impact, as well as the key challenges we have to address.
Artificial intelligence (ai) will radically transform the way we do business in the future, and the way we live. That’s a strong statement, but i believe it’s true. Ai has many faces. As we are increasingly exposed to it, it’s important to understand what it can and can’t do and how companies can pivot wisely to this still evolving reality without overlooking the ethical, human and regulatory questions it raises.
The Impact of Robots and Automation on the Future of EmploymentNabeel Amanat
Summarizing the conference attended in Gulf Hotel, Bahrain on 14th and 15th of march 2018, organized by Polytechnic University Bahrain
Conclusion: The conclusion for this conference was to adapt to changes as per the change in the environment and enhancing innovated technology, software skills to your profile.
One example,
Dr. Ihsan Taie (Chief Technologist O&G Network Integrity R&D Division Saudi Aramco)
PHD in Chemicals but developed a department in Aramco related to IT where he hired individual with different specialization in IT field to create and develop robots to reduce risk and maintenance cost
Will robots take our jobs (short version) for Women Techmakers TalkAva Meredith
The document discusses how robots and AI will impact jobs. It finds that 7.1 million jobs will be lost by 2020 due to automation, but 2.1 million new jobs will be created, resulting in a net loss of over 5 million jobs. While demand for software developers is high, AI can automate coding and system administration tasks. Most industries will face skills disruptions. To prepare for the future of work, people will need math and soft skills, as well as skills in technical project management, AI programming, data science, and mobile and cloud development. Education systems will need to be rethought to encourage lifelong learning.
AI driven automation will create wealth and expand economies. Find out the views of the Executive Office of the US President in this AI Government led initiative.
Latest trends in information technologyAtifa Aqueel
This ppt includes the latest trends in information technology such as big data analytics, cloud computing, virtual reality, 5G wireless technology etc.
Big data disruptions in the world of AI and Autonomous vehicles at Global Big...Sudha Jamthe
Sudha Jamthe's keynote at The Global Big Data Conference, Snat Clara, CA about "Big Data Disruption from the world of AI and Autonomous Vehicles". Sudha maps Autonomous Vehicles (AV) cognition technologies on how it applies as AI technologies in other industries - Robotics, Industrial Cognitive Digital Twins, Healthcare, City IoT Infrastructure and Mobility Services.
AI and its applications are not going away and will cause a significant amount of change to everyday life over the next decade. Whilst there has been a lot of buzz in the past that has not been fulfilled, advances in skills, computing power and modelling and ensuring that the hype is finally being realised. To some extent, we don’t even know what AI is capable of yet which is both exciting and scary!
This document defines artificial intelligence and discusses its applications and impact on the future. It provides definitions of AI as the ability of computers to perform tasks commonly associated with human intelligence and simulate human problem solving. The document also discusses how AI will change various industries like entertainment, medicine, cybersecurity and transportation by 2050 through applications like personalized healthcare, autonomous vehicles, enhanced cybersecurity tools and customized virtual entertainment. It emphasizes the importance of AI in enabling computers to harness massive data to make optimal decisions and discoveries faster than humans.
The Amazing Ways Alibaba Uses Artificial Intelligence And Machine LearningBernard Marr
Alibaba is already one of China's most influential tech companies, but it is very focused on becoming China's artificial intelligence leader as well. From altering retail to developing smart cities and nearly every industry and application in between, Alibaba is helping China achieve its goal to become the dominant AI player in the world.
We interviewed thirty of today's top thinkers in artificial intelligence to get a glimpse of what's coming next - the direction technology and applications will take over the next ten years.
JyotPrakash Gugnani, Student of sem 2 from department of journalism and mass communication, JIMS Vasant Kunj II talk about Areas of Artificial Intelligence. Have a Look!! For more updates: visit: jimssouthdelhi.com
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
Driven by the rapid progress in Artificial Intelligence (AI) research, intelligent machines are gaining the ability to learn, improve and make calculated decisions in ways that will enable them to perform tasks previously thought to rely solely on human experience, creativity, and ingenuity. As a result, we will in the near future see large parts of our lives influenced by AI.
AI innovation will also be central to the achievement of the United Nations' Sustainable Development Goals (SDGs) and will help solving humanity's grand challenges by capitalizing on the unprecedented quantities of data now being generated on sentiment behavior, human health, commerce, communications, migration and more.
With large parts of our lives being influenced by AI, it is critical that government, industry, academia and civil society work together to evaluate the opportunities presented by AI, ensuring that AI benefits all of humanity. Responding to this critical issue, ITU and the XPRIZE Foundation organized AI for Good Global Summit in Geneva, 7-9 June, 2017 in partnership with a number of UN sister agencies. The Summit aimed to accelerate and advance the development and democratization of AI solutions that can address specific global challenges related to poverty, hunger, health, education, the environment, and others.
The Summit provided a neutral platform for government officials, UN agencies, NGO's, industry leaders, and AI experts to discuss the ethical, technical, societal and policy issues related to AI, offer reccommendations and guidance, and promote international dialogue and cooperation in support of AI innovation.
Please visit the AI for Good Global Summit page for more resources: https://www.itu.int/en/ITU-T/AI/Pages/201706-default.aspx
If you would like to speak, partner or sponsor the 2018 edition of the summit, please contact: ai@itu.int
The document discusses how artificial intelligence will impact the future of work. It notes that by 2030, Gartner predicts that 80% of today's project management tasks will be eliminated as AI takes over. It also lists the top 10 jobs that are likely to be adopted by companies using AI and other emerging technologies by 2022. The document emphasizes skills like analytical thinking, active learning, and emotional intelligence as important for the future of work as jobs change. It provides references to additional reports on AI, automation, and the future of jobs.
Impact of Artificial Intelligence in IT IndustryAnand SFJ
https://sfjbstraining.com/product/artificial-intelligence-course
Artificial Intelligence transforms traditional computer methods but also has an impact on various industries. Software which makes Artificial Intelligence relatively more important in this sector.
Artificial Intelligence (AI): Applications in agricultureadityak702
The document discusses the history and applications of artificial intelligence (AI) in agriculture. It defines AI as the theory and development of computer systems able to perform tasks normally requiring human intelligence. The timeline of AI highlights important developments from 1950 to present day. The document outlines different types of AI and discusses 20 applications of AI in agriculture, including decision support systems, precision agriculture, robotics, and use of sensors, machine learning and computer vision. It predicts that AI will have a large impact on agriculture by helping 70 million Indian farmers and adding $9 billion to farmer incomes by 2020.
The future of artificial intelligence in manufacturing industriesusmsystems
For large industries such as gaming, banking, retail, commerce, and government. AI is widely used and slow in the manufacturing sector, facilitating industrial automation. AI-powered machines show an easy path to the future by providing some benefits — providing new opportunities, increasing production capacity and bringing machine technology closer to human interaction.
The document discusses various applications and implications of artificial intelligence (AI). It describes how AI is being used in healthcare to help patients, in agriculture to improve crop yields more sustainably, and in banking for customer support and fraud detection. Autonomous vehicles are also discussed as an area being revolutionized by AI. The document outlines advantages like reduced human error but also disadvantages such as unemployment. It concludes that while AI promises many benefits, its development also raises concerns about risks that must be addressed.
The document discusses the business case for applied artificial intelligence. It covers how AI can enhance enterprises and how to build successful AI ventures. Specifically, it notes that global AI business value is forecast to reach $3.9 trillion by 2022. It then discusses how to introduce AI in enterprises, including defining objectives and benefits. It also outlines challenges of AI introduction. Additionally, it provides a framework for successful AI startups with factors around value creation, implementation, and competitive positioning. The document concludes by discussing implementation aspects like machine learning canvases and technical debts, as well as ethical considerations around issues like bias, privacy, and accountability.
5 Important Artificial Intelligence Predictions (For 2019) Everyone Should ReadBernard Marr
Artificial intelligence (AI), machine learning and deep learning have made huge strides in 2018. In this post we look at some of the key AI predictions for 2019, where is will be used, how it will make the biggest impact, as well as the key challenges we have to address.
Artificial intelligence (ai) will radically transform the way we do business in the future, and the way we live. That’s a strong statement, but i believe it’s true. Ai has many faces. As we are increasingly exposed to it, it’s important to understand what it can and can’t do and how companies can pivot wisely to this still evolving reality without overlooking the ethical, human and regulatory questions it raises.
The Impact of Robots and Automation on the Future of EmploymentNabeel Amanat
Summarizing the conference attended in Gulf Hotel, Bahrain on 14th and 15th of march 2018, organized by Polytechnic University Bahrain
Conclusion: The conclusion for this conference was to adapt to changes as per the change in the environment and enhancing innovated technology, software skills to your profile.
One example,
Dr. Ihsan Taie (Chief Technologist O&G Network Integrity R&D Division Saudi Aramco)
PHD in Chemicals but developed a department in Aramco related to IT where he hired individual with different specialization in IT field to create and develop robots to reduce risk and maintenance cost
Will robots take our jobs (short version) for Women Techmakers TalkAva Meredith
The document discusses how robots and AI will impact jobs. It finds that 7.1 million jobs will be lost by 2020 due to automation, but 2.1 million new jobs will be created, resulting in a net loss of over 5 million jobs. While demand for software developers is high, AI can automate coding and system administration tasks. Most industries will face skills disruptions. To prepare for the future of work, people will need math and soft skills, as well as skills in technical project management, AI programming, data science, and mobile and cloud development. Education systems will need to be rethought to encourage lifelong learning.
AI driven automation will create wealth and expand economies. Find out the views of the Executive Office of the US President in this AI Government led initiative.
Latest trends in information technologyAtifa Aqueel
This ppt includes the latest trends in information technology such as big data analytics, cloud computing, virtual reality, 5G wireless technology etc.
Big data disruptions in the world of AI and Autonomous vehicles at Global Big...Sudha Jamthe
Sudha Jamthe's keynote at The Global Big Data Conference, Snat Clara, CA about "Big Data Disruption from the world of AI and Autonomous Vehicles". Sudha maps Autonomous Vehicles (AV) cognition technologies on how it applies as AI technologies in other industries - Robotics, Industrial Cognitive Digital Twins, Healthcare, City IoT Infrastructure and Mobility Services.
AI and its applications are not going away and will cause a significant amount of change to everyday life over the next decade. Whilst there has been a lot of buzz in the past that has not been fulfilled, advances in skills, computing power and modelling and ensuring that the hype is finally being realised. To some extent, we don’t even know what AI is capable of yet which is both exciting and scary!
This document defines artificial intelligence and discusses its applications and impact on the future. It provides definitions of AI as the ability of computers to perform tasks commonly associated with human intelligence and simulate human problem solving. The document also discusses how AI will change various industries like entertainment, medicine, cybersecurity and transportation by 2050 through applications like personalized healthcare, autonomous vehicles, enhanced cybersecurity tools and customized virtual entertainment. It emphasizes the importance of AI in enabling computers to harness massive data to make optimal decisions and discoveries faster than humans.
The Amazing Ways Alibaba Uses Artificial Intelligence And Machine LearningBernard Marr
Alibaba is already one of China's most influential tech companies, but it is very focused on becoming China's artificial intelligence leader as well. From altering retail to developing smart cities and nearly every industry and application in between, Alibaba is helping China achieve its goal to become the dominant AI player in the world.
We interviewed thirty of today's top thinkers in artificial intelligence to get a glimpse of what's coming next - the direction technology and applications will take over the next ten years.
JyotPrakash Gugnani, Student of sem 2 from department of journalism and mass communication, JIMS Vasant Kunj II talk about Areas of Artificial Intelligence. Have a Look!! For more updates: visit: jimssouthdelhi.com
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
Introduction–Definition - Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.
Artificial intelligence is already used in many applications like web search, navigation, and computer vision. The document discusses the history of AI beginning in the 17th century with early philosophers exploring symbolic reasoning. A key event was the 1956 Dartmouth conference which helped found the field of AI research. The document outlines several branches of AI including neural networks, fuzzy logic, genetic programming, and ontology. It provides examples of current AI applications in fields like computer science, finance, transportation, telecommunications, and medicine.
This document provides an overview of agents and multi-agent systems. It discusses key trends in computer science like ubiquity, intelligence, delegation, and human-orientation that have led to the emergence of multi-agent systems. The document outlines challenges in agent technology like developing reasoning capabilities for agents and ensuring user confidence and trust. It also discusses objections to multi-agent systems regarding whether it is just distributed systems or artificial intelligence.
The advent of artificial super intelligence and its impactsFernando Alcoforado
Artificial Super Intelligence will be the first technology to potentially surpass humans in all dimensions. Until now, human beings have had a monopoly on decision-making and therefore have control over everything. With Artificial Super Intelligence, this can end. A wide range of consequences can occur, including extremely good consequences and consequences as bad as the extinction of the human species.
Introduction to agents and multi-agent systemsAntonio Moreno
Multi-agent systems course at University Rovira i Virgili. Slides mostly based on those of Rosenschein, from the content of the book by Wooldridge.
Lecture 1-Introduction to agents and multi-agent systems.
Artificial intelligence uses in productive systems and impacts on the world...Fernando Alcoforado
This essay aims to present the scientific and technological advances of artificial intelligence, their uses in productive systems and their impacts in the world of work.
This second machine age has seen the rise of artificial intelligence (AI), or “intelligence” that is not the result of
human cogitation. It is now ubiquitous in many commercial products, from search engines to virtual assistants. aI is the result of exponential growth in computing power, memory capacity, cloud computing, distributed and parallel processing, open-source solutions, and global connectivity of both people
and machines. The massive amounts and the speed at which structured and unstructured (e.g., text, audio, video, sensor) data is being generated has made a necessity of speedily processing and generating meaningful, actionable insights from it.
ARTIFICIAL INTELLIGENCE, COGNITIVE TECHNOLOGIES AND DIGITAL LABOREmmanuel Gillain
bring a simple and concise summary of what the cognitive technologies enabling “Digital Labor” mean in order to raise the awareness level amongst the non technical people that care about the technology impacts on business, economy and society.
This step-by-step guide will show you how to build and use an AI app. Whether you are a researcher, business owner or just curious about AI technology, these instructions will help you navigate the steps of creating an AI system that can transform your industry.
Artificial intelligence (AI) is a field of computer science that focuses on solving cognitive programs associated with human intelligence, such as pattern recognition, problem-solving and learning. AI refers to the use of advanced technology, such as robotics, in futuristic scenarios.
Top And Best Digital Marketing Agency With AIamdigitalmark15
Elevate your brand with Digitalaanmo, the top agency for the best and affordable digital marketing services. Unleash success with our expert agency solutions
From Code to Cognition_ Understanding the Human Element in Machine Learning.pdfTyrion Lannister
we navigate this evolving landscape, understanding and appreciating the symbiotic relationship between humans and machines will be crucial in harnessing the true potential of artificial intelligence.
This document provides an overview of artificial intelligence (AI) including definitions, a brief history, advantages, and applications. It defines AI as making machines intelligent and able to perform tasks like humans. The document also discusses robotics as a domain of AI focused on creating intelligent robots. Key applications mentioned include gaming, natural language processing, expert systems, vision systems, speech recognition, and intelligent robots.
Comparison Between Artificial Intelligence, Machine Learning, and Deep LearningZaranTech LLC
Artificial intelligence is a branch of computer science dealing with intelligent behavior in machines. Machine learning is a subset of AI that uses statistical techniques to perform tasks without explicit programming. Deep learning is a subset of machine learning that uses artificial neural networks with many layers to learn representations of data.
The power and potential of artificial intelligence cannot be overstated. It has transformed how we interact with technology, from introducing us to robots that can perform tasks with precision to bringing us to the brink of an era of self-driving vehicles and rockets. And this is just the beginning. With a staggering 270% growth in business adoption in the past four years, it has been clear that AI is not just a tool for solving mathematical problems but a transformative force that will shape the future of our society and economy.
Artificial Intelligence (AI) has become an increasingly common presence in our lives, from robots that can perform tasks with precision to autonomous cars that are changing how we travel. It has become an essential part of everything, from large-scale manufacturing units to the small screens of our smartwatches. Today, companies of all sizes and industries are turning to AI to improve customer satisfaction and boost sales. AI is the next big thing, making its way into the inner workings of Fortune 500 companies to help them automate their business processes. Investing in AI can be beneficial for businesses looking to stay competitive in a fast-paced business world.
leewayhertz.com-How to build an AI app.pdfrobertsamuel23
The power and potential of artificial intelligence cannot be overstated. It has transformed
how we interact with technology, from introducing us to robots that can perform tasks
with precision to bringing us to the brink of an era of self-driving vehicles and rockets
IRJET-Artificial Intelligence and its Applications GoalIRJET Journal
This document discusses artificial intelligence (AI) and its applications. It begins by defining AI as making machines capable of performing intelligent tasks like humans. It then discusses three areas of simulated AI: machine learning systems, machine intelligence systems, and machine consciousness systems. The document outlines various applications of AI in fields like finance, manufacturing, healthcare, transportation, and weather forecasting. It concludes by stating that AI will continue playing an important role in science and technology, but whether AI can achieve human-level consciousness is still unknown and depends on further research.
Similar to Artificial intelligence implementation challenges in embedded design (20)
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Artificial intelligence implementation challenges in embedded design
1. Technical Insights - Embedded
Artificial Intelligence Implementation Challenges in Embedded Systems
The real programming work begins especially in the case of artificial intelligence, problems can lead to a
kind of combinatorial explosion of issues unless there is incredible focus on the task at hand.
An unfortunate consequence can be pressure to produce a tightly bounded, domain specific solution so
as to make good on promised dates and give investors a warm and fuzzy feeling that they’ve picked a
good pony. Product schedules, which all business naturally use as a guidepost, is a critical yardstick to
measure successful execution but sometimes problematic when the solution, like real artificial
intelligence, requires so much different thinking, creativity and has proven so elusive for so many
decades for so many.
Someone creatively designing and developing off in the quiet contemplative corner of their garage,
without the pressure of paying back investors before the next quarter, has as good of a chance as anyone
these days given the ubiquity of low cost primary and secondary storage and incredibly fast
microcontrollers that cost less than a cheeseburger.
The following are the Challenging functionalities in Artificial Intelligence Implementation
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2. Technical Insights - Embedded
Interpreting the environment’s state
The technologies for this task involve analyzing various sensing inputs.
Speech /Voice:
Humans most often interact through written or spoken language. So, it’s clear that they will also expect
this kind of interaction with artificial intelligence environments. Speech recognition and natural language
processing are different and complementary problems, using different techniques.
Speech recognition obtains an electric signal from a microphone. The first step is identifying phone
message in this signal, which involves signal processing and pattern recognition. The next step is joining
phone message and identifying words. Several speech recognition systems are available and are more or
less successful, depending on how the user speaks.
Natural language input is a written sequence, resulting from a speech recognition system or obtained
from a keyboard or even a written document. Natural language processing aims to understand this input.
The first step is syntax analysis, followed by semantic analysis. Knowledge representation plays an
important role. Automatic-translation systems are one of the most studied areas using statistical and
knowledge-based approaches.
Imaging / Vision:
Vision is humans’ richest sensorial input. So, the ability to automate vision is important. Basically,
computer vision is a geometric reasoning problem. Computer vision comprises many areas, such as image
acquisition, image processing, object recognition (2D and 3D), scene analysis, and image-flow analysis.
Computer vision can be used in different situations in artificial intelligence. For example, intelligent
transportation systems can use it to identify traffic problems, traffic patterns, or approaching vehicles.
Computer vision can also identify either human gestures to control equipment or human facial
expressions to identify emotional states.
The processing of data acquired by many other sensorial sources (for example, raw sensors, RFID, and
GPS) can also benefit from artificial intelligence techniques.
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3. Technical Insights - Embedded
Representing the information and knowledge associated with the environment
Artificial Intelligence environments involve real-world problems, which are characterized by incompleteness and uncertainty.
Generally might be correct, some part might be incorrect, and some part might be missing. The question
is how to proceed with an elaborated reasoning process dealing with these information problems. To
handle this situation, researchers have used many techniques, such as Bayesian networks, fuzzy logic,
and rough sets. Generally, we deal with information; some part of it
Knowledge representation:
Knowledge representation is one of the most important areas in artificial intelligence. Expert systems
have achieved tremendous success in areas such as medicine, industry, and business. During the last
decade with the strong development of the Internet and the birth of the Web, humans faced a critical
problem. The amount of information became huge, and the mapping between information and
knowledge became urgent.
The Artificial Intelligence community started paying attention to information retrieval, text mining,
ontology’s, and the Semantic Web. Early experience in intelligent systems development shows us that
intelligence isn’t possible without knowledge; this is also true for artificial intelligence.
Modeling, simulating, and representing entities in the environment:
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4. Technical Insights - Embedded
People expect agents to support features such as sensing capabilities, autonomy, reactive and proactive
reasoning, social abilities, and learning. Multi agent systems emphasize social abilities, such as
communication, co- operation, conflict resolution, negotiation, augmentation, and emotion. Multi agent
systems rapidly became the main paradigm in artificial intelligence. After the Web boom, agents received
even more attention.
Multi agent systems are especially good at modeling real-world and social systems, where problems can
be solved in a concurrent and cooperative way without needing optimal solutions (for example, in traffic
or manufacturing).
In Artificial Intelligence environments, agents are a good way to model, simulate, and represent
meaningful entities such as rooms, cars, or even persons.
Planning decisions or actions:
Planning assists problem solving by producing a plan of action to achieve a particular goal. Artificial
Intelligence planning deals with all the aspects of general planning. Plans can be established before they
execute (offline) or while they execute (online).
They can be deliberative (planning and executing what was planned without considering unexpected
events), reactive (reacting to stimulus in a much more basic way), or hybrid (combining the best of
deliberative and re- active policies).
Planning is particularly linked with intelligence. Convincing someone that a system is intelligent is difficult
if that system can’t plan how to solve problems. Consequently, Artificial Intelligence environments must
support planning to give intelligent advice to users. A clear example is in intelligent transportation
systems—both inside vehicles, where intelligent driving systems will help drivers, and on the road, where
route planning will consider constraints related to traffic, time, and cost.
Most often, planning is associated with some kind of optimization. Here, combining artificial intelligence
and operations research makes sense. Some computational-intelligence and bio-inspired methods such
as genetic algorithms, ant colonies, particle swarm intelligence, taboo search, and simulated annealing
are useful.
Learning about the environment and associated aspects:
Machine learning has received attention from the artificial intelligence community from the beginning.
Since the ’70s, neural networks have had great success, being applied in many real-world problems such
as classification techniques that use more high-level descriptions. For example, inductive learning, casebased reasoning, and decision-tree-based methods have also seen success.
During the ’80s, the term “data mining” started appearing. Many database researchers have used this
term to refer to machine learning techniques (together with some statistics methods such as k-means)
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5. Technical Insights - Embedded
employed in knowledge discovery. Data mining constitutes one phase of knowledge discovery (selection,
cleaning, and preprocessing are phases before data mining, while interpretation and evaluation come
after data mining).
Nowadays, machine learning is widely used, so artificial intelligence will likely also need to handle this
technology. One requirement for artificial intelligence is to learn by observing users. Several systems
understand user commands, but they’re not intelligent enough to avoid doing things that the user
doesn’t want. Basic machine learning methods will enable artificial intelligence systems to learn by
observing users, thus making these systems more acceptable to them
Interacting with humans:
Artificial Intelligence systems should be able to interact intelligently with humans. Such interaction
requires context awareness. In Artificial Intelligence systems, context awareness will involve such factors
as mixed-initiative interfaces, adapting to users and situations, learning by observing users, consciousness
of the current situation, and scalable intelligence. Interaction through natural language and gestures –
Kindly refer Smart camera Image.
Because artificial intelligence systems deal with humans, they will need to consider all pertinent social
and emotional factors. For example, a person might not be interested in watching his or her favorite TV
program, a soccer game, because friends who don’t like soccer are visiting (a social aspect) or because he
or she is in a bad mood (an emotional aspect). Current artificial intelligence research on affective
computing and social computing is important for incorporating such capabilities into artificial intelligence
systems.
Acting on the environment:
The automated embedded devices such as robots could perform actions. Cognitive-robotics research can
provide benefits for artificial intelligence environments such as smart homes. This is especially true when
persons live alone, are elderly, or have health problems. The creation of intelligent robots that can
perform several tasks or just act as companions is important. However, in the current state of the art, we
can create robots that operate well only for specific tasks. Creating robots with the flexibility to do
different tasks, as humans can do, is too complex. This limitation is due primarily to physical constraints.
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