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.
The document discusses artificial intelligence (AI) and defines it as the science and engineering of making intelligent machines, especially intelligent computer programs that have the abilities to learn, reason, perceive and understand language. It outlines several key AI technologies like machine learning, computer vision, natural language processing and speech recognition. It provides examples of applications in areas such as game playing, robotics, education, medical diagnosis and more. The document also gives a brief history of AI and discusses some programming languages commonly used in AI like Lisp.
This document discusses artificial intelligence and its components. It begins with definitions of artificial intelligence as making computers behave like humans and as the intelligence exhibited by machines. The field was founded in 1956 at a conference where leaders like John McCarthy established AI research. The components discussed include playing games like chess, developing expert systems, natural language processing, and robotics. It provides examples of computers defeating humans at chess and the use of robots in manufacturing.
Artificial Intelligence - It's meaning, uses, past and future.
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans
This document provides an overview of artificial intelligence (AI) including definitions, history, major branches, uses, advantages, and disadvantages. It discusses how AI aims to simulate human intelligence through machine learning, problem solving, and rational decision making. The history of AI is explored from early concepts in the 1940s-50s to modern applications. Major branches covered include robotics, data mining, medical diagnosis, and video games. Current and future uses of AI are seen in personal assistants, autonomous systems, speech/image recognition, and many other fields. Both advantages like efficiency and disadvantages like job loss are noted.
This document provides an overview of artificial intelligence (AI) and its future. It defines AI as making intelligent machines and outlines its history from Alan Turing's work in the 1950s to modern applications like voice assistants. The document also discusses benefits of AI like home automation and advancements in transportation and search. However, it notes risks such as unemployment and autonomous war machines turning against humans. It concludes that AI is increasingly integrated into technology and daily life and will continue expanding, possibly resulting in super intelligent systems available across many areas.
Introduction to artificial intelligenceRajkumarVara
This document provides an overview of artificial intelligence, including its history, creators, types, and current applications. It defines AI as concerned with building intelligent machines that can perform human tasks. The modern history of AI began in 1956 when John McCarthy proposed the term. Alan Turing invented the Turing machine in the 1940s. There are three main types of AI: artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. Currently, AI is used in applications like chatbots, healthcare, data security, social media, and Tesla's self-driving cars. The document concludes that while AI is not yet as intelligent as depicted in films, its development will significantly change the world.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
The document discusses artificial intelligence (AI) and defines it as the science and engineering of making intelligent machines, especially intelligent computer programs that have the abilities to learn, reason, perceive and understand language. It outlines several key AI technologies like machine learning, computer vision, natural language processing and speech recognition. It provides examples of applications in areas such as game playing, robotics, education, medical diagnosis and more. The document also gives a brief history of AI and discusses some programming languages commonly used in AI like Lisp.
This document discusses artificial intelligence and its components. It begins with definitions of artificial intelligence as making computers behave like humans and as the intelligence exhibited by machines. The field was founded in 1956 at a conference where leaders like John McCarthy established AI research. The components discussed include playing games like chess, developing expert systems, natural language processing, and robotics. It provides examples of computers defeating humans at chess and the use of robots in manufacturing.
Artificial Intelligence - It's meaning, uses, past and future.
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans
This document provides an overview of artificial intelligence (AI) including definitions, history, major branches, uses, advantages, and disadvantages. It discusses how AI aims to simulate human intelligence through machine learning, problem solving, and rational decision making. The history of AI is explored from early concepts in the 1940s-50s to modern applications. Major branches covered include robotics, data mining, medical diagnosis, and video games. Current and future uses of AI are seen in personal assistants, autonomous systems, speech/image recognition, and many other fields. Both advantages like efficiency and disadvantages like job loss are noted.
This document provides an overview of artificial intelligence (AI) and its future. It defines AI as making intelligent machines and outlines its history from Alan Turing's work in the 1950s to modern applications like voice assistants. The document also discusses benefits of AI like home automation and advancements in transportation and search. However, it notes risks such as unemployment and autonomous war machines turning against humans. It concludes that AI is increasingly integrated into technology and daily life and will continue expanding, possibly resulting in super intelligent systems available across many areas.
Introduction to artificial intelligenceRajkumarVara
This document provides an overview of artificial intelligence, including its history, creators, types, and current applications. It defines AI as concerned with building intelligent machines that can perform human tasks. The modern history of AI began in 1956 when John McCarthy proposed the term. Alan Turing invented the Turing machine in the 1940s. There are three main types of AI: artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. Currently, AI is used in applications like chatbots, healthcare, data security, social media, and Tesla's self-driving cars. The document concludes that while AI is not yet as intelligent as depicted in films, its development will significantly change the world.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
The document provides a history of artificial intelligence, key figures in AI development, and examples of modern AI technologies. It discusses how the idea of AI originated in ancient Greece and how Alan Turing introduced the Turing test in 1937. Examples of modern AI include Sophia, a humanoid robot created by Hanson Robotics, and Rashmi, an Indian humanoid robot that can speak three languages. The document outlines advances in AI and its applications in fields such as military technology, space exploration, healthcare, and more.
Title: Incredible developments in Artificial intelligence which was the future scenario.
Here I discussed the with the major backbones of AI (Machine learning, Neural networks) types Machine learning and type of Artificial intelligence and with some real-time examples of AI and ML & Benefits and Future of AI with some pros and Cons of Artificial Intelligence.
Artificial intelligence (AI) is a broad field that combines computer science, psychology, and philosophy with the goal of creating machines that can think like humans. AI aims to develop intelligent agents that can perceive their environment and take actions to maximize their success. The main fields of AI include machine vision, expert systems, and creating machines that can think rationally or act like humans. The goals of AI include solving complex problems, enhancing human and computer interactions, and developing the theory and practice of building intelligent machines.
This document discusses artificial intelligence and robotics. It begins with definitions of AI from early researchers like John McCarthy and Alan Turing. It then discusses the history and development of AI, including important figures and programming languages. Applications of robotics are outlined in various fields like industrial uses, medical care, and entertainment. The document also explores how AI works with robots through natural language processing. It concludes by discussing the future of AI and warnings about potential issues that may arise from advanced AI systems.
Benefits and risk of artificial intelligence slideshareSandeep Mishra
This document discusses the benefits and risks of artificial intelligence. It begins by explaining what AI is currently, which is narrow or weak AI designed for specific tasks, and the long term goal of general or strong AI that can outperform humans at most cognitive tasks.
It then discusses why researching AI safety is important, both to ensure beneficial outcomes as AI capabilities increase and to address challenges like developing superintelligence that could surpass human intellect. The document outlines some potential dangers like AI being programmed for harmful purposes or failing to fully align goals.
Finally, it notes increased interest in AI safety from technology leaders given recent advances bringing many AI milestones thought to be decades away much closer to the present, making addressing safety issues more
This document is a presentation on artificial intelligence. It begins with a definition of AI and discusses its foundations. It then covers information and applications of AI, its growth, top AI countries including the US, India, and China, and the robot Sophia. The presentation also outlines advantages such as error reduction and difficult exploration, as well as disadvantages including high costs and lack of improvement with experience. It concludes with a bibliography of sources.
An overview of artificial intelligence from the perspective of a potential venture capital investment: what it is, its history, how it can be used, and what it could mean for the future of various industries and humanity.
The document discusses human intelligence and artificial intelligence (AI). It defines human intelligence as comprising abilities such as learning, understanding language, perceiving, reasoning, and feeling. AI is defined as the science and engineering of making machines intelligent, especially computer programs. It involves developing systems that exhibit traits associated with human intelligence such as reasoning, learning, interacting with the environment, and problem solving. The document outlines the history of AI and discusses approaches to developing systems that think like humans or rationally. It also covers applications of AI such as natural language processing, expert systems, robotics, and more.
Artificial intelligence is the study of how to create intelligent machines and programs that can solve complex problems, learn from experience, and take actions that maximize their chances of success. There are two main approaches to AI: engineering, which focuses on building intelligent systems, and cognitive modeling, which aims to understand and emulate human intelligence. AI has many applications including game playing, handwriting recognition, speech recognition, human-computer interaction, navigation, computer vision, expert systems, and web search tools. Some notable achievements of AI include Deep Blue defeating Garry Kasparov at chess in 1997 and AI programs proving mathematical conjections and controlling logistics during the Gulf War.
This document provides an overview of artificial intelligence (AI), including its history, categories, branches, applications, and tools. It discusses how AI has evolved through different generations of computing. Key topics covered include expert systems, neural networks, programming languages used in AI, the American Association for Artificial Intelligence (AAAI), and perspectives on AI's future potential impacts and applications.
Artificial intelligence (AI) is defined as making computers do intelligent tasks like humans. It works using artificial neurons that mimic biological neurons. Neural networks are composed of interconnected artificial neurons. The Turing test tests a machine's ability to demonstrate intelligence comparable to a human. There are different types of AI like expert systems, machine learning, and intelligent agents. While AI can process large amounts of data fast without human limitations, it lacks common sense, intuition, and creativity that humans possess. Overall, AI aims to supplement natural human intelligence by performing tasks through machines to reduce human labor and mistakes.
The document provides an overview of artificial intelligence, including its definition, history, approaches, tools for evaluation, applications, and predictions for the future. It discusses topics such as the traits of an intelligent system, methods like cybernetics and symbolic/statistical approaches, tools including search algorithms and neural networks, and applications in fields like medicine, robotics, and web search engines.
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents".
Robotics is the interdisciplinary branch of engineering and science that includes mechanical engineering, electrical engineering, computer science, and others. Robotics deals with the design, construction, operation, and use of robots,[1] as well as computer systems for their control, sensory feedback, and information processing.
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, current applications, challenges, and the future of AI. It discusses early pioneers in AI like Alan Turing and John McCarthy and how AI has progressed from theoretical discussions to applications in digital assistants, games, robotics, and more through advances in deep learning. Both pros and cons of AI are presented, with the future of AI predicted to include self-driving cars, improved healthcare, and space exploration. The document concludes that AI aims to create machine intelligence through studying and designing intelligent agents.
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 the ability of digital computers or robots to perform tasks commonly associated with intelligent beings. The idea of AI has its origins in ancient Greece but the field began in the 1950s. Today, AI is used in applications like IBM's Watson, driverless cars, automated assembly lines, surgical robots, and traffic control systems. The future of AI depends on whether researchers can achieve human-level or superhuman intelligence through techniques like whole brain emulation. Critics argue key challenges remain in replicating general human intelligence and consciousness with technology.
The document discusses artificial intelligence and how it works. It defines intelligence and AI, explaining that AI aims to make computers as intelligent as humans. It describes how AI uses artificial neurons and networks to function similarly to the human brain. Examples of AI applications are given, like expert systems used in various domains. The document also compares human and artificial intelligence, noting their differing strengths and weaknesses.
Artificial intelligence plays a major role in digital marketing. There are different types of AI:
Reactive machines simply react to input with output without learning. Limited memory types can store previous data and predictions to make better forecasts. Theory of mind AI is beginning to interact with human thoughts and emotions, as seen in self-driving cars interacting with other drivers. The final type is hypothetical self-aware AI that could achieve independent intelligence and potential negotiation with humans.
This document provides instructions for a project where students write a description of a witch or wizard, save a picture of their face, and use an online tool called Blabberize to add their audio description to the picture, creating an animated character. It lists 11 steps for completing the project, which includes writing the description, saving files, uploading the picture to the tool, drawing a mouth on the character, recording the audio description, saving and naming the final blabber creation, and checking their work.
The Irish Football Association was founded in 1880 in Belfast and is the 4th oldest football association. It has qualified for 3 World Cups and represents all communities in Northern Ireland. The IFA runs international, domestic, and grassroots football programs, including over 870 adult and youth teams. It established the Football For All program to promote an inclusive culture and tackle sectarianism through education and community projects. Research shows the program has been largely successful in eliminating sectarianism and creating an inclusive environment for football in Northern Ireland. The IFA aims to further promote football for all and remove any remaining barriers to inclusion.
The document provides a history of artificial intelligence, key figures in AI development, and examples of modern AI technologies. It discusses how the idea of AI originated in ancient Greece and how Alan Turing introduced the Turing test in 1937. Examples of modern AI include Sophia, a humanoid robot created by Hanson Robotics, and Rashmi, an Indian humanoid robot that can speak three languages. The document outlines advances in AI and its applications in fields such as military technology, space exploration, healthcare, and more.
Title: Incredible developments in Artificial intelligence which was the future scenario.
Here I discussed the with the major backbones of AI (Machine learning, Neural networks) types Machine learning and type of Artificial intelligence and with some real-time examples of AI and ML & Benefits and Future of AI with some pros and Cons of Artificial Intelligence.
Artificial intelligence (AI) is a broad field that combines computer science, psychology, and philosophy with the goal of creating machines that can think like humans. AI aims to develop intelligent agents that can perceive their environment and take actions to maximize their success. The main fields of AI include machine vision, expert systems, and creating machines that can think rationally or act like humans. The goals of AI include solving complex problems, enhancing human and computer interactions, and developing the theory and practice of building intelligent machines.
This document discusses artificial intelligence and robotics. It begins with definitions of AI from early researchers like John McCarthy and Alan Turing. It then discusses the history and development of AI, including important figures and programming languages. Applications of robotics are outlined in various fields like industrial uses, medical care, and entertainment. The document also explores how AI works with robots through natural language processing. It concludes by discussing the future of AI and warnings about potential issues that may arise from advanced AI systems.
Benefits and risk of artificial intelligence slideshareSandeep Mishra
This document discusses the benefits and risks of artificial intelligence. It begins by explaining what AI is currently, which is narrow or weak AI designed for specific tasks, and the long term goal of general or strong AI that can outperform humans at most cognitive tasks.
It then discusses why researching AI safety is important, both to ensure beneficial outcomes as AI capabilities increase and to address challenges like developing superintelligence that could surpass human intellect. The document outlines some potential dangers like AI being programmed for harmful purposes or failing to fully align goals.
Finally, it notes increased interest in AI safety from technology leaders given recent advances bringing many AI milestones thought to be decades away much closer to the present, making addressing safety issues more
This document is a presentation on artificial intelligence. It begins with a definition of AI and discusses its foundations. It then covers information and applications of AI, its growth, top AI countries including the US, India, and China, and the robot Sophia. The presentation also outlines advantages such as error reduction and difficult exploration, as well as disadvantages including high costs and lack of improvement with experience. It concludes with a bibliography of sources.
An overview of artificial intelligence from the perspective of a potential venture capital investment: what it is, its history, how it can be used, and what it could mean for the future of various industries and humanity.
The document discusses human intelligence and artificial intelligence (AI). It defines human intelligence as comprising abilities such as learning, understanding language, perceiving, reasoning, and feeling. AI is defined as the science and engineering of making machines intelligent, especially computer programs. It involves developing systems that exhibit traits associated with human intelligence such as reasoning, learning, interacting with the environment, and problem solving. The document outlines the history of AI and discusses approaches to developing systems that think like humans or rationally. It also covers applications of AI such as natural language processing, expert systems, robotics, and more.
Artificial intelligence is the study of how to create intelligent machines and programs that can solve complex problems, learn from experience, and take actions that maximize their chances of success. There are two main approaches to AI: engineering, which focuses on building intelligent systems, and cognitive modeling, which aims to understand and emulate human intelligence. AI has many applications including game playing, handwriting recognition, speech recognition, human-computer interaction, navigation, computer vision, expert systems, and web search tools. Some notable achievements of AI include Deep Blue defeating Garry Kasparov at chess in 1997 and AI programs proving mathematical conjections and controlling logistics during the Gulf War.
This document provides an overview of artificial intelligence (AI), including its history, categories, branches, applications, and tools. It discusses how AI has evolved through different generations of computing. Key topics covered include expert systems, neural networks, programming languages used in AI, the American Association for Artificial Intelligence (AAAI), and perspectives on AI's future potential impacts and applications.
Artificial intelligence (AI) is defined as making computers do intelligent tasks like humans. It works using artificial neurons that mimic biological neurons. Neural networks are composed of interconnected artificial neurons. The Turing test tests a machine's ability to demonstrate intelligence comparable to a human. There are different types of AI like expert systems, machine learning, and intelligent agents. While AI can process large amounts of data fast without human limitations, it lacks common sense, intuition, and creativity that humans possess. Overall, AI aims to supplement natural human intelligence by performing tasks through machines to reduce human labor and mistakes.
The document provides an overview of artificial intelligence, including its definition, history, approaches, tools for evaluation, applications, and predictions for the future. It discusses topics such as the traits of an intelligent system, methods like cybernetics and symbolic/statistical approaches, tools including search algorithms and neural networks, and applications in fields like medicine, robotics, and web search engines.
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents".
Robotics is the interdisciplinary branch of engineering and science that includes mechanical engineering, electrical engineering, computer science, and others. Robotics deals with the design, construction, operation, and use of robots,[1] as well as computer systems for their control, sensory feedback, and information processing.
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, current applications, challenges, and the future of AI. It discusses early pioneers in AI like Alan Turing and John McCarthy and how AI has progressed from theoretical discussions to applications in digital assistants, games, robotics, and more through advances in deep learning. Both pros and cons of AI are presented, with the future of AI predicted to include self-driving cars, improved healthcare, and space exploration. The document concludes that AI aims to create machine intelligence through studying and designing intelligent agents.
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 the ability of digital computers or robots to perform tasks commonly associated with intelligent beings. The idea of AI has its origins in ancient Greece but the field began in the 1950s. Today, AI is used in applications like IBM's Watson, driverless cars, automated assembly lines, surgical robots, and traffic control systems. The future of AI depends on whether researchers can achieve human-level or superhuman intelligence through techniques like whole brain emulation. Critics argue key challenges remain in replicating general human intelligence and consciousness with technology.
The document discusses artificial intelligence and how it works. It defines intelligence and AI, explaining that AI aims to make computers as intelligent as humans. It describes how AI uses artificial neurons and networks to function similarly to the human brain. Examples of AI applications are given, like expert systems used in various domains. The document also compares human and artificial intelligence, noting their differing strengths and weaknesses.
Artificial intelligence plays a major role in digital marketing. There are different types of AI:
Reactive machines simply react to input with output without learning. Limited memory types can store previous data and predictions to make better forecasts. Theory of mind AI is beginning to interact with human thoughts and emotions, as seen in self-driving cars interacting with other drivers. The final type is hypothetical self-aware AI that could achieve independent intelligence and potential negotiation with humans.
This document provides instructions for a project where students write a description of a witch or wizard, save a picture of their face, and use an online tool called Blabberize to add their audio description to the picture, creating an animated character. It lists 11 steps for completing the project, which includes writing the description, saving files, uploading the picture to the tool, drawing a mouth on the character, recording the audio description, saving and naming the final blabber creation, and checking their work.
The Irish Football Association was founded in 1880 in Belfast and is the 4th oldest football association. It has qualified for 3 World Cups and represents all communities in Northern Ireland. The IFA runs international, domestic, and grassroots football programs, including over 870 adult and youth teams. It established the Football For All program to promote an inclusive culture and tackle sectarianism through education and community projects. Research shows the program has been largely successful in eliminating sectarianism and creating an inclusive environment for football in Northern Ireland. The IFA aims to further promote football for all and remove any remaining barriers to inclusion.
The document contains praise and admiration for Indian cricketer Sachin Tendulkar from both fellow cricketers and others in the sports world. They describe him as a once-in-a-generation genius and player who has inspired and motivated many. His longevity, records, humility and the joy he brings millions of fans in India through his batting are highlighted. Many also note how focused and remarkable he is to watch bat.
Harry Potter and the Magic of LiteratureSharon Gerald
The document provides a detailed timeline and analysis of the Harry Potter book series, discussing its literary genres, archetypes, motifs and allusions. It summarizes the series' evolution from initial rejections to worldwide popularity. It also analyzes how the books draw from epic tales, mysteries, myths and legends, with Harry exemplifying common hero archetypes. Literary devices like foreshadowing and symbolism are explored through characters and creatures.
A tribute to SRT as he completed his 20 years in International cricket...Read the whole post here.. http://snicked.wordpress.com/2010/04/18/sachintendulkar/
This document contains a quiz about the Harry Potter series with 21 multiple choice questions. It discusses characters, places, spells, and other details from the books. The questions range from identifying the actor who narrated the audio books to defining acronyms like O.W.L.s and naming the gems associated with each Hogwarts house. It also includes the answers to the quiz questions.
The document discusses artificial intelligence, including its history, applications, and languages. It provides an overview of AI, noting that it aims to recreate human intelligence through machine learning and problem solving. The document then covers key topics like the philosophy of AI, limits on machine intelligence, and comparisons between human and artificial brains. It also gives brief histories of AI and machine learning. The document concludes by discussing popular AI programming languages like Lisp and Prolog, as well as various applications of AI technologies.
10 Steps to a Successful Social Media Marketing StrategyJeff Bullas
Social media marketing success is something that business is now starting to see as vital as part of their marketing plans. Just having a Facebook page or a Twitter account is just the start. Planning and creating a strategy is vital if you want to succeed long term. In this presentation we look at the 10 steps you need to implement. We also look at some specific tactics and case studies of brands and businesses that have been successful at social media marketing.
After a great trip to Melbourne for Future Assembly, I thought it'd be great to present our thoughts on Design Ethics for Artificial Intelligence.
It's a thought-provoking and engaging presentation and will have you pondering our flawed and highly subjective value systems.
Artificial intelligence is the study and design of intelligent agents, with no single goal. It aims to put the human mind into computers by developing machines that can achieve goals through computation. The origins of AI began in the 1940s with the development of electronic computers. Significant early developments included the first stored program computer in the 1950s, the Dartmouth Conference which coined the term "artificial intelligence" in the 1950s, and the development of the LISP programming language. In the following decades, AI research expanded and led to applications in fields like expert systems, games, and military systems. While progress has been made, the full extent of intelligence and the future of AI remains unknown.
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, methods, applications, achievements, and the future of AI. It defines AI as the science and engineering of making intelligent machines, especially intelligent computer programs. The document outlines different methods of AI such as symbolic AI, neural networks, and computational intelligence. It also discusses a wide range of applications of AI such as finance, medicine, gaming, robotics, and more. Finally, it discusses some achievements of AI and envisions continued growth and importance of AI in the future.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
How to Become a Thought Leader in Your NicheLeslie Samuel
Are bloggers thought leaders? Here are some tips on how you can become one. Provide great value, put awesome content out there on a regular basis, and help others.
There's no such thing as Artificial IntelligenceJon Whittle
Despite impressive advances in artificial intelligence (AI), none of the systems currently in use display anything remotely equivalent to human-level intelligence. That's not necessarily a bad thing - this talk argues that the future of AI is Collaborative Intelligence where the best of AI works with the best of human intelligence
Here are three possible interpretations of the phrase "Time flies like an arrow":
1. The passage of time seems to go by very quickly, in the same way that an arrow flies through the air.
2. Certain types of insects that lay their eggs on decaying matter, known as flies, move through the air in a similar way to arrows.
3. The idiom is using "flies" to refer to time passing quickly in an abstract sense, similar to an arrow moving swiftly through space.
The key challenges with natural language understanding are ambiguity and context. Even a short phrase like this one could have multiple meanings without additional context clues. Determining the intended interpretation requires commonsense reasoning abilities that computers still lack
Machine Learning for Non-technical Peopleindico data
Machine learning is one of the most promising and most difficult to understand fields of the modern age. Here are the slides from Slater Victoroff's (CEO of indico) talk at General Assembly Boston for non-technical folks on how to separate the signal from the noise -- stay tuned for the next time he speaks:
https://generalassemb.ly/education/machine-learning-for-non-technical-people
This document discusses how the most inspiring leaders and organizations think, act, and communicate from the inside out by focusing on their purpose or beliefs, rather than just describing what they do. It argues that people are inspired by and buy into an organization's reason for existing ("why") rather than just its products or services ("what"). Examples are given of how Apple, Martin Luther King Jr., and the Wright brothers succeeded by focusing on their driving beliefs and inspiring others who shared those beliefs, rather than just promoting their tangible offerings. The document suggests businesses and leaders should define and communicate their purpose in order to attract loyal customers and followers.
Researchers, Discovery and the Internet: What Next?David Smith
A web2.0 issues and implications overview I put together for the Research Information Network as part of their workshop on researchers and discovery services.
http://www.rin.ac.uk/discovery-services-workshop
The document discusses the themes of ignorance being bliss and the dangers of knowledge in Mary Shelley's Frankenstein. It provides quotes from the novel where Victor Frankenstein regrets pursuing his scientific ambitions to create life, as it leads to disastrous consequences like being shunned by society upon creating the monster and then his friends and family being killed. Near his own death, Victor warns Walton to seek happiness in tranquility and avoid ambition or pursuing knowledge in science, as it could have dangerous results.
Artificial Intelligence or the Brainization of the EconomyWilly Braun
60 years ago, John McCarthy used for the first time the term “Artificial Intelligence”. What does it mean and how has it evolved since 1956?
This is what daphni tried to answer in this in-depth report about AI. We’ve interviewed some of the brightest minds in the field: Bruno Maisonnier (founder of Aldebaran robotics), Massimiliano Versaca (CEO Neurala), Alexandre Lebrun (co-founder of wit.ai), Luc Julia (VP Innovation Samsung).
By Paul Bazin and Pierre-Eric Leibovici
This document provides a summary of artificial intelligence including definitions, history, and whether computers can perform certain tasks. It discusses four approaches to defining AI: (1) thinking like humans through cognitive science, (2) thinking rationally using logic, (3) acting like humans as in the Turing test, and (4) acting rationally to achieve the best outcomes. The document also summarizes key events in the history of AI and whether computers can beat humans at games, recognize speech, understand language, learn, see, plan, and more.
Introduction to Artificial intelligence and MLbansalpra7
**Title: Understanding the Landscape of Artificial Intelligence: A Comprehensive Exploration**
**I. Introduction**
In recent decades, Artificial Intelligence (AI) has emerged as a transformative force, reshaping industries, influencing daily life, and pushing the boundaries of human capabilities. This comprehensive exploration delves into the multifaceted landscape of AI, encompassing its origins, key concepts, applications, ethical considerations, and future prospects.
**II. Historical Perspective**
AI's roots can be traced back to ancient history, where philosophers contemplated the nature of intelligence. However, it wasn't until the mid-20th century that AI as a field of study gained momentum. The influential Dartmouth Conference in 1956 marked the official birth of AI, with early pioneers like Alan Turing laying the theoretical groundwork.
**III. Foundations of AI**
Understanding AI requires grasping its foundational principles. Machine Learning (ML), a subset of AI, empowers machines to learn patterns and make decisions without explicit programming. Within ML, various approaches, such as supervised learning, unsupervised learning, and reinforcement learning, play crucial roles in shaping AI applications.
**IV. Types of Artificial Intelligence**
AI is not a monolithic entity; it spans a spectrum of capabilities. Narrow AI, also known as Weak AI, excels in specific tasks, like image recognition or language translation. In contrast, General AI, or Strong AI, would possess human-like intelligence across a wide range of tasks, a goal that remains a long-term aspiration.
**V. Applications of AI**
AI's impact is felt across diverse sectors. In healthcare, AI aids in diagnostics and personalized treatment plans. In finance, it enhances fraud detection and risk assessment. Self-driving cars exemplify AI in transportation, while virtual assistants like Siri and Alexa showcase its role in daily life. The convergence of AI with other technologies, such as the Internet of Things (IoT) and robotics, amplifies its transformative potential.
**VI. Machine Learning Algorithms**
The backbone of AI lies in its algorithms. Linear regression, decision trees, neural networks, and deep learning models are among the many tools in the ML toolkit. Exploring the mechanics of these algorithms reveals the intricacies of how AI processes information, learns from data, and makes predictions.
Custom Research Paper Writing Service By Khan John - IssuuSusan Cox
This document provides instructions for using a custom research paper writing service on the HelpWriting.net website. It outlines a 5-step process: 1) Create an account with an email and password. 2) Complete a 10-minute order form providing instructions, sources, and deadline. 3) Review writer bids and qualifications and select a writer. 4) Review the completed paper and authorize payment. 5) Request revisions to ensure satisfaction, and the company guarantees original, high-quality work with refunds for plagiarism.
This is a light-hearted, non-technical presentation about the current state of the art in Artificial Intelligence, particularly the field of Neural Networks and Deep Learning. This talk was presented for the general public in Mission Creak festival in Iowa City, IA on March 3, 2015
Make things people want verses make people want things. Technology and the minutia of bullshit that proclaims to promote it get's uncovered and tortured by Steve Price, along with some examples of great things.
I've included these because in essence these notes are taken from the people behind some of the products and help to (I hope) expose them and their products for the nonsense they really are.
Ben Kunz Mediassociates speech to Boise Ad FederationBen Kunz
Greetings -- I hope you enjoy this exploration of the history of human networks, how media can best use them, and the ethical conundrum we now face over how far to take personal minds in our marketing. For more information, ping me at 203 506 7269. Cheers. @benkunz
Roald Dahl Quote Good Writing Is Essentially RewritiJessica Huston
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
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- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
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Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
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- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
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4. 4
Notes:
1. Intro - When we talk about machines today, we’re referring to artificial intelligence and machine learning
programs (like Siri) and robots like Arnold in Terminator. Do I have to call him the Governator now? Not
sure. In any case, we all see these machines around us, now impacting our day-to-day.
2. Here’s a simple example. Let’s walk through the images at the top.
- You used to wake up to a mechanical clock a wind-up that would rattle your bedside each morning.
- Once you were up, on a cold day you might wander over to your thermostat check the temperature and
manually turn on your heating.
- After some breakfast you might cozy up to a print newspaper magazine...telling you about the “yuuuuuge
crowds” at Trumps inauguration.
- You then jump into your car for your daily commute to work, considering traffic as you go along and
adjusting your route.
3. Today, you wake up to an alarm clock set by your smartphone.
- As you wake up you either control your Nest thermostat device and change the temperature or let the
pre-set mourning temperature kick in.
- Maybe you stroll to the kitchen and grab your espresso, while listening to your Amazon Alexa device walk
you through the morning news.
- Soon, when you step out of your house you may enter your Google driverless car, which will take you to
work while recognizing all traffic patterns and schedule changes faster than any human ever could.
6. Ventral Stream
(recognizes objects,
ties words to what
you’re seeing)
Dorsal Stream
(recognizes objects
in physical space,
ties a 3-D image to
what you’re seeing)
Limbic System
(recognizes feelings attached to
what you’re seeing)
6
Eyes
(as light enters recognizes
geometry/shapes, sends
information 30 parts brain)
1
2
3 4
Source: TED Talk “Three ways the brain creates meaning.”
7. 7 Source: TED Talk “Three ways the brain creates meaning.”
Notes:
Source/Credit: TED Talk “Three ways the brain creates meaning.”
Link: https://www.ted.com/talks/tom_wujec_on_3_ways_the_brain_creates_meaning
Intro
- Let’s talk a little about how our brains processes information.
- Cognitive psychologists tell us that the human brain doesn’t see the world as it is.
- Instead it actually creates a collection of “ah-ha” moments as it discovers and processes
information.
Item #1 on slide - Eyes.
- Processing begins with the eyes
- Light enters and hits the back of the retina, circulates, and streams to the very back of
the brain at the primary visual cortex.
- Here the brain sees simple geometry, just shapes. But here’s the really important
part...this area of the brain also sends information to 30 other parts of your brain.
- These other parts then piece together what you’re seeing in a “ah-ha” experience.
8. 8 Source: TED Talk “Three ways the brain creates meaning.”
Notes:
Let’s talk about a few of the key parts of the brain that receive this information:
- Item #2 Ventral Stream - this is the part of the brain that recognizes a thing as a thing
(...that’s a phone). It’s the part of the brain that’s activated when you call something by
a name - a word.
- Item #3 Dorsal Stream - this area locates objects in physical space. So right now
you’re looking at your screen maybe in front of a wall, and you’re seeing a 3D mental
map of this space. If you closed your eyes right now you could probably touch the
screen and the wall behind it.
- Item #4 Limbic System - deep inside the brain, this is a super old part of your brain is
what feels. So when you see a picture of your dog and feel love...or you see a picture
of your ex at McDonalds in your stories and feel...hangry?
So what can we learn from this?
- The human eye creates a map of what you’re seeing and the space around you by
identifying dozens or hundreds of objects.
- The brain then processes this information it sees to create one unified mental node of the
world around you.
- Quite simply, humans are amazing pattern-recognition machines.
10. 10
Notes:
1. Let’s run through a simple example - the act of reading.
2. You first recognize the patterns of individual letters
3. Then the patterns of individual words
4. Then groups of words together, then paragraphs, then entire chapters, and books overall.
- And take it from me, as the “old guy” in the room, the books and articles you read now whether in the
classroom or not, all add up.
- Your brain looks at information and patterns across this massive library of things you’ve read in your life.
11. IMDB Rating: 7.5 IMDB Rating 9.0
IMDB Rating: 7.4
11
vs
IMDB Rating: 9.2
Source: IMDB website. TED Talk “How to use data to make a hit TV show.”
12. 12 Source: IMDB website. TED Talk “How to use data to make a hit TV show.”
Notes:
Source/Credit: TED Talk “How to use data to make a hit TV show.”
Link: https://www.ted.com/talks/sebastian_wernicke_how_to_use_data_to_make_a_hit_tv_show
1. Let’s go back in time to 2013. Before original shows online were a normal thing. Back then,
Amazon and Netflix set out to launch original TV Shows.
- At the time Amazon had a senior executive named Roy Price, who was in charge of picking the shows
content the company was going to create.
- Roy decided to to take a bunch of TV show ideas, through an evaluation picked 8, and for each of these 8
candidates created a pilot or first episode.
- Amazon then took these shows and put them online for millions of users to watch...for free.
- So millions showed up and watched these episodes and Amazon used machine learning and algorithms to
analyze in detail when someone pressed pause, when someone skipped a scene, what they skipped,
and what they replayed.
- After crunching all the data an answer emerges and Amazon looked to greenlight a sitcom about 4
Republican US senators. It was called “Alpha House.” How many of you have heard of it? (audience raises
hands)
- Well it was fantastically average. In TV land getting an IMDB rating of around 7.4 means you’re part of the
large pile of shows that are average. Alpha House was a 7.6
13. 13 Source: IMDB website. TED Talk “How to use data to make a hit TV show.”
Notes:
2. Now in the same year, Netflix also sets out to launch original TV Shows.
- Ted Sarandos, Netflix’s Chief Content Officer, doesn’t hold a competition.
- Ted worked with his team and they used the data to discover what kinds of content people liked, the ratings they gave,
what producers they liked, what actors and so on. They realized a show about a single Senator could be really successful.
They then found and revamped a British show called “House of Cards.”
- House of cards was a fantastic success. It has an IMDB rating of 9.0, well above the average, and is in the small sliver of
very successful shows.
- Think The Godfather versus The Accountant, when comparing the two shows.
3. The question of course is, what happened?
- Amazon conducted a crowdsourced process to decide on their show versus Netflix which had a human team look at machine
generated data about their subscribers to determine the “House of Cards” series could be successful with this same audience.
Today, Amazon follows a similar process looking at their Prime subscribers and put out shows that win awards.
- This is just one example, but there are many scenarios where the analysis of millions of data points with no human analysis
does not yield the best result.
4. Why is this the case?
- All data analysis involves taking a problem, ripping it apart and understanding its little pieces. Then putting these pieces
together to come to some conclusion.
- Machines conducting data analysis are not great at putting pieces back together and to drawing a conclusion.
- However, as we now know, the human brain is really good at that. It’s all about pattern recognition.
- Even with incomplete information, especially if the human brain is that of an expert’s, humans can look at different pieces of
information and rebuild them into a single unified answer.
16. 16 Source: TED Talk “The jobs we’ll lose to machines and the ones we won’t.”
Notes:
Source/Credit: TED Talk “The jobs we’ll lose to machines - and the ones we won’t.”
Link:
https://www.ted.com/talks/anthony_goldbloom_the_jobs_we_ll_lose_to_machines_and_the_ones_w
e_won_t?language=en
1. Let’s start by talking about Artificial Intelligence and Machine learning.
- Machine learning is responsible for most of the disruption we’ve seen to date. It's the most powerful branch
of artificial intelligence. It allows machines to learn from data and mimic some of the things that humans can
do.
- Machine learning started in the early '90s with relatively simple tasks like assessing credit risk from loan
applications or sorting mail by reading handwritten zip codes.
- Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far,
far more complex tasks... like scanning your eyes and diagnosing diseases such as diabetic retinopathy or
even something like reading human essays and grading them just like a teacher would
2. Now, there have been some things that machines haven’t been great at. Machines haven’t been
able to handle things they haven't seen many times before.
- The fundamental limitations of machine learning is that it needs to learn from large volumes of past data.
Now, humans don't.
- We have the ability to connect broken pieces of information and solve problems we’ve never seen before.
18. 18 Source: Google DeepMind materials and book “Whiplash - How to Survive Our Faster Future.”
Notes:
Source/Credit: Google Deepmind materials and book “Whiplash - How to Survive Our Faster Future”
by Jeff Howe and Joi Ito
Link: https://www.amazon.com/Whiplash-How-Survive-Faster-Future/dp/1455544590
1. Today, the limitation of machines not being able to handle the unfamiliar is also changing. Let’s
walk through an example.
2. What you’re seeing in the middle of this slide is the ancient Chinese board game called “Go.”
- It’s probably one of the most complex games humans have ever devised.
- There are 10 to the power of 170 possible board positions. This is more than there are atoms in the
universe.
- Since there are so many possible positions, there is no way to calculate all possible moves.
- One of the reasons a robot hasn’t been able to beat a human player...until it finally happened last year in
March of 2016.
3. The Google DeepMind algorithm beat a human 4 out of 5 times. Where did DeepMind come from
and how did it win?
- What is DeepMind? DeepMind was actually a British artificial intelligence startup founded by Dennis
Hassabis in 2010. Based here in London. Google acquired the company in 2014 for $500M and continued
the team’s work with Dennis at the helm. He’s a young guy and a genius, so for anyone that’s interested in
AI, I would recommend googling him.
19. 19 Source: Google DeepMind materials and book “Whiplash - How to Survive Our Faster Future.”
Notes:
- When the team build the DeepMind algorithm, called AlphaGo, they didn’t use brute force to calculate all the moves
it could make. As was done previously. Instead they used reinforcement learning and neural networks to mimic
the process of a human brain.
4. What is reinforcement learning?
- Unlike AI for Siri or IBM Watson, Deepmind uses deep reinforcement learning. The team started training the
algorithm by showing it 100,000 games. At first it just mimicked human players. Then it allowed the machine to play
itself 30 MILLION TIMES, using reinforcement learning the system learned to improve itself incrementally by avoiding
its errors and also by “reinforcing” its wins.
- The machine knows a certain move resulted in a win more times in the past, than another move, and thus chooses
that move.
- DeepMind combined this memory system with an approach to AI called “neural networking” which mimics the
human brain and acts as a bridge between information we give the machine and it’s own memory system.
- In short the machine developed a subconscious that helped determine the moves it played. The same way a
human that’s a master of the game has a subconscious containing all of it’s prior gaming history.
5. What’s next to DeepMind?
- It’s been tested to play arcade games and is now moving on to immersive 3D games like Doom because it’s a
closer proxy to real life.
- Over time DeepMind will move into healthcare, robotics, computer vision, finance, and even news publishing and
writing.
22. 22
Notes:
1. We’ve already seen what machines can do when they’re given a “memory” so it’s not hard to
imagine a world maybe just a handful of years away where robots are as lifelike as they are in the
HBO show Westworld.
2. Let’s talk more about WestWorld.
- In the show the machines or “hosts” as they’re called are given an extra script of code called "reveries" or
revenant memories.
- These memories can be subtle actions the robots have taken in the past, or violent actions they've taken.
- These memories are like a subconscious and this single feature leads the robots to learn that they are in
fact...robots and that their world is designed by humans.
- Well things go dark from there. CLIP OF WESTWORLD:
https://www.youtube.com/watch?v=0CBRByBCcRU
3. So is that it? Are we all doomed?
- In the thousands of years of meaningful civilization...AI is the first thing that humans have created that
tends to function in ways humans can’t predict. It can be scary.
- However, if you put aside the WestWorld scenario...of robot in a cowboy hat killing you in a saloon.
- You can imagine AI helping us to fix some of the biggest issues faced by the human race. It can help us
cure diseases and build things that would have taken us centuries to make otherwise. So the future of
humans vs. machines isn’t all carnage :) THE END.