Cognitive computing
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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.
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The Artificial Intelligence in IoT Applications. Take your first step towards a bright future with our renowned alumnus,
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Artificial Intelligence(A.pptx
This document is a seminar report on artificial intelligence submitted by Yukyhi Raj S.N. to partially fulfill requirements for a BCA degree. The report includes an introduction to AI, its history and applications. It discusses goals of AI like problem solving. It also examines the differences between computer and human intelligence and early milestones in the field like the Turing test. The report provides details on natural language processing, voice synthesis and recognition. It concludes that AI has helped make businesses more efficient by assisting with difficult tasks.
Introduction•Super Computer developed by IBM Research•Named for .pdf
Introduction
•Super Computer developed by IBM Research
•Named for IMB’s founder: Thomas J. Watson
•Initially created for Jeopardy! Game Show
Dr. David Ferrucci leads the Watson project
Development
•Search engines deliver thousands of results that match keywords
•University’s have worked on a consistent question answering software for years
•Programmed by 25 IBM scientists
Not connected to the internet
Jeopardy! Challenge
•Set out to answer complex Jeopardy! Questions
•Language is hard for computers because of “intended meaning”
•During trials, it won 70% of practice games
•February 2011: First computer to compete against humans in Jeopardy!
•Defeated shows greatest two champions Ken Jennings and Brad Rutter
Purpose of Watson
•Idea formed during IBM top executives brainstorming publicity stunts
•DeepBlue– chess supercomputer defeated Garry Kasparov
•IBM’s previous most advanced machine was slow and inaccurate
•Overall goal: “to create a new generation of technology that can find answers from data more
effectively than current search engines”
Technology
•Question-answering Technology
•Deep understanding of natural language.
–Process and answer complex questions that have puns, irony, and/or riddles
•Computer running Software called Deep QA
•Runs on cluster of Power 750 computers
–ten racks holding 90 servers, for a total of 2880 processor cores running DeepQA software and
storage
–Holds approximately one million books worth of information
Managerial Purposes
•Financial Assistant: Working with Citi Bank
–Help analyze customer needs
–Process financial, economic, product, and client data
–Help financial professionals make better decision
•Could IBM Watson rival complex derivatives on the trade floor?
Other Possibilities?
•Travel
•Retail
•Healthcare
Classroom
Advantages
•Provides Services that revolve around the new, digital world
•Gives immediate answers instead of search results
•Healthcare uses
–Diagnosis
–Information Warehouse
•Efficiency and Organization
Disadvantages
•Cannot read PET and CT scans to identify tumors
•Questions asked must be in text
•Less human effort
–Too reliant upon technology
–Less personal interaction between doctors and patients
•Not cognitive
–Only manipulates symbols
•Limits understanding and reasoning behind decisions
Competition
•Thus far there are no other computers that are near the performance level of Watson
•Microsoft and GE announced plans to create something similar to use in the healthcare industry
–Aim to use analytics, high performance software technologies to deliver patient outcomes and
clinical applications
Applications to SIT
•New technology for a business’ Decision Making Processes
–Organizational structure may shift based on allocation of decision making
•Potentially eliminates the needs/advantages of Virtual Teams (especially in healthcare)
•Changes Knowledge Management Processes
Solution
Introduction
•Super Computer developed by IBM Research
•Named for IMB’s founder: Thomas J. Watson
•Initially creat.
Ai introduction
Artificial intelligence (AI) is intelligence exhibited by machines. It is the branch of computer science which deals with creating computers or machines that are as intelligent as humans. The document discusses the history and evolution of AI from its foundations in 1943 to modern applications. It also defines different types of AI such as narrow AI, artificial general intelligence, and artificial super intelligence. Popular AI techniques like machine learning, deep learning, computer vision and natural language processing are also summarized.
AIML_Unit1.pptx
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.
AILABS - Lecture Series - Is AI the New Electricity? - Advances In Machine Le...
Prof. Garain discusses in brief on the backgrounds of learning algorithms & major breakthroughs that have been made in the field of machine perception in the last 50 yrs. He also discusses the role of statistical algorithms like artificial neural network, support vector machines, and other concepts related to Deep Learning algorithms.
Along with the above, Prof. Garain touched upon the basics of CNN & RNN, Long Short-Term Memory Networks (LSTM) & attention network & illustrate all of these using real-life problems. Several state-of-the-art problems like image captioning, visual question answering, medical image analysis etc. were discussed to make the potential of deep learning algorithms understandable.
Prof. Utpal Garain is one of the leading minds in Kolkata in the field of Neural Networks & Artificial Intelligence. His research interest is now focused on AI research, especially exploring deep learning methods for language, image and video analysis including NLP tools, OCRs, handwriting analysis, computational forensics and the like.
n01.ppt
This document provides an overview of an introduction to artificial intelligence course. It discusses course administration details like the instructor, TAs, meeting times, grading, and textbook. It then covers topics that will be discussed in the course like what AI is, the ingredients of intelligence, history of AI, applications of AI, and goals of AI. Key problems in AI like representation, search, inference, learning, and planning are also summarized. Different design methodologies like thinking rationally to formalize inference and thinking like humans from a cognitive science perspective are contrasted.
Assessing computational thinking
The document discusses assessing computational thinking (CT). It defines CT as using skills like abstraction, decomposition, algorithm design, and generalization to solve problems. CT is important for 21st century skills and jobs. The document outlines how CT can be assessed through coding tasks, problem formulation depth, and system design precision and efficiency. It notes that while CT uses computing, it can be done without computers. Overall, the document argues that CT fosters systematic thinking and is an important skill that can be taught and assessed.
Ibm's watson
IBM's Watson is a question answering computer system developed by IBM to answer questions posed in natural language. It was named after IBM's founder Thomas J. Watson and was initially created to compete on the game show Jeopardy! where it defeated human champions in 2011. Watson uses advanced natural language processing, semantic analysis, and machine learning to defeat human opponents. It is capable of answering complex questions with nuanced language and is being developed by IBM for commercial applications in fields like healthcare, finance and education.
Ibm's watson
IBM's Watson is a question answering computer system developed by IBM to answer questions posed in natural language. It was named after IBM's founder Thomas J. Watson and was initially created to compete on the game show Jeopardy! where it defeated human champions in 2011. Watson uses advanced natural language processing, semantic analysis, and machine learning to defeat human opponents. It is capable of answering complex questions with nuanced language and is being developed by IBM for commercial applications in fields like healthcare, finance and education.
Artificial intelligence- The science of intelligent programs
Artificial intelligence (AI) involves creating intelligent computer programs and machines that can interact with the real world similarly to humans. AI uses techniques like machine learning, deep learning, and neural networks to allow programs to learn from data and experience without being explicitly programmed. While AI has potential benefits, some experts warn that advanced AI could pose risks if not developed carefully due to concerns it could become difficult for humans to control once a certain level of intelligence is achieved.
Ibm's watson
IBM's Watson is a question answering computer system developed by IBM to answer questions posed in natural language. It was named after IBM's founder Thomas J. Watson and was initially created to compete on the game show Jeopardy! where it defeated human champions in 2011. Watson uses advanced natural language processing, semantic analysis, and machine learning to defeat human opponents. It is capable of answering complex questions with nuanced language and is being developed by IBM for commercial applications in fields like healthcare, finance and education.
Ibm's watson
IBM's Watson is a question answering computer system developed by IBM to answer questions posed in natural language. It was named after IBM's founder Thomas J. Watson and was initially created to compete on the game show Jeopardy! where it defeated human champions in 2011. Watson uses advanced natural language processing, semantic analysis, and machine learning to defeat human opponents. It is capable of answering complex questions with nuanced language and is being developed by IBM for commercial applications in fields like healthcare, finance and education.
Lec1 introduction
This document provides an overview of artificial intelligence. It defines intelligence as the ability to plan, solve problems, reason, learn, understand new situations, and apply knowledge. AI is described as building intelligent systems that can think and act like humans or rationally. The history of AI is discussed, from its origins in the 1950s to current applications. Key concepts to be learned in the semester include problem solving, machine learning, evolutionary computation, robotics, and intelligent agents. Python and NetLogo will be used as tools.
Artificial intelligence
Artificial intelligence technologies are being used widely today and major projects aim to continue advancing AI capabilities. The document discusses how AI is used for tasks like robotic process automation, text analysis, speech recognition, virtual assistants, and biometrics. It also outlines concerns about ensuring AI systems remain helpful rather than harmful to humanity. Major projects like Google Brain and the Blue Brain Project seek to better understand and replicate the human brain to develop more intelligent computer systems.
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Autonomy in targeting is a function that could be applied to any intelligent system, in particular the rapidly expanding array of robotic systems, in the air, on land and at sea – including swarms of small robots. This is an area of significant investment and emphasis for many armed forces, and the question is not so much whether we will see more intelligent robots, but whether and by what means they will remain under human control. Today’s remote-controlled weapons could become tomorrow’s autonomous weapons with just a software upgrade. The central element of any future autonomous weapon system will be the software. Military powers are investing in AI for a wide range of applications10 and significant efforts are already underway to harness developments in image, facial and behavior recognition using AI and machine learning techniques for intelligence gathering and “automatic target recognition” to identify people, objects or patterns. Although not all autonomous weapon systems incorporate AI and machine learning, this software could form the basis of future autonomous weapon systems.Artificialintelligence
machines will be capable, within 20 years, of doing any work a man can do." Two years later, MIT researcher Marvin Minsky predicted, "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."
(artificial intelligence innovator Herbert Simon.1965
Lecture 1 introduction
This document provides an overview of an Intelligent Systems course. It outlines the course assignments and grading breakdown. It then discusses what AI is, including definitions and different views of AI like thinking humanly, acting humanly, thinking rationally, and acting rationally. It also provides a brief history of AI and discusses the current state of the art in applications like speech recognition, machine translation, robotics, and recommendation systems.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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Cognitive computing
- 1. Cognitive Computing Patel Gayatri K. MCA, Roll no:41 Dharmsinh Desai Univercity, Nadiad
- 2. My Agendas: • Introduction • Need of cognitive technology • Architecture of cognitive systems • Examples of cognitive systems • Cognitive Computing: 5 Future Technology Innovations
- 3. The worst(pig) and best thing(super computer) on world!
- 5. When there is a fire the pig tries to come out from the room.. but the super computer fails at that point.. So what is great? Obviously PIG!! Yeah… you heard it right!! So it is necessary to make computers think like Human(Animal).
- 6. Introduction • • What Is Cognition? • Mental action of acquiring knowledge through thoughts, experience and senses. What is Cognitive Computing? • “Technology for the development of computer system from s/w and h/w elements which have ability to think and react like human minds.” • Combination of Neuroscience , Super computing and Nanotechnology.
- 7. Introduction(cont.) • Originally referred as AI, from 1990’s called Cognitive Computing.
- 8. Why it is too hard for computer to understand humans?
- 9. Need Of Cognitive Computing: • Today’s Information Challenge:
- 10. Search vs. Expert Q&A Decision Maker Search Engine Finds Documents containing Keywords Delivers Documents based on Popularity Has Question Distills to 2-3 Keywords Reads Documents, Finds Answers Finds & Analyzes Evidence Expert Understands Question Produces Possible Answers & Evidence Delivers Response, Evidence & Confidence Analyzes Evidence, Computes Confidence Asks NL Question Considers Answer & Evidence Decision Maker
- 11. What if an enterprise has all the answer it need to succeed?
- 12. Purpose: • “to create a new generation of technology that can find answers from data more effectively than current search engines”
- 13. IBM Watson • For this purpose, the very first cognitive computer named “Watson” was developed by IBM co. • Capable of answering questions posed in natural language • Watson was named after IBM's Thomas J. Watson.
- 14. IBM Watson(cont.) • Search engines deliver thousands of results that match keywords • University’s have worked on a consistent question answering software for years • Programmed by 25 IBM scientists • Not connected to the internet
- 15. Jeopardy Challenge! • February 2011: First computer to compete against humans in Jeopardy! • Defeated shows greatest two champions Ken Jennings and Brad Rutter
- 16. Technology • Question-answering Technology • Deep understanding of natural language. • Computer running Software called Deep QA ▫ Holds approximately one million books worth of information
- 17. How does Watson answer the questions?
- 18. Process • Step 1: • Question Analysis • Step 2: • Hypothesis generation • Step 3: • Hypothesis and Evidence Scoring • Step 4: • Final Merging and Ranking
- 19. A little more in depth
- 20. Examples Of Cognitive Technology
- 21. Cognitive Computing : 5 Future Technology Innovations By IBM
- 23. Conclusion • We believe that cognitive systems will help us make sense of our amazingly complex world and provide a new collaborative dimension to human reasoning and decision making. • These technologies will help create new products, services, companies and entire industries.
- 24. References • http://www.research.ibm.com/cognitive- computing/why-cognitive- systems.shtml#fbid=ItfZPfHiWoz • http://www.forbes.com/sites/rogerkay/2011/12/ 09/cognitive-computing-when-computers- become-brains/ • http://www.neuralytix.com/blog/2014/02/24/co gnitive-computing/
- 25. THANK YOU