The document provides an overview of artificial intelligence and its applications and risks in the life sciences domain. It discusses the history and recent advances of AI, including deep learning techniques. It then outlines several current and potential future applications of AI in life sciences areas like drug discovery, clinical trials, manufacturing and more. However, it also notes many open risks like data and model bias, adversarial attacks, lack of explainability and more. It argues that agencies are beginning to regulate AI for medical applications but that more work is needed to address risks and ensure appropriate, safe and effective use of AI in life sciences.
A brief overview of artificial intelligence (AI), followed by a few examples of practical use within small businesses, large enterprises, and nonprofits.
The document discusses artificial intelligence (AI) and machine learning. It provides examples of how machine learning works including showing the training process and making inferences from new data. It then discusses applications of AI like computer vision, natural language processing, reinforcement learning and more. It also discusses the growth and capabilities of AI over time as well as implications and applications in different industries.
3 steps to Creating Conversational AI with Everything Around UsJack C Crawford
Text chatbots and smart speakers have introduced new ways to search for information, get things done, and control a growing number of smart devices around us. These manifestations of intelligence have been limited to simple assistance, and have not yet reached the third stage of chatbot maturity described by Gartner. In this talk, we explore three steps to accelerate the move to engaging AI.
Augmented intelligence is new way forward ! Steve Ardire
1. Augmented Intelligence transcends current narrow AI and allows machines and humans to work together pervasively and competitively.
2. Augmented Intelligence provides faster insights into operations too complex for human minds alone by understanding them better.
3. Augmented Intelligence with causal AI has the greatest potential to change industries and competition by how businesses operate.
Artificial intelligence (ai) will radically transform the way we do business in the future, and the way we live. That’s a strong statement, but i believe it’s true. Ai has many faces. As we are increasingly exposed to it, it’s important to understand what it can and can’t do and how companies can pivot wisely to this still evolving reality without overlooking the ethical, human and regulatory questions it raises.
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
Augmented intelligence as a response to the crisis of artificial intelligenceAlexander Ryzhov
The document discusses augmented intelligence as a pragmatic approach to artificial intelligence. It summarizes Prof. Alexander Ryzhov's presentation which outlined two main problems of augmented intelligence: (1) perception modeling and (2) perception-based computing. Formal definitions and solutions are provided for each problem. Frameworks and applications of augmented intelligence are presented, including for modeling complex processes, personalization, and new areas like healthcare and education. The presentation argues augmented intelligence can help solve practical problems by enhancing human expertise rather than attempting to replicate all of human intelligence.
The document provides an overview of artificial intelligence and its applications and risks in the life sciences domain. It discusses the history and recent advances of AI, including deep learning techniques. It then outlines several current and potential future applications of AI in life sciences areas like drug discovery, clinical trials, manufacturing and more. However, it also notes many open risks like data and model bias, adversarial attacks, lack of explainability and more. It argues that agencies are beginning to regulate AI for medical applications but that more work is needed to address risks and ensure appropriate, safe and effective use of AI in life sciences.
A brief overview of artificial intelligence (AI), followed by a few examples of practical use within small businesses, large enterprises, and nonprofits.
The document discusses artificial intelligence (AI) and machine learning. It provides examples of how machine learning works including showing the training process and making inferences from new data. It then discusses applications of AI like computer vision, natural language processing, reinforcement learning and more. It also discusses the growth and capabilities of AI over time as well as implications and applications in different industries.
3 steps to Creating Conversational AI with Everything Around UsJack C Crawford
Text chatbots and smart speakers have introduced new ways to search for information, get things done, and control a growing number of smart devices around us. These manifestations of intelligence have been limited to simple assistance, and have not yet reached the third stage of chatbot maturity described by Gartner. In this talk, we explore three steps to accelerate the move to engaging AI.
Augmented intelligence is new way forward ! Steve Ardire
1. Augmented Intelligence transcends current narrow AI and allows machines and humans to work together pervasively and competitively.
2. Augmented Intelligence provides faster insights into operations too complex for human minds alone by understanding them better.
3. Augmented Intelligence with causal AI has the greatest potential to change industries and competition by how businesses operate.
Artificial intelligence (ai) will radically transform the way we do business in the future, and the way we live. That’s a strong statement, but i believe it’s true. Ai has many faces. As we are increasingly exposed to it, it’s important to understand what it can and can’t do and how companies can pivot wisely to this still evolving reality without overlooking the ethical, human and regulatory questions it raises.
AI Basic, AI vs Machine Learning vs Deep Learning, AI Applications, Top 50 AI Game Changer Solutions, Advanced Analytics, Conversational Bots, Financial Services, Healthcare, Insurance, Manufacturing, Quality & Security, Retail, Social Impact, and Transportation & Logistics
Augmented intelligence as a response to the crisis of artificial intelligenceAlexander Ryzhov
The document discusses augmented intelligence as a pragmatic approach to artificial intelligence. It summarizes Prof. Alexander Ryzhov's presentation which outlined two main problems of augmented intelligence: (1) perception modeling and (2) perception-based computing. Formal definitions and solutions are provided for each problem. Frameworks and applications of augmented intelligence are presented, including for modeling complex processes, personalization, and new areas like healthcare and education. The presentation argues augmented intelligence can help solve practical problems by enhancing human expertise rather than attempting to replicate all of human intelligence.
Conversational AI versus AI Data ScienceRazorthink
Uncover the difference between a conversational AI and AI data science in this informative presentation, as well as how AI is being used on the Enterprise level.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
The State of Artificial Intelligence and What It Means for the PhilippinesThinking Machines
What consumer-ready applications of artificial intelligence are out there? What are the implications of semi-autonomous agents on Manila's BPO industry? Thinking Machines CEO and data scientist Stephanie Sy delivered this presentation on the current data science and AI landscape at the "Humans + Machines: Using Artificial Intelligence to Power Your People" conference held on February 19, 2016 at BGC, Taguig, Philippines.
Intelligence Augmentation - The Next-Gen AIMelanie Cook
Robotics and AI have integrated human and mechanical capabilities at work, with jobs lost and skills condensed to a keystroke. But human intelligence is far from obsolete.
With crowd-computing we have knowledge exchanges like Wiki, and real-time curated news. Semantic technology helps leaders to understand what is happening in the work place. But neurology shows that these leaders cannot make choices, and therefore take action, without emotion.
Augmented Intelligence takes human intuition and imagination, and combines it with AI’s ability to automate and scale, making the Intelligent Workplace hard to beat.
Digital Futures Webinar with Amaze CSO Rick Curtis Jan 2014amazeplc
Amaze's Chief Strategy Officer, Rick Curtis gives his thoughts on what will be hot in digital over the next 24 months and beyond. Rick discussed the following areas:
• The trends that will change the way businesses function and how we live our lives through 2014 and beyond
• What businesses should be thinking about as they compete in the continually evolving technological landscape
• What businesses need to be doing in order to remain competitive in a future being driven by Connectivity, Context and Collaboration.
To view a recording of this webinar, please click here:
https://vimeo.com/amazeplc/review/83694979/18dc31fd96
#AI is About to Reshape the Workplace & Your Organization's #DataStrategySteve Ardire
#AI is About to Reshape the Workplace & Your Organization's #DataStrategy https://shar.es/1C4oQI at #CDOVision http://cdovision2016.dataversity.net/ April 19 - 20 in San Diego
The document discusses the business case for applied artificial intelligence. It covers how AI can enhance enterprises and how to build successful AI ventures. Specifically, it notes that global AI business value is forecast to reach $3.9 trillion by 2022. It then discusses how to introduce AI in enterprises, including defining objectives and benefits. It also outlines challenges of AI introduction. Additionally, it provides a framework for successful AI startups with factors around value creation, implementation, and competitive positioning. The document concludes by discussing implementation aspects like machine learning canvases and technical debts, as well as ethical considerations around issues like bias, privacy, and accountability.
1) The document discusses how AI is impacting various industries and the future of work.
2) Machines are able to process vast amounts of information and handle complex processes better than humans.
3) Many jobs will be automated but AI will drive humans to perform higher-level cognitive work. Augmented intelligence where humans and machines work together will increase.
Artificial intelligence is promising new technologies but also hype that needs separating from reality. A discussion was held between executives in healthcare, machine learning and analytics with experts Hilary Mason and Sandy Allerheiligen. In the short term, AI automates tasks to save money and makes recommendations. In the long term, AI will transform industries like healthcare through medical imaging analysis and self-driving cars. Companies should start with problems not solutions, emphasize how AI augments not replaces humans, and engage skeptics to gain support.
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.
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It was presented at the joint session of ONE and the Digital Council. It covers some of the key trends and developments in AI including operationalizing AI, responsible AI and National AI Strategies
Augmenting human intelligence for future of work is the next disruptive innov...Steve Ardire
Steve Ardire
AI startup advisor 'force multiplier' aka 'The Merchant of Light'
https://www.forcemultipliersteveardire.com
https://www.linkedin.com/in/sardire/
Learn the workings of using intelligent machines for your processes using content-ready Artificial Intelligence PowerPoint Presentation Slides. Processes like learning, reasoning, self-correction, etc. are executed by artificial intelligent machines. Incorporate ready-made artificial intelligence PPT presentation templates and maximize the chance of achieving the organizational goals. This deck comprises of templates such as artificial intelligence objectives, artificial intelligence components, artificial intelligence statistics, artificial intelligence & investment by sector, artificial intelligence in various sectors, core areas of artificial intelligence, artificial intelligence value chain elements, artificial intelligence development phases, artificial intelligence approaches, machine learning (pattern based), machine learning description, machine learning process, machine learning use cases, and more. These templates are customizable. Edit color, text, icon and font size as per your need. Grab easy-to-understand artificial intelligence PowerPoint presentation slideshow and perform tasks associated with intelligent beings. Find solutions to the business problems without human intervention. Provide better products and services with the help of AI PPT templates. Click the download button to perform difficult tasks with ease using ready-made artificial intelligence PowerPoint presentation slides. Our Artificial Intelligence Powerpoint Presentation Slides team will alert you about changing demands. Their eyes and ears are always open.
Advanced AI Applications In EnterprisesAnandSRao1962
This document discusses advanced applications of AI in enterprises. It begins with an overview of AI and its abilities in sensing, thinking and acting. It then discusses four lenses for viewing enterprise AI: the business lens focusing on metrics and value chains, the intelligence lens on automated to autonomous intelligence, the data lens on structured vs. unstructured data, and the technology lens on techniques and tools. Several case studies are presented on using AI in pharmaceuticals, construction, automotive and financial advising. The document concludes with building and evolving an enterprise AI capability through developing an AI strategy and roadmap.
1) The document discusses AI technology and startups, outlining different types of AI technologies including deep learning, machine learning, and predictive APIs.
2) It notes that while many startups claim to use AI, few actually succeed in achieving what they promise due to lack of a viable business idea or talent.
3) The document advocates for closer collaboration between startups and universities, with universities conducting foundational research and startups commercializing outcomes.
The document is a newsletter curated by BootstrapLabs to share insights and innovations in artificial intelligence. It contains 60 issues from 2017 summarizing over 200 AI news articles. BootstrapLabs is a venture capital firm focused on applied artificial intelligence, and it uses this newsletter to share information with its community of over 40,000 executives, founders, researchers and investors interested in AI. The newsletter demonstrates how interest and investment in AI grew significantly in 2017, with areas like machine learning, deep learning, robotics, autonomous vehicles and more transforming industries.
Provides a brief introduction to Augmented Intelligence, and why it is important for developing and implementing business strategy in the 21st century.
The documents discuss the balance between AI and human workers. By 2021, AI assistants are forecast to handle 85% of customer service queries at just 10% of the cost of live agents. However, humans still provide skills like empathy, ethics and complex decision making that AI cannot replace. When used as augmentation rather than replacement, AI can help humans perform tasks faster and improve outcomes. An experiment found that including AI bots in a coordination game improved overall human performance, particularly during difficult tasks. For the future, organizations must view digital transformation as both a technology and people journey to create new jobs and reskill employees as roles evolve with new technologies.
This document summarizes a presentation by PwC on artificial intelligence and its applications and risks in the legal services industry. The presentation covers how AI can be used for tasks like legal research, e-discovery, contracts management, and compliance. It also discusses challenges of AI adoption like data and tool issues. Risks of AI like bias, lack of explainability, and job disruption are examined. The document concludes with a proposed breakout session for the event attendees to analyze which legal tasks could be automated or augmented with AI.
Artificial intelligence (AI) is the field of computer science that develops machines or software with human-like intelligence. AI can perform tasks like humans or even better than humans through activities like speech recognition, decision making, and translation. There are two main categories of AI: narrow AI, which is dedicated to a specific task, and strong/general AI, which does not currently exist but is being researched to allow machines to think like humans through their own intelligence and self-awareness. AI has many applications across industries like healthcare, transportation, education, and more. The evolution of AI began in the 1940s and important milestones include the invention of the Turing test in 1950, the development of machine learning in the 1950
Artificial intelligence (AI) is the field of computer science that develops machines or software with human-like intelligence. There are two types of AI: narrow AI, which is limited to specific tasks, and strong AI, which would have general human-level intelligence. AI is being applied in many areas including healthcare, transportation, education, and more. Some key developments in AI history include the invention of the Turing test in 1950 to measure machine intelligence, IBM's Deep Blue beating the chess champion in 1997, and IBM Watson winning Jeopardy in 2011. Cognitive computing systems like Watson are aimed at simulating human thought processes.
Conversational AI versus AI Data ScienceRazorthink
Uncover the difference between a conversational AI and AI data science in this informative presentation, as well as how AI is being used on the Enterprise level.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
The State of Artificial Intelligence and What It Means for the PhilippinesThinking Machines
What consumer-ready applications of artificial intelligence are out there? What are the implications of semi-autonomous agents on Manila's BPO industry? Thinking Machines CEO and data scientist Stephanie Sy delivered this presentation on the current data science and AI landscape at the "Humans + Machines: Using Artificial Intelligence to Power Your People" conference held on February 19, 2016 at BGC, Taguig, Philippines.
Intelligence Augmentation - The Next-Gen AIMelanie Cook
Robotics and AI have integrated human and mechanical capabilities at work, with jobs lost and skills condensed to a keystroke. But human intelligence is far from obsolete.
With crowd-computing we have knowledge exchanges like Wiki, and real-time curated news. Semantic technology helps leaders to understand what is happening in the work place. But neurology shows that these leaders cannot make choices, and therefore take action, without emotion.
Augmented Intelligence takes human intuition and imagination, and combines it with AI’s ability to automate and scale, making the Intelligent Workplace hard to beat.
Digital Futures Webinar with Amaze CSO Rick Curtis Jan 2014amazeplc
Amaze's Chief Strategy Officer, Rick Curtis gives his thoughts on what will be hot in digital over the next 24 months and beyond. Rick discussed the following areas:
• The trends that will change the way businesses function and how we live our lives through 2014 and beyond
• What businesses should be thinking about as they compete in the continually evolving technological landscape
• What businesses need to be doing in order to remain competitive in a future being driven by Connectivity, Context and Collaboration.
To view a recording of this webinar, please click here:
https://vimeo.com/amazeplc/review/83694979/18dc31fd96
#AI is About to Reshape the Workplace & Your Organization's #DataStrategySteve Ardire
#AI is About to Reshape the Workplace & Your Organization's #DataStrategy https://shar.es/1C4oQI at #CDOVision http://cdovision2016.dataversity.net/ April 19 - 20 in San Diego
The document discusses the business case for applied artificial intelligence. It covers how AI can enhance enterprises and how to build successful AI ventures. Specifically, it notes that global AI business value is forecast to reach $3.9 trillion by 2022. It then discusses how to introduce AI in enterprises, including defining objectives and benefits. It also outlines challenges of AI introduction. Additionally, it provides a framework for successful AI startups with factors around value creation, implementation, and competitive positioning. The document concludes by discussing implementation aspects like machine learning canvases and technical debts, as well as ethical considerations around issues like bias, privacy, and accountability.
1) The document discusses how AI is impacting various industries and the future of work.
2) Machines are able to process vast amounts of information and handle complex processes better than humans.
3) Many jobs will be automated but AI will drive humans to perform higher-level cognitive work. Augmented intelligence where humans and machines work together will increase.
Artificial intelligence is promising new technologies but also hype that needs separating from reality. A discussion was held between executives in healthcare, machine learning and analytics with experts Hilary Mason and Sandy Allerheiligen. In the short term, AI automates tasks to save money and makes recommendations. In the long term, AI will transform industries like healthcare through medical imaging analysis and self-driving cars. Companies should start with problems not solutions, emphasize how AI augments not replaces humans, and engage skeptics to gain support.
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.
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It was presented at the joint session of ONE and the Digital Council. It covers some of the key trends and developments in AI including operationalizing AI, responsible AI and National AI Strategies
Augmenting human intelligence for future of work is the next disruptive innov...Steve Ardire
Steve Ardire
AI startup advisor 'force multiplier' aka 'The Merchant of Light'
https://www.forcemultipliersteveardire.com
https://www.linkedin.com/in/sardire/
Learn the workings of using intelligent machines for your processes using content-ready Artificial Intelligence PowerPoint Presentation Slides. Processes like learning, reasoning, self-correction, etc. are executed by artificial intelligent machines. Incorporate ready-made artificial intelligence PPT presentation templates and maximize the chance of achieving the organizational goals. This deck comprises of templates such as artificial intelligence objectives, artificial intelligence components, artificial intelligence statistics, artificial intelligence & investment by sector, artificial intelligence in various sectors, core areas of artificial intelligence, artificial intelligence value chain elements, artificial intelligence development phases, artificial intelligence approaches, machine learning (pattern based), machine learning description, machine learning process, machine learning use cases, and more. These templates are customizable. Edit color, text, icon and font size as per your need. Grab easy-to-understand artificial intelligence PowerPoint presentation slideshow and perform tasks associated with intelligent beings. Find solutions to the business problems without human intervention. Provide better products and services with the help of AI PPT templates. Click the download button to perform difficult tasks with ease using ready-made artificial intelligence PowerPoint presentation slides. Our Artificial Intelligence Powerpoint Presentation Slides team will alert you about changing demands. Their eyes and ears are always open.
Advanced AI Applications In EnterprisesAnandSRao1962
This document discusses advanced applications of AI in enterprises. It begins with an overview of AI and its abilities in sensing, thinking and acting. It then discusses four lenses for viewing enterprise AI: the business lens focusing on metrics and value chains, the intelligence lens on automated to autonomous intelligence, the data lens on structured vs. unstructured data, and the technology lens on techniques and tools. Several case studies are presented on using AI in pharmaceuticals, construction, automotive and financial advising. The document concludes with building and evolving an enterprise AI capability through developing an AI strategy and roadmap.
1) The document discusses AI technology and startups, outlining different types of AI technologies including deep learning, machine learning, and predictive APIs.
2) It notes that while many startups claim to use AI, few actually succeed in achieving what they promise due to lack of a viable business idea or talent.
3) The document advocates for closer collaboration between startups and universities, with universities conducting foundational research and startups commercializing outcomes.
The document is a newsletter curated by BootstrapLabs to share insights and innovations in artificial intelligence. It contains 60 issues from 2017 summarizing over 200 AI news articles. BootstrapLabs is a venture capital firm focused on applied artificial intelligence, and it uses this newsletter to share information with its community of over 40,000 executives, founders, researchers and investors interested in AI. The newsletter demonstrates how interest and investment in AI grew significantly in 2017, with areas like machine learning, deep learning, robotics, autonomous vehicles and more transforming industries.
Provides a brief introduction to Augmented Intelligence, and why it is important for developing and implementing business strategy in the 21st century.
The documents discuss the balance between AI and human workers. By 2021, AI assistants are forecast to handle 85% of customer service queries at just 10% of the cost of live agents. However, humans still provide skills like empathy, ethics and complex decision making that AI cannot replace. When used as augmentation rather than replacement, AI can help humans perform tasks faster and improve outcomes. An experiment found that including AI bots in a coordination game improved overall human performance, particularly during difficult tasks. For the future, organizations must view digital transformation as both a technology and people journey to create new jobs and reskill employees as roles evolve with new technologies.
This document summarizes a presentation by PwC on artificial intelligence and its applications and risks in the legal services industry. The presentation covers how AI can be used for tasks like legal research, e-discovery, contracts management, and compliance. It also discusses challenges of AI adoption like data and tool issues. Risks of AI like bias, lack of explainability, and job disruption are examined. The document concludes with a proposed breakout session for the event attendees to analyze which legal tasks could be automated or augmented with AI.
Artificial intelligence (AI) is the field of computer science that develops machines or software with human-like intelligence. AI can perform tasks like humans or even better than humans through activities like speech recognition, decision making, and translation. There are two main categories of AI: narrow AI, which is dedicated to a specific task, and strong/general AI, which does not currently exist but is being researched to allow machines to think like humans through their own intelligence and self-awareness. AI has many applications across industries like healthcare, transportation, education, and more. The evolution of AI began in the 1940s and important milestones include the invention of the Turing test in 1950, the development of machine learning in the 1950
Artificial intelligence (AI) is the field of computer science that develops machines or software with human-like intelligence. There are two types of AI: narrow AI, which is limited to specific tasks, and strong AI, which would have general human-level intelligence. AI is being applied in many areas including healthcare, transportation, education, and more. Some key developments in AI history include the invention of the Turing test in 1950 to measure machine intelligence, IBM's Deep Blue beating the chess champion in 1997, and IBM Watson winning Jeopardy in 2011. Cognitive computing systems like Watson are aimed at simulating human thought processes.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and act like humans. The goal of AI is to develop computer systems capable of performing tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, learning from experience, and making decisions.
There are various types of AI, including narrow AI and general AI. Narrow AI, also known as weak AI, is designed to perform specific tasks or solve particular problems, such as speech recognition, image recognition, or playing chess. General AI, also known as strong AI or artificial general intelligence (AGI), refers to AI systems that possess the ability to understand, learn, and apply knowledge across a wide range of tasks, similar to human intelligence.
AI algorithms and techniques can be categorized into several subfields, including:
1. Machine Learning: Machine learning is a subset of AI that focuses on the development of algorithms that enable computers to learn from data and improve their performance over time without being explicitly programmed. This includes supervised learning, unsupervised learning, and reinforcement learning.
2. Deep Learning: Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to model complex patterns in large amounts of data. Deep learning has been particularly successful in tasks such as image recognition, speech recognition, and natural language processing.
3. Natural Language Processing (NLP): NLP is a field of AI that focuses on the interaction between computers and humans through natural language. NLP enables computers to understand, interpret, and generate human language, allowing for applications such as language translation, sentiment analysis, and chatbots.
4. Computer Vision: Computer vision is a field of AI that enables computers to interpret and understand visual information from the real world, such as images and videos. Computer vision algorithms can be used for tasks such as object detection, image classification, and facial recognition.
5. Robotics: Robotics combines AI with mechanical engineering to create machines that can perform tasks autonomously or semi-autonomously. AI-powered robots are used in various industries, including manufacturing, healthcare, and agriculture, to automate repetitive tasks and improve efficiency.
AI has a wide range of applications across various industries, including healthcare, finance, transportation, retail, and entertainment. Some examples of AI applications include virtual assistants like Siri and Alexa, autonomous vehicles, recommendation systems like those used by Netflix and Amazon, and medical diagnosis systems.
While AI has the potential to bring about significant benefits and advancements, it also raises ethical and societal concerns, such as job displacement, algorithmic bias, privacy issues, and the potential for misuse or abuse of AI te
This document provides an overview of artificial intelligence (AI), including its history, applications, and types. It discusses early milestones in AI development as well as modern advances in deep learning, big data, and efforts to create artificial general intelligence. The document also examines what comprises AI and how intelligent agents are structured, defined in terms of their perception, environment, actuators, and sensors (PEAS). It explores rational agents and the Turing test as a way to evaluate machine intelligence.
Artificial intelligence and machine learning are discussed. AI is defined as making computers intelligent like humans through understanding, reasoning, planning, communication and perception. Machine learning is a subset of AI that allows machines to learn from experience without being explicitly programmed. The document provides background on AI and ML, including definitions, history, and discussions of intelligence and applications.
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.
AI - How Artificial Intelligence Will Impact Your BusinessPaul Barter
AI - How Artificial Intelligence Will Impact Your Business
DESCRIPTION:
AI (Artificial Intelligence) has the potential to radically transform employment, productivity and society. Business decision makers need to mitigate underlying risks and invest appropriately to drive future competitive advantage.
The document discusses artificial intelligence (AI) from several perspectives. It defines AI as making computers that think like humans or act intelligently. It outlines key areas of AI research such as machine learning, robotics, and natural language processing. It also discusses different definitions and approaches to AI, including systems that act rationally by making optimal decisions, systems that think rationally using logic, and systems that think or act like humans. A brief history of AI research from the 1950s to the 1990s is also provided, covering milestones and challenges in the field.
1. Artificial Intelligence aims to understand and build intelligent systems by studying human intelligence and behavior.
2. There are different approaches to defining AI such as thinking rationally, acting rationally, thinking humanly, and acting humanly.
3. The foundations of AI draw from various fields including philosophy, mathematics, economics, neuroscience, psychology, and computer engineering.
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.
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.
Artificial intelligence (AI) is the study of computer systems that attempt to model and apply human intelligence. Early pioneers like Alan Turing asked if machines could think in the 1950s, and the field of AI was established in a 1956 workshop. Modern AI has made advances in digital assistants like Siri, robotics, deep learning, and self-driving cars. However, challenges remain around computing power, intuitive thinking, and human-level judgment. The future of AI may include improved healthcare, exploration, and automation, but risks include unemployment, diminished human abilities, and potential misuse if it falls into the wrong hands.
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...InnoTech
Artificial intelligence and sensor networks may now be poised to disrupt various industries and jobs. Recent advances in algorithms, sensors, data collection, mobile technology, and robotics have increased concerns about the potential threats of artificial superintelligence ending humanity. The rapid changes in science and technology could significantly impact jobs in the coming decades as AI and automation replace many human roles.
Webinar on AI in IoT applications KCG Connect Alumni Digital Series by RajkumarRajkumar R
The Artificial Intelligence in IoT Applications. Take your first step towards a bright future with our renowned alumnus,
Prof R. Raj Kumar on AI for IoT Applications.
He is an award wining author of the book, ‘India 2030’.
To get access to the webinar kindly contact your respective department heads.
Looking forward to having you on the webinar.
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#KCGCollege #KCGStudentlife #KCGConnect #Education #EmergingTechnologies #ArtificialIntelligence #IoT #MachineLearning #BlockChain #ElectricVehicle #QuantumTechnology #CAD
THE FUTURE OF ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON SOCIETY.pdfSyedZakirHussian
Artificial Intelligence (AI) is the talk of the town! It’s no longer just the stuff of science fiction, but a rapidly evolving technology that’s changing our world in ways we couldn’t have imagined just a few short years ago. From Siri and Alexa to self-driving cars and smart homes, AI is already playing a significant role in our daily lives. But what does the future hold for this cutting-edge technology? How will it continue to impact our society?
In this blog, we’ll be exploring the future of Artificial Intelligence and its impact on society. From advancements in healthcare and employment to privacy and security concerns, we’ll take a deep dive into the many ways AI is shaping our world. And, because we believe that life is too short to be serious all the time, we’ll also sprinkle in a bit of humor to keep things interesting. So, buckle up, and let’s go on a journey to the future!
The advancements in AI are nothing short of remarkable, and it’s exciting to think about what the future holds. But it’s important to remember that with great power comes great responsibility. As we move forward with AI, it’s essential to consider the potential impact on society and to develop responsible practices to ensure that this technology is used for the greater good. We hope this blog will provide a valuable resource for those interested in learning more about the future of Artificial Intelligence and its impact on society.
The document provides an overview of artificial intelligence (AI), including:
- Definitions of AI and a brief history of the field from early computers through modern machine learning advances.
- Descriptions of how AI works using artificial neural networks and logic-based systems, as well as examples like expert systems and current applications in areas such as personal assistants, robotics, and computer vision.
- A discussion of the current status and future potential of AI, along with challenges for developing true human-level intelligence and comparisons between human and artificial forms of intelligence.
Power point presentation on basic of Artificial Intelligent Vishal Singh
The document provides an overview of artificial intelligence (AI). It defines AI as the study of computer systems that attempt to model human intelligence. The early history of AI is discussed, noting Alan Turing's 1950 paper that asked if machines can think. The current status of AI includes intelligent personal assistants on mobile devices, as well as applications in video games, navigation, robotics, and deep learning. Key challenges for AI are computing power, intuitive thinking, and judgment. The future of AI is seen in self-driving cars, improved healthcare, and new areas of exploration.
This presentation was after a showing of Robot & Frank and Livermore, CA public library. The point of the session was to explore AI basics and discuss the potential of the movie coming true.
Company Valuation webinar series - Tuesday, 4 June 2024FelixPerez547899
This session provided an update as to the latest valuation data in the UK and then delved into a discussion on the upcoming election and the impacts on valuation. We finished, as always with a Q&A
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
How are Lilac French Bulldogs Beauty Charming the World and Capturing Hearts....Lacey Max
“After being the most listed dog breed in the United States for 31
years in a row, the Labrador Retriever has dropped to second place
in the American Kennel Club's annual survey of the country's most
popular canines. The French Bulldog is the new top dog in the
United States as of 2022. The stylish puppy has ascended the
rankings in rapid time despite having health concerns and limited
color choices.”
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Brian Fitzsimmons on the Business Strategy and Content Flywheel of Barstool S...Neil Horowitz
On episode 272 of the Digital and Social Media Sports Podcast, Neil chatted with Brian Fitzsimmons, Director of Licensing and Business Development for Barstool Sports.
What follows is a collection of snippets from the podcast. To hear the full interview and more, check out the podcast on all podcast platforms and at www.dsmsports.net
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
Easily Verify Compliance and Security with Binance KYCAny kyc Account
Use our simple KYC verification guide to make sure your Binance account is safe and compliant. Discover the fundamentals, appreciate the significance of KYC, and trade on one of the biggest cryptocurrency exchanges with confidence.
The APCO Geopolitical Radar - Q3 2024 The Global Operating Environment for Bu...APCO
The Radar reflects input from APCO’s teams located around the world. It distils a host of interconnected events and trends into insights to inform operational and strategic decisions. Issues covered in this edition include:
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
❼❷⓿❺❻❷❽❷❼❽ Dpboss Matka Result Satta Matka Guessing Satta Fix jodi Kalyan Final ank Satta Matka Dpbos Final ank Satta Matta Matka 143 Kalyan Matka Guessing Final Matka Final ank Today Matka 420 Satta Batta Satta 143 Kalyan Chart Main Bazar Chart vip Matka Guessing Dpboss 143 Guessing Kalyan night
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This PowerPoint compilation offers a comprehensive overview of 20 leading innovation management frameworks and methodologies, selected for their broad applicability across various industries and organizational contexts. These frameworks are valuable resources for a wide range of users, including business professionals, educators, and consultants.
Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
This compilation is ideal for anyone looking to enhance their understanding of innovation management and drive meaningful change within their organization. Whether you aim to improve product development processes, enhance customer experiences, or drive digital transformation, these frameworks offer valuable insights and tools to help you achieve your goals.
INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
2. The goal of this lecture
• General trend on intelligence
• What is intelligence?
• How far ultimately AI can reach?
• AI will take over human?
• What have been studied so far?
• What is happening now,
• Where are we now?
• What would happen in 10 years?
• How business could change?
Don’t confuse those two!
HAL
I, Robot
3. Disclaimer
• Predicting future is not possible
Our universe, Our life
Never repeat
Artificial life
You can not repeat process
Our universe 1.38*10^10 year old, would probably exist 10^10^26??
If it were 1 years, Christ, Budda, Mohamed were born
last few seconds, our knowledge just expand in our universe quite recently
4. What is intelligence?
• Definitions
• Individuals differ from one another in their ability to understand complex ideas
to adapt effectively to the environment to learn from experience, to engage in
various forms of reasoning to overcome obstacle by taking thought. (American
Psychological Association task force on Intelligence)
• They are not quantitative difference, they are qualitative difference
Intelligence person could see stuff normal people don’t
• F = T 𝛻 S, Drive the system to maximize future freedom of action
“Intelligence should be viewed as a physical process that tries to maximize
future freedom action and avoids the constraints its own future.” PRL 110
168702 (2013) Intelligence explored because human invents tools and start
using them. AI could be last tool human will invent
5. Intelligence
• They are not quantitative difference, they are qualitative difference
• They see stuff we don’t János Mattis-Teutsch
Kouhei Uchimura
Richard Feynman
6. Proposition
• Our brain activities can be realized by computer
-> There is no reason we can’t simulate thinking, recognition, memory,
feelings
Neural network
7. Life is advancing
• Biological
• Evolve hardware
• Evolve software
• Cultural • Technological
• Evolve hardware
• Design software
• Design hardware
• Design software
8. 3 components of our cognitive activities
• What do we think
• How you feel
• What do you believe
-
Pathos
Emotions/Values
Ethos
Credibility/Trust
Logos
Logic/Reason/Proof
Aristotle (350 B.C.)
9. Immanuel Kant (1724-1804?)
• Critiques of pure reason
• What do we think
• Metaphycis
• Critiques of judgement
• How you feel
• Ascetics, theory of beauty
• Critiques of practical reason
• What do you believe
• Ethics
Judgement Practical
Pure reason
Immanuel Kant
(1724-1804)
10. Artificial intellingence can’t believe
• They could potentially think and feel but not believe
• Our cognition is active (Construcuralism)
• Our understanding is based on experience and perception, we
can extend out cognitive activity with metaphysical activities.
• Our understanding = unification of our judgement on things =
not necessary true at all.
• While we have a lot to answer our cognitive activities.
Metaphysical activities here
Hardest for computer.
Sensing
/Observation
Understanding
/Meaning
Integration Judgement/Execution
11. What will bottlenecks be
Design goals Understanding Structure Proposition Execution
It does not have will Sensors are not developed like humans
Needs data
It can not have questions
Cant design framework
No sense of common sense
Can not order human
12. It is very far.
AI on economy Human level AI Superintelligence
Who is in charge?
Humans
Cyborgs
AI
How will humans treated?
Well
Replaced
Badly
14. What is happening now?
• 1st Reasoning (1956- 1960-)
• 10 years after 1st computer
• Decision making tree,Game theory
• Chess, Go
• 2nd Expert system (1980-)
• 5th generation computer (Japan)
• Dark age after this era
• 3rd Machine learning(2010 -)
• Web + Big data
• Computation power
• Breakthrough with Deep learning
3G AI
≠
neural network
15. What is happening now?
• Recognition
• Information ……………..Web search, movie, music, picture, voice.
• Voice, picture, movie …….. Feeling, cancer detections, movie editing
• Detecting anomaly …….. Fraud, suspicious person or trade, disaster
• Prediction
• Number ………….. Sales, economic parameters, election, cancer, credit
• Demands ………… order, users preferences,
• Matching ……. Advertising, recommendations,
• Execution
• Presentation ………… Summary, Writing, Translations, Composition, Drawing
• Design …………………. Chart, Logo, Site Design, Medicine, Architecture, Cooking
• Optimization ………... Game, Transportation, Place for new stores, medical
• Automation ………….. Q&A, Mobile, car, SEO, Cooking, operations
16. It is very far.
Imaging Multimodal Planning/action Abstraction Language Understanding
Understand language
Acquire knowledge through
language
Understand feelings
2030??
2020??
17. We enter all connected age
Telecommunication
• 1G phone
• 2G mail
• 3G i-mode
• 4G smartphone
• 5G ??? <- wearable? IoT
Business
• B-B
• B-B -> B-C
• B-C
• B-C, C-C
• B-B-C, C-B-C
How the system could change with post-smarthone?
How the money flow changes by that?
Computer
• IBM
• Microsoft
• Google
• Apple, Facebook,
Amazon
• ??
18. 4 Key technologies backed by 5G
• IoT
• Smartphone, wearable devices
Smart home, driverless car
• Blockchain
• ANNGOUKA, Consensus algorism
P2P, Distributed Ledger Technology
• Cloud
• Amazon AWS, IBM, Microsoft
• AI (3rd generations)
• Analyses and uses data
Collect data Store data
Manage data Analyse data
19. What are jobs??
• Job is about solving problem
• So you need to find problem which people or technology can’t solve easily
• Job is about entreating people
• AI can’t do anything meaningless
20. Job wont be gone but parts of job are automated
• Medical
• Legal system
• Office
• IT
• Publishing
• Sales
• Mobile
• Real-estate
• Security
Ex.)
21. Entertainment wont be gone but part of they are
connected, depend, and attended
• Sports
• Show
• Fashion
• Music
• Events
Ex.)
22. We enter imaginary dimensions
• We should play more in imaginary dimensions
Re (実数)
Im (虚数)
Centralized
Decentralized
Distributed
Problem Design
Mass
production
Product
Problem AI
A product Solution
problem -> theory ->
experiment -> solution
Problem -> data -> AI ->
solution -> theory
Problem solving
Production
Open and close
Grab
23. We enter imaginary dimensions
• We should play more in imaginary dimensions
• But remember the 4 questions, to evaluate business
What value do they provide?To whom?
How do they deliver? How do they make money?