Cognitive computing is the simulation of human thought processes in a computerized model. It's goal is to create automated non-organic systems that are capable of solving real problems (business and personal) without requiring
human assistance.
This document discusses the role of design in societal transitions to more sustainable futures. It addresses the complex temporal nature of "systems problems" that exist at multiple scales within social and environmental systems. The authors argue that designers need to understand how to work iteratively over long time horizons at multiple scales. They discuss concepts like temporal complexity, transition design, and contingencies to emphasize the radical contingency of our worlds and the need to design within transitions rather than seeking resolution or endpoints. The focus is on evaluating situations and rapidly adapting to changing conditions to profit from what is harmful to opponents or advantageous at a given time.
Results of survey distributed to participants in the organizational design elective at the Frankfurt Institute of Finance & Management, Spring 2018. See https://www.organizationdesign.net for background information
Introduction to Cognitive Computing the science behind and use of IBM WatsonSubhendu Dey
The lecture was given in a Cognitive and Analytics workshop at Indian Institute of Management. Topics covered was -
1) Understanding Natural Language Processing, Classification, Watson & its modules
2) Industry applications of Cognitive Computing
3) Understanding Cognitive Architecture
4) Understanding the disciplines / tools being used in Cognitive Science
This document summarizes a report on cognitive computing trends from IBM. It discusses how [1] cognitive computing is already in use with increased adoption by early adopters and startups, [2] various technologies like machine learning, natural language processing, and predictive analytics will continue to advance, and [3] leading enterprises are aggressively pursuing cognitive solutions to address industries like healthcare, banking, and manufacturing. It also notes challenges to further adoption like demonstrating clear ROI and use cases.
The FIRM & IBM Event : How cognitive computing is transforming hr and the emp...Emma Mirrington
Cognitive computing can help transform key areas of HR by improving decision making and expanding human expertise. A study found that CEOs and CHROs believe cognitive solutions can address talent challenges, but many are uncertain how to apply them. Research also found that employees are willing to receive guidance from cognitive systems in certain situations, such as for complex or frequent problems. Three key areas that are well-suited for cognitive solutions are talent acquisition and onboarding, talent development, and HR operations. Cognitive systems can help improve matching candidates to jobs, providing personalized learning recommendations, and enabling more efficient HR services.
Cognitive computing for academics 20170301 v5ISSIP
Cognitive computing is the study of how people and machines can think better together. It is not about machines doing all the thinking for humans. Done correctly, cognitive computing can help people become better thinkers and decision makers. It exercises the mind and makes it stronger. Cognitive computing studies how humans and AI systems can collaborate on tasks like transcribing speech, recognizing images, and understanding text. The document discusses how different academic fields study thinking, including psychology (people), artificial intelligence (machines), cognitive science (both people and machines), and cognitive computing (people and machines thinking together).
The Intelligent Enterprise: How Companies are Using Cognitive Computing to Dr...Susanne Hupfer, Ph.D.
Presented by Susanne Hupfer and Nancy Pearson at IBM World of Watson Conference, Oct. 2016.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
This document discusses the role of design in societal transitions to more sustainable futures. It addresses the complex temporal nature of "systems problems" that exist at multiple scales within social and environmental systems. The authors argue that designers need to understand how to work iteratively over long time horizons at multiple scales. They discuss concepts like temporal complexity, transition design, and contingencies to emphasize the radical contingency of our worlds and the need to design within transitions rather than seeking resolution or endpoints. The focus is on evaluating situations and rapidly adapting to changing conditions to profit from what is harmful to opponents or advantageous at a given time.
Results of survey distributed to participants in the organizational design elective at the Frankfurt Institute of Finance & Management, Spring 2018. See https://www.organizationdesign.net for background information
Introduction to Cognitive Computing the science behind and use of IBM WatsonSubhendu Dey
The lecture was given in a Cognitive and Analytics workshop at Indian Institute of Management. Topics covered was -
1) Understanding Natural Language Processing, Classification, Watson & its modules
2) Industry applications of Cognitive Computing
3) Understanding Cognitive Architecture
4) Understanding the disciplines / tools being used in Cognitive Science
This document summarizes a report on cognitive computing trends from IBM. It discusses how [1] cognitive computing is already in use with increased adoption by early adopters and startups, [2] various technologies like machine learning, natural language processing, and predictive analytics will continue to advance, and [3] leading enterprises are aggressively pursuing cognitive solutions to address industries like healthcare, banking, and manufacturing. It also notes challenges to further adoption like demonstrating clear ROI and use cases.
The FIRM & IBM Event : How cognitive computing is transforming hr and the emp...Emma Mirrington
Cognitive computing can help transform key areas of HR by improving decision making and expanding human expertise. A study found that CEOs and CHROs believe cognitive solutions can address talent challenges, but many are uncertain how to apply them. Research also found that employees are willing to receive guidance from cognitive systems in certain situations, such as for complex or frequent problems. Three key areas that are well-suited for cognitive solutions are talent acquisition and onboarding, talent development, and HR operations. Cognitive systems can help improve matching candidates to jobs, providing personalized learning recommendations, and enabling more efficient HR services.
Cognitive computing for academics 20170301 v5ISSIP
Cognitive computing is the study of how people and machines can think better together. It is not about machines doing all the thinking for humans. Done correctly, cognitive computing can help people become better thinkers and decision makers. It exercises the mind and makes it stronger. Cognitive computing studies how humans and AI systems can collaborate on tasks like transcribing speech, recognizing images, and understanding text. The document discusses how different academic fields study thinking, including psychology (people), artificial intelligence (machines), cognitive science (both people and machines), and cognitive computing (people and machines thinking together).
The Intelligent Enterprise: How Companies are Using Cognitive Computing to Dr...Susanne Hupfer, Ph.D.
Presented by Susanne Hupfer and Nancy Pearson at IBM World of Watson Conference, Oct. 2016.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
Understanding the New World of Cognitive ComputingDATAVERSITY
Cognitive Computing is a rapidly developing technology that has reached practical application and implementation. So what is it? Do you need it? How can it benefit your business?
In this webinar a panel of experts in Cognitive Computing will discuss the technology, the current practical applications, and where this technology is going. The discussion will start with a review of a recent survey produced by DATAVERSITY on how Cognitive Computing is currently understood by your peers. The panel will also review many components of the technology including:
Cognitive Analytics
Machine Learning
Deep Learning
Reasoning
And next generation artificial intelligence (AI)
And get involved in the discussion with your own questions to present to the panel.
This document discusses cognitive computing. It begins with an introduction that defines cognition and cognitive computing. Cognitive computing aims to develop systems that can think and react like the human mind through a combination of neuroscience, supercomputing, and nanotechnology. The need for cognitive computing is that today's information is challenging to manage and current search engines are limited. An example provided is IBM's Watson, the first cognitive computer, which was able to answer questions in natural language and defeat human champions on Jeopardy. The document concludes by stating that cognitive systems will help make sense of complex information and create new industries through collaboration with human reasoning.
Graphs and Machine Learning have long been a focus for Franz Inc. and currently we are collaborating with a number of companies to deliver the ability to understand possible future events based on a company's internal as well as externally available data. By combining machine learning, semantic technologies, big data, graph databases and dynamic visualizations we will discuss the core components of a Cognitive Computing platform.
We discuss example Cognitive Computing platforms from Ecommerce, fraud detection and healthcare that combine structured/unstructured data, knowledge, linked open data, predictive analytics, and machine learning to enhance corporate decision making.
(1) The building blocks are getting better for the next generation of makers
(2) T-shaped talent is what IBM looks for, and people with lots of ideas! - Whole New Engineer Related
(3) The AI building blocks are getting better too
(4) The next generation can build an amazing world
(5) However, they need to wrestle with ethical decisions - and Whole New Engineer topic, for sure
(6) Q&A
The skills implications of Cognitive ComputingDale Lane
1) Cognitive computing systems learn from interactions with people and data to perform tasks like thinking and making complex decisions with large amounts of information.
2) These systems will change how people interact with technology and require new skills like designing systems that can learn to solve problems and access necessary data.
3) Cognitive computing will be highly disruptive and enable new combinations of human and computer intelligence beyond what either could do alone.
Faith's talk at Barcamp Southampton 2016
She made a chat bot that can answer questions about owls, and used that for most of her presentation. Here are some slides we used to talk about why she chose owls, and how she made the bot.
Cognitive Computing by Professor Gordon Pipadiannepatricia
Professor Dr. Gordon Pipa, University of Osnabrueck, Germany is making this presentation for the Cognitive Systems Institute Speaker Series on May 26, 2016.
SmartData Webinar: Commercial Cognitive Computing -- How to choose and build ...DATAVERSITY
This document provides an overview of cognitive computing and how to build a first cognitive computing application. It discusses fundamentals like natural cognitive processes, approaches to machine learning, and perception. It also outlines the cognitive computing technology ecosystem, including machine learning platforms, input/output technologies, infrastructure providers, and analytics/visualization tools. Finally, it offers advice on first steps like identifying a domain and data sources, choosing a machine learning model, and building a virtuous learning cycle.
The document discusses how open-source intelligence (OSINT) can be used to analyze the Twitter account of Donald Trump and identify that there are two distinct personas tweeting - one from Trump himself using an Android phone in the mornings that tweets more negatively, and another "cutout" persona using an iPhone that tweets later with more positive language and additional features like links and pictures. The analysis of sentiment, emotion, and linguistic structures of the tweets over time indicates the two personas have distinct profiles, and that the account overall has been tweeting more negatively as Trump's presidency progressed.
Applying cognitive computing to business operations, transforming front to ba...HfS Research
Ambitious business leaders are reinventing their enterprises digitally with creative strategies, products and customer experiences. Emerging cognitive solutions have the ability to impact business processes in entirely new ways through autonomous decision making and insightful human engagement. However, many business leaders still view cognitive computing as tomorrow’s potential, not necessarily today’s.
In this webinar, experts from HfS Research, IBM, and Waterfund discuss how cognitive platform based solutions and a design-thinking led approach allow for delivering a personalized, end-to-end frictionless experience.
Watch and learn:
Getting real with Cognitive. Real enterprise case examples of cognitive solutions that transform the way Finance, HR and Procurement services operate
How cognitive capabilities and solutions are enhancing IBM clients' BPO services
The role of service delivery to achieve the Intelligent OneOffice
How the next generation of Service Delivery can bring about a frictionless front to back office transformation
Watch the webinar: http://www.hfsresearch.com/pov/hfs-webinar-august-4
The cognitive advantage: Insights from early adopters on driving business valueSusanne Hupfer, Ph.D.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
IBM faces three main dilemmas in managing innovation: balancing bottom-up and top-down approaches; focusing on long-term research versus short-term success; and determining how open to be with innovation versus developing proprietary intellectual property. Successfully navigating these tensions is key to innovation success. The document discusses IBM's efforts to balance these dilemmas through collaborative open innovation with partners while still generating patents and intellectual property.
Manoj Saxena TED talk - Bending the Knowledge Curve with Cognitive ComputingManoj Saxena
Watson Solutions General Manager Manoj Saxena's TED talk on Bending the Knowledge Curve: "We have only just begun a new era of Cognitive Computing which will dramatically influence our own evolution" http://bit.ly/13cyAGX
Utilizing Social Health Websites for Cognitive Computing and Clinical Decisio...CrowdTruth
Crowdsourced annotations data offers cognitive computing systems insights in lay semantics. This is especially important in health care, where medical terminology is often not aligned with patients `lay' language. However, the general crowd often has limited medical knowledge. Therefore this research investigated the opportunities of social health websites for obtaining ground truth annotations data for cognitive computing systems including clinical decision support systems. By identifying these websites and analyzing their data, it offers a starting point for the future utilization of user-generated health content for cognitive systems. However, the opportunities of social health data are currently limited by various legal regulations. Therefore this paper also dwells on the legal aspects of implementing social health data for cognitive computing systems.
The Cognitive Edge: A New Competitive AdvantageIDC Italy
Sintesi dell'intervento di Giancarlo Vercellino, Research & Consulting Manager di IDC Italia, all'evento Insightful Business 2017: From Data to Business Discovery – Il Cognitive Computing come strumento per il Business, svoltosi a Milano il 15 marzo 2017
The document summarizes Peter Diamandis' top 10 tech trends of 2016 that are transforming humanity. The trends include: 1) Hyper-connecting the world through initiatives like Google's solar drones and satellite constellations from OneWeb and SpaceX. 2) Solar and renewable energy becoming cheaper than coal. 3) Progress in combating diseases like cancer through immunotherapy and CRISPR gene editing. 4) Advances in extending human life through research on aging and stem cells. 5) Successes with stem cells in growing human eyes and helping stroke and paralysis victims. 6) Developments in autonomous vehicles by companies like Google, Tesla, and Uber.
The document discusses DIVE+, a tool that aims to address the issues of audiences feeling disconnected from the massive amounts of digital cultural content available by bringing them back into the driving seat of exploration. It does this through an event-centric browser called DIVE that allows linking objects through events and collecting diverse perspectives from crowdsourcing to support different points of view. The goal is to shift museums and archives from being mere inventories to places that engage users through event narratives and an infinity of exploration options in linked open data.
This document discusses cognitive computing capabilities and their potential to change how people live and work. It outlines three areas of cognitive capability: engagement, discovery, and decision. Engagement capabilities allow systems to interact naturally with humans through dialogue. Discovery capabilities help systems find new patterns and insights in data. Decision capabilities allow systems to make evidence-based decisions that evolve over time. The document also notes six forces that will influence adoption rates and five dimensions that will impact future cognitive capabilities. It provides an example of how USAA uses cognitive computing to help military members transition to civilian life by answering their questions.
The document summarizes key points from Daniel Pink's book "A Whole New Mind" which argues that society is shifting from valuing left-brain, logical thinking to also valuing right-brain capabilities for the "Conceptual Age". It discusses six essential right-brain aptitudes needed for the future: Design, Story, Symphony, Empathy, Play, and Meaning. For each aptitude, it provides strategies for cultivating those skills and their importance for the future.
"Understanding Humans with Machines" (Arthur Tisi)Maryam Farooq
At NYAI #16, Arthur Tisi explores deep neural networks that dominate advanced approaches to pattern recognition. Today neural networks transcribe our speech, recognize our pets, understand linguistics and fight our trolls. Recent advances by Geoff Hinton and the introduction of capsule networks only ups the ante. But despite the results, we have to wonder… why do they work so well?
In this session, Arthur Tisi, CEO and Founder of MeaningBot, will share some extremely remarkable results in applying deep neural networks to natural language processing (NLP), particularly in the areas of determining human traits in the areas of leadership, team building, personality, consumption preferences and more. Arthur will cite real world examples and share some of the math and science behind these advances including different variants of artificial neural networks, such as deep multilayer perceptron (MLP), convolutional neural network (CNN), recursive neural network (RNN), recurrent neural network (RNN), long short-term memory (LSTM), sequence-to-sequence model, and shallow neural networks including word2vec for word embeddings.
Understanding the New World of Cognitive ComputingDATAVERSITY
Cognitive Computing is a rapidly developing technology that has reached practical application and implementation. So what is it? Do you need it? How can it benefit your business?
In this webinar a panel of experts in Cognitive Computing will discuss the technology, the current practical applications, and where this technology is going. The discussion will start with a review of a recent survey produced by DATAVERSITY on how Cognitive Computing is currently understood by your peers. The panel will also review many components of the technology including:
Cognitive Analytics
Machine Learning
Deep Learning
Reasoning
And next generation artificial intelligence (AI)
And get involved in the discussion with your own questions to present to the panel.
This document discusses cognitive computing. It begins with an introduction that defines cognition and cognitive computing. Cognitive computing aims to develop systems that can think and react like the human mind through a combination of neuroscience, supercomputing, and nanotechnology. The need for cognitive computing is that today's information is challenging to manage and current search engines are limited. An example provided is IBM's Watson, the first cognitive computer, which was able to answer questions in natural language and defeat human champions on Jeopardy. The document concludes by stating that cognitive systems will help make sense of complex information and create new industries through collaboration with human reasoning.
Graphs and Machine Learning have long been a focus for Franz Inc. and currently we are collaborating with a number of companies to deliver the ability to understand possible future events based on a company's internal as well as externally available data. By combining machine learning, semantic technologies, big data, graph databases and dynamic visualizations we will discuss the core components of a Cognitive Computing platform.
We discuss example Cognitive Computing platforms from Ecommerce, fraud detection and healthcare that combine structured/unstructured data, knowledge, linked open data, predictive analytics, and machine learning to enhance corporate decision making.
(1) The building blocks are getting better for the next generation of makers
(2) T-shaped talent is what IBM looks for, and people with lots of ideas! - Whole New Engineer Related
(3) The AI building blocks are getting better too
(4) The next generation can build an amazing world
(5) However, they need to wrestle with ethical decisions - and Whole New Engineer topic, for sure
(6) Q&A
The skills implications of Cognitive ComputingDale Lane
1) Cognitive computing systems learn from interactions with people and data to perform tasks like thinking and making complex decisions with large amounts of information.
2) These systems will change how people interact with technology and require new skills like designing systems that can learn to solve problems and access necessary data.
3) Cognitive computing will be highly disruptive and enable new combinations of human and computer intelligence beyond what either could do alone.
Faith's talk at Barcamp Southampton 2016
She made a chat bot that can answer questions about owls, and used that for most of her presentation. Here are some slides we used to talk about why she chose owls, and how she made the bot.
Cognitive Computing by Professor Gordon Pipadiannepatricia
Professor Dr. Gordon Pipa, University of Osnabrueck, Germany is making this presentation for the Cognitive Systems Institute Speaker Series on May 26, 2016.
SmartData Webinar: Commercial Cognitive Computing -- How to choose and build ...DATAVERSITY
This document provides an overview of cognitive computing and how to build a first cognitive computing application. It discusses fundamentals like natural cognitive processes, approaches to machine learning, and perception. It also outlines the cognitive computing technology ecosystem, including machine learning platforms, input/output technologies, infrastructure providers, and analytics/visualization tools. Finally, it offers advice on first steps like identifying a domain and data sources, choosing a machine learning model, and building a virtuous learning cycle.
The document discusses how open-source intelligence (OSINT) can be used to analyze the Twitter account of Donald Trump and identify that there are two distinct personas tweeting - one from Trump himself using an Android phone in the mornings that tweets more negatively, and another "cutout" persona using an iPhone that tweets later with more positive language and additional features like links and pictures. The analysis of sentiment, emotion, and linguistic structures of the tweets over time indicates the two personas have distinct profiles, and that the account overall has been tweeting more negatively as Trump's presidency progressed.
Applying cognitive computing to business operations, transforming front to ba...HfS Research
Ambitious business leaders are reinventing their enterprises digitally with creative strategies, products and customer experiences. Emerging cognitive solutions have the ability to impact business processes in entirely new ways through autonomous decision making and insightful human engagement. However, many business leaders still view cognitive computing as tomorrow’s potential, not necessarily today’s.
In this webinar, experts from HfS Research, IBM, and Waterfund discuss how cognitive platform based solutions and a design-thinking led approach allow for delivering a personalized, end-to-end frictionless experience.
Watch and learn:
Getting real with Cognitive. Real enterprise case examples of cognitive solutions that transform the way Finance, HR and Procurement services operate
How cognitive capabilities and solutions are enhancing IBM clients' BPO services
The role of service delivery to achieve the Intelligent OneOffice
How the next generation of Service Delivery can bring about a frictionless front to back office transformation
Watch the webinar: http://www.hfsresearch.com/pov/hfs-webinar-august-4
The cognitive advantage: Insights from early adopters on driving business valueSusanne Hupfer, Ph.D.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
IBM faces three main dilemmas in managing innovation: balancing bottom-up and top-down approaches; focusing on long-term research versus short-term success; and determining how open to be with innovation versus developing proprietary intellectual property. Successfully navigating these tensions is key to innovation success. The document discusses IBM's efforts to balance these dilemmas through collaborative open innovation with partners while still generating patents and intellectual property.
Manoj Saxena TED talk - Bending the Knowledge Curve with Cognitive ComputingManoj Saxena
Watson Solutions General Manager Manoj Saxena's TED talk on Bending the Knowledge Curve: "We have only just begun a new era of Cognitive Computing which will dramatically influence our own evolution" http://bit.ly/13cyAGX
Utilizing Social Health Websites for Cognitive Computing and Clinical Decisio...CrowdTruth
Crowdsourced annotations data offers cognitive computing systems insights in lay semantics. This is especially important in health care, where medical terminology is often not aligned with patients `lay' language. However, the general crowd often has limited medical knowledge. Therefore this research investigated the opportunities of social health websites for obtaining ground truth annotations data for cognitive computing systems including clinical decision support systems. By identifying these websites and analyzing their data, it offers a starting point for the future utilization of user-generated health content for cognitive systems. However, the opportunities of social health data are currently limited by various legal regulations. Therefore this paper also dwells on the legal aspects of implementing social health data for cognitive computing systems.
The Cognitive Edge: A New Competitive AdvantageIDC Italy
Sintesi dell'intervento di Giancarlo Vercellino, Research & Consulting Manager di IDC Italia, all'evento Insightful Business 2017: From Data to Business Discovery – Il Cognitive Computing come strumento per il Business, svoltosi a Milano il 15 marzo 2017
The document summarizes Peter Diamandis' top 10 tech trends of 2016 that are transforming humanity. The trends include: 1) Hyper-connecting the world through initiatives like Google's solar drones and satellite constellations from OneWeb and SpaceX. 2) Solar and renewable energy becoming cheaper than coal. 3) Progress in combating diseases like cancer through immunotherapy and CRISPR gene editing. 4) Advances in extending human life through research on aging and stem cells. 5) Successes with stem cells in growing human eyes and helping stroke and paralysis victims. 6) Developments in autonomous vehicles by companies like Google, Tesla, and Uber.
The document discusses DIVE+, a tool that aims to address the issues of audiences feeling disconnected from the massive amounts of digital cultural content available by bringing them back into the driving seat of exploration. It does this through an event-centric browser called DIVE that allows linking objects through events and collecting diverse perspectives from crowdsourcing to support different points of view. The goal is to shift museums and archives from being mere inventories to places that engage users through event narratives and an infinity of exploration options in linked open data.
This document discusses cognitive computing capabilities and their potential to change how people live and work. It outlines three areas of cognitive capability: engagement, discovery, and decision. Engagement capabilities allow systems to interact naturally with humans through dialogue. Discovery capabilities help systems find new patterns and insights in data. Decision capabilities allow systems to make evidence-based decisions that evolve over time. The document also notes six forces that will influence adoption rates and five dimensions that will impact future cognitive capabilities. It provides an example of how USAA uses cognitive computing to help military members transition to civilian life by answering their questions.
The document summarizes key points from Daniel Pink's book "A Whole New Mind" which argues that society is shifting from valuing left-brain, logical thinking to also valuing right-brain capabilities for the "Conceptual Age". It discusses six essential right-brain aptitudes needed for the future: Design, Story, Symphony, Empathy, Play, and Meaning. For each aptitude, it provides strategies for cultivating those skills and their importance for the future.
"Understanding Humans with Machines" (Arthur Tisi)Maryam Farooq
At NYAI #16, Arthur Tisi explores deep neural networks that dominate advanced approaches to pattern recognition. Today neural networks transcribe our speech, recognize our pets, understand linguistics and fight our trolls. Recent advances by Geoff Hinton and the introduction of capsule networks only ups the ante. But despite the results, we have to wonder… why do they work so well?
In this session, Arthur Tisi, CEO and Founder of MeaningBot, will share some extremely remarkable results in applying deep neural networks to natural language processing (NLP), particularly in the areas of determining human traits in the areas of leadership, team building, personality, consumption preferences and more. Arthur will cite real world examples and share some of the math and science behind these advances including different variants of artificial neural networks, such as deep multilayer perceptron (MLP), convolutional neural network (CNN), recursive neural network (RNN), recurrent neural network (RNN), long short-term memory (LSTM), sequence-to-sequence model, and shallow neural networks including word2vec for word embeddings.
The Future of AI: Going BeyondDeep Learning, Watson, and the Semantic WebJames Hendler
These slides, based on a presentation at distinguished lecture at IBM Almaden in March, 2017 explore some of the challenges to machine learning and some recent work. It is a newer version of the slides originally presented at IJCAI 2016.
This document discusses the history and development of electronics and semiconductors. It begins with William Shockley, Walter Brattain, and John Bardeen successfully testing the point-contact transistor in 1947, setting off the semiconductor revolution. Gordon Teal later perfected the silicon-based junction transistor at Texas Instruments, greatly reducing costs. In 1965, Gordon Moore predicted that the number of transistors on a chip would double every two years, known as Moore's Law. The document then discusses shrinking transistor sizes over time and notes that Moore's Law cannot hold indefinitely as transistors reach the atomic scale. It provides sources for further information.
The document discusses several key challenges facing large information systems like the Library of Congress, including fragmentation, findability, and complexity. It notes that users struggle to know which sites to visit for different purposes or find what they need from the home page. Even worse, most potential users never access the Library's resources because they are not easily findable. The document advocates mapping systems and contexts and sharing those maps in order to create environments for understanding.
This document discusses common sense in machines and intelligence without emotion. It explores how the mind works as a "society of mind" made up of many smaller mental agents or processes. While computers can perform many tasks, common sense involves a large variety of knowledge that is difficult for computers to manage. The author proposes that intelligence arises from the interactions between mental agents, not from any single part. Memory may involve "knowledge lines" that connect ideas to the agents that learned them. Overall, the document speculatively examines challenges for machines to develop common sense and human-like intelligence through understanding the mind as a complex system.
"Objective fiction: the semantic construction of web reality" talks about current challenges for semantic technologies, and the Semantic Web in particular, focusing on cognitive and social dimensions of human semantics.
This document provides an agenda for a series of discussions on digital humanities taking place in Pisa, Italy from February to April 2017. The agenda includes topics such as the future, innovation, knowledge, and human questions. Session dates and times are listed, with some sessions devoted to specific topics like the future, innovation, platforms, and rights. Readings are also suggested on future thinking from authors like Al Gore and James Canton. Overall, the document outlines discussions that will examine relationships between digital technologies and humanities as they relate to understanding and shaping the future.
The document discusses several key topics related to artificial intelligence including definitions of intelligence, the origins and evolution of AI, and different areas that contribute to AI research such as mathematics, neuroscience, psychology, and learning. It provides definitions of intelligence from thinkers like Einstein and Socrates and discusses different types of intelligence. The document also summarizes different perspectives on what constitutes AI and examines concepts like the Turing test.
This is my talk delivered 06/04/2024 at the CUBE event (https://www.uni-corvinus.hu/post/landing-page/cube/?lang=en) at the Gellért Campus of the Corvinus University.
Do We Possess the Intelligence to Design Artificial IntelligenceKonrad+King
This presentation was given by Christopher Konrad at the Interaction19 Redux event in San Diego. It is an examination of the aspects of human behavior that can impact or influence the Artificial Intelligence (AI) systems that we are designing.
Knowledge Representation in the Age of Deep Learning, Watson, and the Semanti...James Hendler
IJCAI 16 keynote on the need to bring modern AI accomplishments of recent years into connection with the more traditional goals of symbolic AI (and vice versa).
Making Decisions in a World Awash in Data: We’re going to need a different bo...Micah Altman
In his abstract, Scriffignano summarizes as follows:
l explore some of the ways in which the massive availability of data is changing and the types of questions we must ask in the context of making business decisions. Truth be told, nearly all organizations struggle to make sense out of the mounting data already within the enterprise. At the same time, businesses, individuals, and governments continue to try to outpace one another, often in ways that are informed by newly-available data and technology, but just as often using that data and technology in alarmingly inappropriate or incomplete ways. Multiple “solutions” exist to take data that is poorly understood, promising to derive meaning that is often transient at best. A tremendous amount of “dark” innovation continues in the space of fraud and other bad behavior (e.g. cyber crime, cyber terrorism), highlighting that there are very real risks to taking a fast-follower strategy in making sense out of the ever-increasing amount of data available. Tools and technologies can be very helpful or, as Scriffignano puts it, “they can accelerate the speed with which we hit the wall.” Drawing on unstructured, highly dynamic sources of data, fascinating inference can be derived if we ask the right questions (and maybe use a bit of different math!). This session will cover three main themes: The new normal (how the data around us continues to change), how are we reacting (bringing data science into the room), and the path ahead (creating a mindset in the organization that evolves). Ultimately, what we learn is governed as much by the data available as by the questions we ask. This talk, both relevant and occasionally irreverent, will explore some of the new ways data is being used to expose risk and opportunity and the skills we need to take advantage of a world awash in data.
Dodig-Crnkovic-Information and ComputationJosé Nafría
This document discusses open system thinking and natural computation from an info-computationalism perspective. It provides background on the author and their research interests in computing paradigms, natural/unconventional computing, information dynamics, and computational aspects of science. Key concepts covered include complexity, emergence, self-organization, generative models, agent-based models, and viewing information and computation as the primary stuff and dynamics of the universe respectively. Examples are given of complexity arising from simplicity and adaptive complex systems.
Software update for human brain, at a large scale2co
If we can download "Kung Fu Master skills", would we do the same for "Greatest Thinker skills?" Could we software-update ourselves to be a better person? How, from technological and engineering point of view? What would happen if millions did download such skills and became Greatest Thinkers?
"You Can Do It" by Louis Monier (Altavista Co-Founder & CTO) & Gregory Renard (CTO & Artificial Intelligence Lead Architect at Xbrain) for Deep Learning keynote #0 at Holberton School (http://www.meetup.com/Holberton-School/events/228364522/)
If you want to assist to similar keynote for free, checkout http://www.meetup.com/Holberton-School/
Here are some key terms that are similar to "champagne":
- Sparkling wines
- French champagne
- Cognac
- Rosé
- White wine
- Sparkling wine
- Wine
- Burgundy
- Bordeaux
- Cava
- Prosecco
Some specific champagne brands that are similar terms include Moët, Veuve Clicquot, Dom Pérignon, Taittinger, and Bollinger. Grape varieties used in champagne production like Chardonnay and Pinot Noir could also be considered similar terms.
BB Triatmoko, SJ, MA, MBA, Emerging Management Issues and Challenges.pptxssuser3d9304
1. The document discusses emerging management challenges in the global marketplace such as the effects of globalization, black swan events, knowledge-based management, ethics and social responsibility, and environmental development.
2. It notes that since the 2008 global financial crisis, the unpredictability of the future has been recognized, so organizations must develop robust management systems that can handle uncertainty.
3. Small, ecologically diverse and entrepreneurial organizations that foster innovation are discussed as being better able to handle unpredictability compared to large speculative organizations.
Similar to Enabling cognitive computing business (20)
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
18. 18
Cognitive Computing
We Are In Need Of
Cognitive computing is the simulation of human thought
processes in a computerized model.
Cognitive computing involves self-learning systems that
use data mining, pattern recognition and natural language
processing to mimic the way the human brain works.
The goal of cognitive computing is to create automated
non-organic systems that are capable of solving
problems without requiring human assistance.
DEFINITION
COMPOSITION
GOALS
24. 24
Cognitive Computing Characteristics
FIRST WAVE (KS)
• Handcrafted Knowledge
• Statistical Learning
• Contextual Adaptation
Perceiving
Learning
Abstraction
Reasoning
SECOND WAVE (AI) THIRD WAVE (ATHENIC)
• Handcrafted Knowledge
• Enable reasoning over
narrowly defined problems
• No learning capability and
poor handling of uncertainty
• Cyber Security (Mechaphish)
• ELIZA - Psychotherapy
• Nuanced classification and
prediction capabilities
• No contextual capability and
minimal reasoning ability
• Statistically impressive, but
individually unreliable
• Observer real-time cyber
attacks at scale
• Disease identification
• Handcrafted Knowledge
• Statistical Learning
• Systems construct explanatory
models for classes of real
world phenomena
• Learns overtime how the world
is constructed
• Vast amounts of training data
• Diagnose diseases and
example why
• Find bad guys and explain
why
25. 25
Real-world high dimensional data (such as images) lie on low-
dimensional manifolds embedded in the high-dimensional
space.
• Each manifold represents a different entity
• Understanding data comes by separating the manifolds
Manifolds: Foundation of Knowledge
29. 29
Cloud Translate
Cloud Natural
Language
Cloud Speech
Cloud Vision
Athena Evolve
Athena Genetics
Cloud Video
Intelligence
Athena TensorFlow
Neural Networks
Cognizant and Google Cloud
ATHENIC SYSTEMS
Athena Cloud
Machine Learning
Google Compute,
Storage, Big Data