The document discusses the history, goals, current status, and future of artificial intelligence. It defines AI as making computers think intelligently like humans by studying the human brain. The goals of AI are to create expert systems that exhibit intelligent behavior and implement human intelligence in machines. The history of AI includes early foundations in the 1940s and milestones like Deep Blue beating Kasparov in 1997. Current AI is demonstrated in technologies like mobile assistants, robots, and self-driving cars. The future of AI is expected to include more human-level speech recognition and practical applications that digitally recreate human intelligence.
Artificial intelligence (AI) is an area of computer science focused on creating intelligent machines that can perform tasks like humans. The field was born in 1956 at a workshop where Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky, and Arthur Samuel became the founders of AI research. They and their students produced early programs that could learn checkers strategies, solve word problems in algebra, prove logical theorems, and speak English. By the 1960s, AI research was heavily funded by the Department of Defense and laboratories were established worldwide.
This document provides an overview of artificial intelligence. It begins with definitions of AI and examples like self-driving cars. It then discusses the early history, including Turing's 1950 paper asking if machines can think and McCarthy's coining of the term "artificial intelligence" in 1956. Current applications of AI are reviewed like mobile phones, games, navigation and robotics. The document also notes Google's role and promises to cover advantages, disadvantages and future scope of AI.
This document provides an overview of artificial intelligence (AI). It defines AI as the study of computer systems that attempt to model human intelligence. The document outlines the early history of AI beginning in 1950 with Alan Turing's paper on machine intelligence. It describes the current status of AI in applications such as mobile phones, video games, GPS, and robotics. Challenges for AI are discussed as well as the future potential in areas like self-driving cars and medical care. Both pros and cons of AI are presented before the document concludes with a definition of AI as the study and design of intelligent agents.
This document discusses artificial intelligence and machine learning in Africa. It provides a brief history of AI from Greek mythology to modern times. Key figures discussed include Charles Babbage, Ada Lovelace, Alan Turing, and researchers at the 1956 Dartmouth Conference. The document defines what AI is and is not, and classifies AI types. It also discusses machine learning, big data, data mining, and deep learning. It notes that bridging the gap between African and Western tech students requires interview skills, competitions, progressive work experience, impact knowledge, university education, and being timely with knowledge.
Artificial intelligence (AI) is an area of computer science that emphasizes creating intelligent machines that work like humans. AI involves programming computers for traits like perception, learning, planning, problem solving and knowledge. While initially developed in 1956, AI has grown in demand due to big data. AI can be categorized into weak AI, which is designed for specific tasks, and strong AI, which aims for general intelligence. AI has many applications in fields like law, education, business, finance, healthcare and manufacturing. It provides advantages such as increasing work efficiency and reducing costs and errors, but also faces disadvantages like potential misuse if not properly programmed. The future of AI is focused on developing smarter systems through advances in machine learning and deep learning.
Will robots take our jobs? A report from the World Economic Forum found that while 7.1 million jobs may be lost due to automation, 2.1 million new jobs will be created, resulting in a net loss of over 5 million jobs by 2020 across major economies. The drivers of increased robotization include technological advances in areas like machine learning, 3D printing, and quantum computing, as well as the increased productivity, lower costs, and improved safety that robots provide compared to human workers. Nearly every industry like transportation, farming, healthcare, and IT will be impacted. Proposed solutions include retraining workers, incentivizing lifelong learning, and political actions like a universal basic income.
The document discusses the history, goals, current status, and future of artificial intelligence. It defines AI as making computers think intelligently like humans by studying the human brain. The goals of AI are to create expert systems that exhibit intelligent behavior and implement human intelligence in machines. The history of AI includes early foundations in the 1940s and milestones like Deep Blue beating Kasparov in 1997. Current AI is demonstrated in technologies like mobile assistants, robots, and self-driving cars. The future of AI is expected to include more human-level speech recognition and practical applications that digitally recreate human intelligence.
Artificial intelligence (AI) is an area of computer science focused on creating intelligent machines that can perform tasks like humans. The field was born in 1956 at a workshop where Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky, and Arthur Samuel became the founders of AI research. They and their students produced early programs that could learn checkers strategies, solve word problems in algebra, prove logical theorems, and speak English. By the 1960s, AI research was heavily funded by the Department of Defense and laboratories were established worldwide.
This document provides an overview of artificial intelligence. It begins with definitions of AI and examples like self-driving cars. It then discusses the early history, including Turing's 1950 paper asking if machines can think and McCarthy's coining of the term "artificial intelligence" in 1956. Current applications of AI are reviewed like mobile phones, games, navigation and robotics. The document also notes Google's role and promises to cover advantages, disadvantages and future scope of AI.
This document provides an overview of artificial intelligence (AI). It defines AI as the study of computer systems that attempt to model human intelligence. The document outlines the early history of AI beginning in 1950 with Alan Turing's paper on machine intelligence. It describes the current status of AI in applications such as mobile phones, video games, GPS, and robotics. Challenges for AI are discussed as well as the future potential in areas like self-driving cars and medical care. Both pros and cons of AI are presented before the document concludes with a definition of AI as the study and design of intelligent agents.
This document discusses artificial intelligence and machine learning in Africa. It provides a brief history of AI from Greek mythology to modern times. Key figures discussed include Charles Babbage, Ada Lovelace, Alan Turing, and researchers at the 1956 Dartmouth Conference. The document defines what AI is and is not, and classifies AI types. It also discusses machine learning, big data, data mining, and deep learning. It notes that bridging the gap between African and Western tech students requires interview skills, competitions, progressive work experience, impact knowledge, university education, and being timely with knowledge.
Artificial intelligence (AI) is an area of computer science that emphasizes creating intelligent machines that work like humans. AI involves programming computers for traits like perception, learning, planning, problem solving and knowledge. While initially developed in 1956, AI has grown in demand due to big data. AI can be categorized into weak AI, which is designed for specific tasks, and strong AI, which aims for general intelligence. AI has many applications in fields like law, education, business, finance, healthcare and manufacturing. It provides advantages such as increasing work efficiency and reducing costs and errors, but also faces disadvantages like potential misuse if not properly programmed. The future of AI is focused on developing smarter systems through advances in machine learning and deep learning.
Will robots take our jobs? A report from the World Economic Forum found that while 7.1 million jobs may be lost due to automation, 2.1 million new jobs will be created, resulting in a net loss of over 5 million jobs by 2020 across major economies. The drivers of increased robotization include technological advances in areas like machine learning, 3D printing, and quantum computing, as well as the increased productivity, lower costs, and improved safety that robots provide compared to human workers. Nearly every industry like transportation, farming, healthcare, and IT will be impacted. Proposed solutions include retraining workers, incentivizing lifelong learning, and political actions like a universal basic income.
Artificial intelligence (AI) is the intelligence exhibited by machines and the branch of computer science which develops it. Alan Turing conceptualized AI with the Turing Test to evaluate a machine's ability to exhibit intelligent behavior equivalent to a human. John McCarthy is considered the father of AI. While machines are now capable of performing many tasks that humans can do, they lack human qualities like creativity, common sense, and emotional intelligence. AI provides benefits like precision, ability to do repetitive tasks, and reducing risks, but also has disadvantages like costs, lack of human touch, potential job losses, and possibility of being misused. AI is applied in fields such as robotics, banking, medical diagnosis, defense technologies, and space exploration.
Artificial intelligence (AI) is the field of computer science focusing on creating intelligent machines. Researchers are developing systems that can understand speech, beat humans at chess, and perform other intelligent tasks. The term was first coined in 1956, and since then AI has made advances in areas like machine learning, natural language processing, and robotics. However, fully human-level AI remains an ongoing challenge. Researchers take different approaches, such as attempting to replicate the human brain through neural networks or developing intelligent programs through symbolic reasoning. AI is used today for applications like logistics, data mining, and medical diagnosis.
It is a slide on artificial intilligence.You have to describe these point. This slide can use also student of CSE,EEE and othe engennering subjects.This presentation is a group presentation if anyone want to make it individually then he or she has to reduce the number of slides.By using this silde on can be talk at least 10 minute at presentation time
Overview of artificial intelligence, its definition and classification, its history and historical development, as well as several theories and concepts.
Artificial Intelligence (AI) is defined as the study of computer systems that attempt to model human intelligence. The document traces the early history of AI from Alan Turing's 1950 paper asking if machines can think to John McCarthy convening a workshop in 1955 that helped establish the field. Currently, AI is used in many applications including mobile devices, video games, GPS, robotics, and deep learning algorithms used by Google. The future of AI is promising with potential applications in self-driving cars, improved healthcare through medical diagnosis and treatment, and space exploration.
This document provides an introduction to artificial intelligence, including definitions, a brief history, advantages, disadvantages, applications, and examples of AI robots. It notes that AI was born from a workshop in 1956 led by researchers including John McCarthy and Marvin Minsky. Some key advantages discussed are fast decision making using AI and using robots instead of humans in dangerous situations. Disadvantages include needing regular updates and an inability to feel human emotions. Applications mentioned include healthcare, automotive, government, video games, and military. The document concludes that AI will be very important to daily life and that in 2025 ISRO plans to send the first robot into space.
Artificial Intelligence - Forwarded by Jeff CampauJeff Campau
This document defines artificial intelligence and discusses its history and current applications. It begins with definitions of AI and discusses early pioneers like Alan Turing and John McCarthy. Currently, AI is used in digital assistants like Siri, intelligent games, robotics, and other applications. The document also covers challenges for AI like computing power and intuitive thinking. It predicts future advances in self-driving cars, medical care, and space exploration. Both pros and cons of AI are provided such as precision and costs/unemployment. The conclusion restates that AI aims to create machine intelligence.
The document discusses artificial intelligence (AI) and provides examples of current AI applications. It defines AI as the development of computer systems that can perform tasks requiring human intelligence, such as visual perception and language translation. Examples of current AI include self-driving cars, robotics, navigation systems, and chatbots. Weak AI is designed for specific tasks while strong AI would think and act like humans, but no systems have achieved strong AI yet. The document also discusses machine learning, the Turing test for measuring intelligence, and potential future applications of AI in fields like the military, law, business, healthcare, and more.
On March 26, 2015 Steve Omohundro gave a talk in the IBM Research 2015 Distinguished Speaker Series at the Accelerated Discovery Lab, IBM Research, Almaden.
Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating “arms races” in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial “rational drives” of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the “Safe-AI Scaffolding Strategy” for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by the laws of physics, mathematical proof, and cryptographic complexity. “Smart contracts” are a promising decentralized cryptographic technology used in Ethereum and other second-generation cryptocurrencies. They can express economic, legal, and political rules and will be a key component in governing autonomous technologies. If we are able to meet the challenges, AI and robotics have the potential to dramatically improve every aspect of human life.
Machine learning is the important to each world .machine learning decide our future these slides contain introduction of machine learning and application advantage and disadvantages,how machine as computer
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.[1][2]:2 Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.
Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning.[3][4] In its application across business problems, machine learning is also referred to as predictive analytics.
Humanity will change more in the next 20 years than in the previous 300 years. What if …robots replaced the world’s workforce?
This is the presentation delivered by Glen Leonhard at London Business School's 2015 Global Leadership Summit.
Artificial intelligence will change workplaces as AI systems can perform jobs more efficiently by taking over labor-intensive and routine tasks. While AI may create new jobs and economic growth, it also presents challenges like ensuring an ethical development of AI and retraining workers for new roles. There are concerns that AI could surpass human intelligence or lose control and harm humanity if not developed properly. The document discusses both the pros and cons of increasing AI capabilities in the workplace.
This document discusses emerging technologies and their impact on student futures and jobs. It explores how technology is changing living, learning and working in the 21st century. The author envisions a future where students learn skills like coding, engineering, and arts through programs that blend subjects and expose them to innovation models. They provide examples of schools cultivating innovators through interdisciplinary STEM+arts programs and competitions that inspire passion for science, technology and problem solving.
The document discusses the history and forecast of artificial intelligence. It describes 3 waves of AI development since 1957, with the current wave focused on deep learning, chatbots, and robots. The document forecasts that AI may become intelligent assistants to humans, and discusses challenges around jobs, sustainability, education and more. Impacts of AI like autonomous weapons are also addressed. The document advocates balancing commercial and peaceful applications of AI technologies going forward.
1) Machines are increasingly impacting daily human routines through technologies like smart home devices and driverless cars.
2) Both humans and machines process information through pattern recognition, but humans excel at piecing together incomplete information in new ways while machines rely more on analyzing large datasets.
3) Early attempts by companies to use only data analysis or only human judgment in developing TV shows met with varying levels of success, showing the value of combining the two approaches.
Robotics is a branch of technology that deals with the design, construction, operation, and application of robots and computer systems to control them. Robots can take the place of humans in hazardous or manufacturing processes, or resemble humans. The word "robot" comes from the Slavic word for forced labor and was introduced in a 1921 play. Components of a robot include a power source, actuators like electric motors or muscle wire, and sensors for feedback. Artificial intelligence aims to create machine intelligence by designing intelligent agents that perceive their environment and take actions to maximize success. Some problems in AI include replicating specific human traits or capabilities in machines. Philosophy questions whether machines can truly be intelligent or have a mind like humans.
Machine Learning - Where to Next?, May 2015Peter Morgan
This document provides an overview of machine learning and artificial intelligence presented by Peter Morgan at the BrightTALK Machine Learning and Data Science Summit on May 21, 2015. The summary covers the speaker's background working in AI and machine learning, a definition and history of machine learning, current and potential applications of machine learning across many industries, prominent companies and researchers in the field, opportunities and threats of advanced AI, and predictions for the future of the technology.
This technical seminar covers behavior-based robotics and its applications. It begins with definitions of robots, robotics, and behavior-based robotics. It describes how behavior is expressed through stimulus-response diagrams and finite state machines. Behavior-based architectures like subsumption architecture and motor schemas are explained. The history of robotics is reviewed from mechanical robots to present-day humanoids. Applications include entertainment, exploration, medical assistants, transportation, and more. Key issues discussed are grounding in reality, situatedness, embodiment, emergent behavior, and scalability.
Human Robot Interaction (HRI) in Next Generation LearningFarzad Sabetzadeh
The presence of robots in our everyday activities is inevitable in the near future and this should not be met with skepticism but instead, with a practical outlook on how we can best interact with them. From homes to workplaces and cities, we are attempting to make our lives to be more productive, more efficient and so-called "Smarter". The building block of this "Smart" journey lies on how we will educate the next generation of our human workforce to interact and collaborate with robots. The first wave of modernization in human-machine interaction took us from punch cards to keyboards and mouse. The second wave took us to touchscreens and smart devices. This talk will explore the next generation learning and how to prepare and educate ourselves and our next generation for the time, when human-robot interaction (HRI) becomes an essential part of our day to day lives.
Based on Capabilities
B. Based on Functionality
1. Reactive Machines:
- Reactive machines are the simplest form of AI. They perceive their environment and
respond in a predetermined manner to achieve a specific goal.
- Examples include thermostats, industrial robots, and vacuum cleaners.
2. Limited Memory:
- These systems can remember past experiences and use that information to guide future
actions.
- Examples include chess playing programs and self-driving cars.
3. Theory of Mind:
- These systems can model other agents and take their beliefs, intentions, and desires into
account.
- Examples include personal assistants like Siri that understand context.
4. Self
The document discusses the history of artificial intelligence from its origins in the 1940s to modern applications. It describes several key early developments, including the first artificial neuron model (1943), the proposal of the Turing Test (1950), and the coining of the term "artificial intelligence" at the Dartmouth Conference (1956). The document also notes periods of growth and funding declines ("AI winters") for the field throughout its development. Overall, the history shows steady progress in AI from its theoretical beginnings to impactful applications today.
Artificial intelligence (AI) is the intelligence exhibited by machines and the branch of computer science which develops it. Alan Turing conceptualized AI with the Turing Test to evaluate a machine's ability to exhibit intelligent behavior equivalent to a human. John McCarthy is considered the father of AI. While machines are now capable of performing many tasks that humans can do, they lack human qualities like creativity, common sense, and emotional intelligence. AI provides benefits like precision, ability to do repetitive tasks, and reducing risks, but also has disadvantages like costs, lack of human touch, potential job losses, and possibility of being misused. AI is applied in fields such as robotics, banking, medical diagnosis, defense technologies, and space exploration.
Artificial intelligence (AI) is the field of computer science focusing on creating intelligent machines. Researchers are developing systems that can understand speech, beat humans at chess, and perform other intelligent tasks. The term was first coined in 1956, and since then AI has made advances in areas like machine learning, natural language processing, and robotics. However, fully human-level AI remains an ongoing challenge. Researchers take different approaches, such as attempting to replicate the human brain through neural networks or developing intelligent programs through symbolic reasoning. AI is used today for applications like logistics, data mining, and medical diagnosis.
It is a slide on artificial intilligence.You have to describe these point. This slide can use also student of CSE,EEE and othe engennering subjects.This presentation is a group presentation if anyone want to make it individually then he or she has to reduce the number of slides.By using this silde on can be talk at least 10 minute at presentation time
Overview of artificial intelligence, its definition and classification, its history and historical development, as well as several theories and concepts.
Artificial Intelligence (AI) is defined as the study of computer systems that attempt to model human intelligence. The document traces the early history of AI from Alan Turing's 1950 paper asking if machines can think to John McCarthy convening a workshop in 1955 that helped establish the field. Currently, AI is used in many applications including mobile devices, video games, GPS, robotics, and deep learning algorithms used by Google. The future of AI is promising with potential applications in self-driving cars, improved healthcare through medical diagnosis and treatment, and space exploration.
This document provides an introduction to artificial intelligence, including definitions, a brief history, advantages, disadvantages, applications, and examples of AI robots. It notes that AI was born from a workshop in 1956 led by researchers including John McCarthy and Marvin Minsky. Some key advantages discussed are fast decision making using AI and using robots instead of humans in dangerous situations. Disadvantages include needing regular updates and an inability to feel human emotions. Applications mentioned include healthcare, automotive, government, video games, and military. The document concludes that AI will be very important to daily life and that in 2025 ISRO plans to send the first robot into space.
Artificial Intelligence - Forwarded by Jeff CampauJeff Campau
This document defines artificial intelligence and discusses its history and current applications. It begins with definitions of AI and discusses early pioneers like Alan Turing and John McCarthy. Currently, AI is used in digital assistants like Siri, intelligent games, robotics, and other applications. The document also covers challenges for AI like computing power and intuitive thinking. It predicts future advances in self-driving cars, medical care, and space exploration. Both pros and cons of AI are provided such as precision and costs/unemployment. The conclusion restates that AI aims to create machine intelligence.
The document discusses artificial intelligence (AI) and provides examples of current AI applications. It defines AI as the development of computer systems that can perform tasks requiring human intelligence, such as visual perception and language translation. Examples of current AI include self-driving cars, robotics, navigation systems, and chatbots. Weak AI is designed for specific tasks while strong AI would think and act like humans, but no systems have achieved strong AI yet. The document also discusses machine learning, the Turing test for measuring intelligence, and potential future applications of AI in fields like the military, law, business, healthcare, and more.
On March 26, 2015 Steve Omohundro gave a talk in the IBM Research 2015 Distinguished Speaker Series at the Accelerated Discovery Lab, IBM Research, Almaden.
Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating “arms races” in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial “rational drives” of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the “Safe-AI Scaffolding Strategy” for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by the laws of physics, mathematical proof, and cryptographic complexity. “Smart contracts” are a promising decentralized cryptographic technology used in Ethereum and other second-generation cryptocurrencies. They can express economic, legal, and political rules and will be a key component in governing autonomous technologies. If we are able to meet the challenges, AI and robotics have the potential to dramatically improve every aspect of human life.
Machine learning is the important to each world .machine learning decide our future these slides contain introduction of machine learning and application advantage and disadvantages,how machine as computer
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.[1][2]:2 Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.
Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning.[3][4] In its application across business problems, machine learning is also referred to as predictive analytics.
Humanity will change more in the next 20 years than in the previous 300 years. What if …robots replaced the world’s workforce?
This is the presentation delivered by Glen Leonhard at London Business School's 2015 Global Leadership Summit.
Artificial intelligence will change workplaces as AI systems can perform jobs more efficiently by taking over labor-intensive and routine tasks. While AI may create new jobs and economic growth, it also presents challenges like ensuring an ethical development of AI and retraining workers for new roles. There are concerns that AI could surpass human intelligence or lose control and harm humanity if not developed properly. The document discusses both the pros and cons of increasing AI capabilities in the workplace.
This document discusses emerging technologies and their impact on student futures and jobs. It explores how technology is changing living, learning and working in the 21st century. The author envisions a future where students learn skills like coding, engineering, and arts through programs that blend subjects and expose them to innovation models. They provide examples of schools cultivating innovators through interdisciplinary STEM+arts programs and competitions that inspire passion for science, technology and problem solving.
The document discusses the history and forecast of artificial intelligence. It describes 3 waves of AI development since 1957, with the current wave focused on deep learning, chatbots, and robots. The document forecasts that AI may become intelligent assistants to humans, and discusses challenges around jobs, sustainability, education and more. Impacts of AI like autonomous weapons are also addressed. The document advocates balancing commercial and peaceful applications of AI technologies going forward.
1) Machines are increasingly impacting daily human routines through technologies like smart home devices and driverless cars.
2) Both humans and machines process information through pattern recognition, but humans excel at piecing together incomplete information in new ways while machines rely more on analyzing large datasets.
3) Early attempts by companies to use only data analysis or only human judgment in developing TV shows met with varying levels of success, showing the value of combining the two approaches.
Robotics is a branch of technology that deals with the design, construction, operation, and application of robots and computer systems to control them. Robots can take the place of humans in hazardous or manufacturing processes, or resemble humans. The word "robot" comes from the Slavic word for forced labor and was introduced in a 1921 play. Components of a robot include a power source, actuators like electric motors or muscle wire, and sensors for feedback. Artificial intelligence aims to create machine intelligence by designing intelligent agents that perceive their environment and take actions to maximize success. Some problems in AI include replicating specific human traits or capabilities in machines. Philosophy questions whether machines can truly be intelligent or have a mind like humans.
Machine Learning - Where to Next?, May 2015Peter Morgan
This document provides an overview of machine learning and artificial intelligence presented by Peter Morgan at the BrightTALK Machine Learning and Data Science Summit on May 21, 2015. The summary covers the speaker's background working in AI and machine learning, a definition and history of machine learning, current and potential applications of machine learning across many industries, prominent companies and researchers in the field, opportunities and threats of advanced AI, and predictions for the future of the technology.
This technical seminar covers behavior-based robotics and its applications. It begins with definitions of robots, robotics, and behavior-based robotics. It describes how behavior is expressed through stimulus-response diagrams and finite state machines. Behavior-based architectures like subsumption architecture and motor schemas are explained. The history of robotics is reviewed from mechanical robots to present-day humanoids. Applications include entertainment, exploration, medical assistants, transportation, and more. Key issues discussed are grounding in reality, situatedness, embodiment, emergent behavior, and scalability.
Human Robot Interaction (HRI) in Next Generation LearningFarzad Sabetzadeh
The presence of robots in our everyday activities is inevitable in the near future and this should not be met with skepticism but instead, with a practical outlook on how we can best interact with them. From homes to workplaces and cities, we are attempting to make our lives to be more productive, more efficient and so-called "Smarter". The building block of this "Smart" journey lies on how we will educate the next generation of our human workforce to interact and collaborate with robots. The first wave of modernization in human-machine interaction took us from punch cards to keyboards and mouse. The second wave took us to touchscreens and smart devices. This talk will explore the next generation learning and how to prepare and educate ourselves and our next generation for the time, when human-robot interaction (HRI) becomes an essential part of our day to day lives.
Based on Capabilities
B. Based on Functionality
1. Reactive Machines:
- Reactive machines are the simplest form of AI. They perceive their environment and
respond in a predetermined manner to achieve a specific goal.
- Examples include thermostats, industrial robots, and vacuum cleaners.
2. Limited Memory:
- These systems can remember past experiences and use that information to guide future
actions.
- Examples include chess playing programs and self-driving cars.
3. Theory of Mind:
- These systems can model other agents and take their beliefs, intentions, and desires into
account.
- Examples include personal assistants like Siri that understand context.
4. Self
The document discusses the history of artificial intelligence from its origins in the 1940s to modern applications. It describes several key early developments, including the first artificial neuron model (1943), the proposal of the Turing Test (1950), and the coining of the term "artificial intelligence" at the Dartmouth Conference (1956). The document also notes periods of growth and funding declines ("AI winters") for the field throughout its development. Overall, the history shows steady progress in AI from its theoretical beginnings to impactful applications today.
The document provides an introduction to artificial intelligence, including definitions, goals, and applications of AI. It discusses key concepts such as intelligent systems, the history of AI, foundations of AI, and components of AI systems. Examples are given throughout such as chess-playing programs, self-driving cars, and chatbots like Eliza. The document also summarizes an approach for developing an AI to play the game Tic-Tac-Toe.
This document provides an overview of artificial intelligence (AI), including its history, applications, advantages, and disadvantages. It discusses early milestones in AI like the Turing Test (1950) and Logic Theorist (1956). Applications mentioned include agriculture, astronomy, gaming, robotics, and more. Advantages are high speed, reliability in risky situations. Disadvantages include high costs, inability to think outside programmed tasks, and lack of emotions. The conclusion states AI could solve many problems and unlock a future where computers make more informed decisions based on understanding our world through data.
Artificial intelligence (AI) aims to create intelligent machines that can function like humans. AI involves techniques like machine learning and deep learning. AI is used in many applications today including smart assistants, self-driving cars, spam filters, and recommendations. Major companies and countries are investing heavily in AI research and development. Future trends may include greater use of AI in areas like cybersecurity, healthcare, transportation, and combining AI with augmented or virtual reality technologies.
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.
Artificial intelligence is the study of intelligent behavior and the attempt to find ways in which such behavior could be engineered in any type of artifact. There are two main types of AI - weak AI which only simulates human intelligence and strong AI which matches or exceeds human intelligence. Some key developments in AI history include McCarthy coining the term in 1955 and the creation of languages like LISP and PROLOG. Current applications of AI include speech recognition, robotics, gaming, facial recognition and use in the military and life sciences. The future of AI could see machines matching and exceeding human intelligence and potentially merging with humans. There are both advantages like efficiency but also risks like uncontrolled self-modification that come with continued advances in AI.
Artificial intelligence - (A seminar on Emerging Trends of Technology) ileomax
This presentation got the first prize for the competition at a seminar Emerging Trends of Technology @ MGM Indore.
Please leave your comments if you like/unlike it..
Rise of Artificial Intelligence
What is the history of AI, The application, its pros and cons, how would be the future, AI limitations, Threat to humans, Advancements and conclusion.
No one can now deny the importance of artificial intelligence. When we wake up in the morning and until we go to our bed at night, we use AI.
Various applications can be seen of AI for eg. we use language translation, google maps, speech recognition, self-driven cars and many more.
See full presentation to explore more.
Given above is a PowerPoint Presentation on Artificial Intelligence (AI). Ideal for activities, school projects, essays etc. Hope it is accommodating.
Thank you.
You can also find out my other presentations on Technology.
The links are given below-
https://www.slideshare.net/GursheenKaurChawla/all-about-the-internetpptx and https://www.slideshare.net/GursheenKaurChawla/impact-of-online-gamespptx
The document provides an overview of artificial intelligence (AI) including definitions of AI and machine learning. It discusses the history of AI from its origins in the 1940s and 50s to modern applications. The major branches of AI are described as well as common uses in areas like robotics, data mining, medical diagnosis, and video games. Both the advantages of AI such as efficiency and lack of errors as well as the disadvantages including cost and potential to decrease human labor are outlined. The document concludes by discussing the future of AI and some of the ethical issues that arise.
This document provides an introduction to artificial intelligence, including definitions and explanations of key concepts. It defines AI as making computers behave like humans through techniques like machine learning, reasoning, and problem solving. It then discusses narrow AI which focuses on specific tasks, general AI that can understand any intellectual task, and super AI that surpasses human intelligence. The document also covers reactive machines, limited memory AI, and the theory of mind approach. The overall summary is that the document serves as an introductory overview of the basics of artificial intelligence.
Advancement in artificial intelligence: Should Humans be Worried?Raymond Owusu
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8. Basic Definition of AI:
“Branch of Computer Science which deals
with the making of such machines that
behaves and work like a Human.
OR
“The branch of Computer Science that is
concerned with the automation of intelligent
behavior.”
OR
“The study of how to make computers to
do the things which at present a human
can do better.”
9. AI is a system of program which does
something smart.
AI deals with the making of machines
which behaves like humans such that:
Reasoning
Learning
Problem Solving
Perceptions
10. Disciplines of AI:
• Machine Learning:
By finding rules and patterns, make analyses
and prediction.
• Deep Learning:
How brain works to obtain knowledge.
11. Understanding of AI by real life
Smart Phones
Smart Cars
Advertisements
Human Nature
13. Maturation of AI
Year-1943
• Warren McCulloch and Walter Pitts
proposed the model of Artificial neurons
Year-1949
Donald Hebb modifying the strength between neurons .And his
rule called Hebbian Learing.
When two cells fire together connection between them strong.
14. Year-1950
• Alan Turing English mathematician and pioneer in
machine learning.
• Publishes ”Computing machinery and Intelligence”
• Turing Test.
15. BIRTH OFAI
YEAR-1955
• Allen Newell and Herbert A.Simon created “First Intelligent
Program”named was “Logic Thoerist”.
• Program have proven 38 to 52 thoerems form Principia
Mathematica chapter 2.
Year-1956
• John McCarthy American Scientist.
• First workshop on AI. Researcher from CMU,MIT and employee
form IBM met together .
• First adopted the word of”Artificial Intelligence” at Dartmouth
conference.
16. At that time high level computer language
FORTRAN,LISP,COBOL have created.
The Golden years-early enthusiasm(1956-1974)
Year-1966
• The researcher developing algoritms which can solve the
mathematical problems.
• Joseph Weizenbaum created first chatbot named was ELIZA.
Year-1972
• The first humanoid robot was built in JAPAN named was
WABOT-1.
17. The first AI winter(1974-1980)
• In these years Scientist dealt with severe shortage of funding.
• Interest of publicity on AI decrease.
A boom of AI(1981-1987)
• Came back with “expert system”.
• Decision making ability of a human expert.
• First national conference of the America Association on AI
was held at Stanford University
The second AI winter(1987-1993)
• Again investor and government stopped funding for AI search due
to high cost but not efficient.
• Expert system such as XCON was very costly
18. The emergence of intelligent agents.
Year-1997
• Deep blue a chess playing computer from IBM beat Gary Kasparov.
Year-2002
• AI entered the home in the form of Roomba,a vaccum cleaner.
Year-2006
• Came in business world.
• Companies like facebook,twitter and Netflix also started using AI.
19. Deep learning , big data and artificial
intelligence(2011-present)
Year-(2011-2013)
• IBM’s Waston won the jeopardy (a quiz show).
• Personal assistant like Siri , Google now , Cortana recognition to answer
question.
Year-2014
• Chatbot “Eugene Goostman” won
a competition in famous ”turing test”.
Year-2018-2019
Alexa:
• Alexa is an intelligent personal
assistant made by amazon
• Smart speaker
20. DARPA
It is responsible for the developemt of emerging technology
and science.
DARPA working on several project like,
ACTUV(ASW Continuous Trail Unmanned Vessel)
Robotic Landing Gear
AI enabled chips:
Self learning chip
Specific utilization like computer vision, speech
recognition.
AI Learn through observation
Nowadays companies like facebook,Google,IBM and
Amazon are working with AI and creating amazing devices .
24. Heavy Industries:
Huge machines involve risk in their maintenance and work.
So in become necessary part to have an automated AI agent
their operation.
Paints
25. Education:
Solve different problem
OMR system
Finance:
Banking system
ATM
Face recognize account
Investment stocks
39. AI in daily life:
• Virtual Personal Assistant
• Siri/Alexa
• Apple’s Siri and Amazon’s Alexa both use AI to
help you complete tasks or answer questions on
your mobile devices.
• As example of weak AI, Siri and Alexa are
programmed with responses and actions based
on commands or questions posed to them by the
phone owner.
40.
41.
42.
43. Netflix:
Netflix and chill would be pretty boring
without the right Movies and TV shows.
So how does Netflix understand which
movies or show you would be interested in.