Watson - a super computer, presentation is based on a super computer made by IBM basically to play Jeopardy! quiz show.
This is made by me in order to present it in my final Seminar presentation.
IBM Watson Ecosystem roadshow - Chicago 4-2-14cheribergeron
IBM Watson is powering a new generation of cognitive applications. Learn how IBM is partnering with visionaries and entrepreneurs to bring innovative cognitive applications to market through the IBM Watson Ecosystem.
What is IBM Watson, What is Cognitive Computing, What organizations benefit from IBM Watson, and get an exclusive look into IBM Watson in an in-depth demo exploration. For more information about Watson, email Cresco at info@crescointl.com or visit http://www.crescointl.com.
VanFUNDING Oct 18, 2016: Closing keynote IBM Watson in the cognitive era (Ca...Craig Asano
Lead Partner - Business Analytics and Cognitive Services, IBM Global Business Services, Caroline Ong, delivers closing keynote at VanFUNDING 2016 at The Imperial Vancouver. Introducing IBM Watson in the Cognitive Era and the potential for accelerating Fintech Crowdfunding markets.
IBM Watson Ecosystem roadshow - Chicago 4-2-14cheribergeron
IBM Watson is powering a new generation of cognitive applications. Learn how IBM is partnering with visionaries and entrepreneurs to bring innovative cognitive applications to market through the IBM Watson Ecosystem.
What is IBM Watson, What is Cognitive Computing, What organizations benefit from IBM Watson, and get an exclusive look into IBM Watson in an in-depth demo exploration. For more information about Watson, email Cresco at info@crescointl.com or visit http://www.crescointl.com.
VanFUNDING Oct 18, 2016: Closing keynote IBM Watson in the cognitive era (Ca...Craig Asano
Lead Partner - Business Analytics and Cognitive Services, IBM Global Business Services, Caroline Ong, delivers closing keynote at VanFUNDING 2016 at The Imperial Vancouver. Introducing IBM Watson in the Cognitive Era and the potential for accelerating Fintech Crowdfunding markets.
IBM Watson Jeopardy! white paper which explains Watson’s workload optimised system design based on IBM DeepQA architecture and POWER7® processor-based servers
A modified version of IBM Watson Analytics presentation. It covers its development, history, how it works and screen shot of IBM Watson Analytics Application. The presentation included a sample of a Food Production Index of the Philippines from 1999 to 2013 Analytics presentation conducted at Asia Pacific College, Manila, Philippines. The report was used in Advance Emerging Technology class at the University of the East, Manila, Philippines.
Watson Customer Engagement offerings deliver a broad range of capabilities for marketing, commerce and supply chain activities. Each offering is designed to complement the skills of forward-thinking professionals like you. To enhance your expertise. To empower you to make better, more informed decisions. And help you take action confidently as you drive your organization's growth and deliver rapid innovation.
IBM Watson Question-Answering System and Cognitive ComputingRakuten Group, Inc.
IBM's vision of cognitive computing has been steadily embraced across the industries since IBM's Watson question-answering system made a sensational debut at the US Jeopardy! television quiz show in 2011. As a core member of the Watson project, I would like to share the excitement of the project and the last five and a half year of its progress into the cognitive business. In this talk, I will also give a technical overview of Watson, major use cases, and perspectives on the future of cognitive computing.
https://tech.rakuten.co.jp/
IBM Watson, the cognitive technology that enhances, scales, & accelerates human expertise, is available to anyone through Bluemix, IBM’s PaaS. Watson's cognitive capabilities on Bluemix will enhance apps & help developers realize ideas not possible with today's systems.
Quick test, ask your phone “find anything but pizza restaurants”. Did you get back a list of pizza restaurants? Think about how we’ve been trained to keyword search. We have all been Google-fied & we may not even know it. Humans adapt their language, one that predates machines, to the limitations of a system.
But Watson is not a machine that lets us talk to it. It’s bigger, and that’s why this is a historic moment for developers, businesses & entrepreneurs. IBM is creating tools that can understand language, determine a personality portrait, expand concepts & more. In this session we will discuss & demo Watson Services on Bluemix & how developers can now embed these into their apps for unprecedented cognitive power.
A presentation given in Denmark, introducing cognitive computing, highlighting potential benefits and early use-cases in insurance with IBM Watson. The presentation included demos.
Link to youtube video of FlexRate Insurers self-service demo: https://www.youtube.com/watch?v=8xRN9RzpVBE&spfreload=10
Link to IBM Watson white paper on Cognitive Computing in Insurance:
Outlines Watson accomplishments in 2012 and new products announced in early 2013. THIS DOCUMENT IS PROVIDED FOR REFERENCE PURPOSES ONLY. IBM RESERVES THE RIGHTS TO MAKE CHANGES TO THIS EVOLVING PORTFOLIO.
Invited talk at the LTsolutions International Workshop in Donostia-San Sebastián, Spain on 21st May 2015.
More information about the workshop at: http://www.langune.com/home/presentationen/ltsolutions
Deloitte's report and point of view on IBM's Watson. IBM Watson, AI, Cognitive Computing are rapidly evolving technologies that can support and enhance enterprise solutions. Learn about IBM Watson the Why? and the How?
Presentation of IBM Watson, the components of Watson, how it works and examples of where Watson is being put to use, today. Finally links and information about, how you can get to work with Watson as a software developer.
Presentation given in te conference 'Driving IT' in Copenhagen, November 14, 2014
Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project. Watson is a cognitive technology that processes information more like a human than a computer—by understanding natural language, generating hypotheses based on evidence and learning as it goes.
This presentation provides demonstrations of Watson API Services utilized in various Big Data and Analytic applications and was presented at Penn State's Nittany Watson Challenge Immersion event on January 19-20, 2017.
IBM Watson Jeopardy! white paper which explains Watson’s workload optimised system design based on IBM DeepQA architecture and POWER7® processor-based servers
A modified version of IBM Watson Analytics presentation. It covers its development, history, how it works and screen shot of IBM Watson Analytics Application. The presentation included a sample of a Food Production Index of the Philippines from 1999 to 2013 Analytics presentation conducted at Asia Pacific College, Manila, Philippines. The report was used in Advance Emerging Technology class at the University of the East, Manila, Philippines.
Watson Customer Engagement offerings deliver a broad range of capabilities for marketing, commerce and supply chain activities. Each offering is designed to complement the skills of forward-thinking professionals like you. To enhance your expertise. To empower you to make better, more informed decisions. And help you take action confidently as you drive your organization's growth and deliver rapid innovation.
IBM Watson Question-Answering System and Cognitive ComputingRakuten Group, Inc.
IBM's vision of cognitive computing has been steadily embraced across the industries since IBM's Watson question-answering system made a sensational debut at the US Jeopardy! television quiz show in 2011. As a core member of the Watson project, I would like to share the excitement of the project and the last five and a half year of its progress into the cognitive business. In this talk, I will also give a technical overview of Watson, major use cases, and perspectives on the future of cognitive computing.
https://tech.rakuten.co.jp/
IBM Watson, the cognitive technology that enhances, scales, & accelerates human expertise, is available to anyone through Bluemix, IBM’s PaaS. Watson's cognitive capabilities on Bluemix will enhance apps & help developers realize ideas not possible with today's systems.
Quick test, ask your phone “find anything but pizza restaurants”. Did you get back a list of pizza restaurants? Think about how we’ve been trained to keyword search. We have all been Google-fied & we may not even know it. Humans adapt their language, one that predates machines, to the limitations of a system.
But Watson is not a machine that lets us talk to it. It’s bigger, and that’s why this is a historic moment for developers, businesses & entrepreneurs. IBM is creating tools that can understand language, determine a personality portrait, expand concepts & more. In this session we will discuss & demo Watson Services on Bluemix & how developers can now embed these into their apps for unprecedented cognitive power.
A presentation given in Denmark, introducing cognitive computing, highlighting potential benefits and early use-cases in insurance with IBM Watson. The presentation included demos.
Link to youtube video of FlexRate Insurers self-service demo: https://www.youtube.com/watch?v=8xRN9RzpVBE&spfreload=10
Link to IBM Watson white paper on Cognitive Computing in Insurance:
Outlines Watson accomplishments in 2012 and new products announced in early 2013. THIS DOCUMENT IS PROVIDED FOR REFERENCE PURPOSES ONLY. IBM RESERVES THE RIGHTS TO MAKE CHANGES TO THIS EVOLVING PORTFOLIO.
Invited talk at the LTsolutions International Workshop in Donostia-San Sebastián, Spain on 21st May 2015.
More information about the workshop at: http://www.langune.com/home/presentationen/ltsolutions
Deloitte's report and point of view on IBM's Watson. IBM Watson, AI, Cognitive Computing are rapidly evolving technologies that can support and enhance enterprise solutions. Learn about IBM Watson the Why? and the How?
Presentation of IBM Watson, the components of Watson, how it works and examples of where Watson is being put to use, today. Finally links and information about, how you can get to work with Watson as a software developer.
Presentation given in te conference 'Driving IT' in Copenhagen, November 14, 2014
Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project. Watson is a cognitive technology that processes information more like a human than a computer—by understanding natural language, generating hypotheses based on evidence and learning as it goes.
This presentation provides demonstrations of Watson API Services utilized in various Big Data and Analytic applications and was presented at Penn State's Nittany Watson Challenge Immersion event on January 19-20, 2017.
Discover what comes next for IBM Watson and the industries particularly suited for Watson solutions, such as healthcare, banking, and the financial sector. All of which deal with massive amounts of unstructured data coming from various sources. Find out how the advanced analytics used in Watson are being put to work in businesses around the world.
IBM Watson overview presented by Mike Pointer, Watson Sr. Solution Architect, at Penn State's Nittany Watson Challenge Immersion event on January 19-20, 2017.
Please download the presentation, instead of viewing online, in order to see the videos and animations.
Watson brings a new era of computing to our lives. Cognitive computing changes the way a computer interacts with the world, and how it reacts to it. Besides excelling in answering questions in Jeopardy!, see how IBM is putting Watson to work in finance, medicine, services, and why you may be talking to Watson very soon, and not even notice it!
Post 1What is text analytics How does it differ from text mini.docxstilliegeorgiana
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
Post 1What is text analytics How does it differ from text minianhcrowley
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
Machine Learning on Big Data with HADOOPEPAM Systems
Machine learning is definitely an exciting application
that helps you to tap on the power of big
data. As for corporate data continues to grow
bigger and more complex, machine learning will
become even more attractive. The industry has
come up elegant solutions to help corporations
to solve this problem. Let’s get ready; it is just a
matter time this problem arrives at your desk.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Communications Mining Series - Zero to Hero - Session 1
Watson - a supercomputer
1. BE - 3rd Year
Information Technology
A. D. Patel Institute of Technology
Prepared by:
Utsav Patel - 120010116017
Harshil Darji - 120010110645
2. CONTENTS
History
Description
• Software
• Hardware
• Data
Operation
Future Application
• Health care
• IBM Watson Group
FIVE WAYS WATSON WILL CHANGE COMPUTING
3. HISTORY
Since Deep Blue's victory over Garry Kasparov in chess in 1997, IBM had been on the
hunt for a new challenge.
IBM Research executive Paul Horn backed Lickel up, pushing for someone in his
department to take up the challenge of playing Jeopardy! with an IBM system.
In competitions managed by the United States government, Watson's predecessor, a
system named Piquant, was usually able to respond correctly to only about 35% of clues
and often required several minutes to respond.
To compete successfully on Jeopardy!, Watson would need to respond in no more than a
few seconds, and at that time.
The IBM team was given three to five years and a staff of 15 people to solve the
problems. By February 2010, Watson could beat human Jeopardy! contestants on a
regular basis.
4. DESCRIPTION
Watson is an artificially intelligent computer system capable of answering questions
posed in natural language, developed in IBM's DeepQA project by a research team led
by principal investigator David Ferrucci.
Watson was named after IBM's first CEO and industrialist Thomas J. Watson.
The computer system was specifically developed to answer questions on the quiz show
Jeopardy!
Watson had access to 200 million pages of structured and unstructured content
consuming four terabytes of disk storage including the full text of Wikipedia, but was not
connected to the Internet during the game.
Basically it consist of Software, Hardware, Data which is explained in upcoming slides.
5. SOFTWARE:
Watson uses IBM's DeepQA software and the Apache UIMA (Unstructured Information
Management Architecture) framework. The system was written in various languages,
including Java, C++, and Prolog, and runs on the SUSE Linux Enterprise Server 11
operating system using Apache Hadoop framework to provide distributed computing.
HARDWARE:
The system is workload optimized, integrating massively parallel POWER7 processors
and being built on IBM's DeepQA technology, which it uses to generate hypotheses,
gather massive evidence, and analyze data. Watson is composed of a cluster of ninety
IBM Power 750 servers, each of which uses a 3.5 GHz POWER7 eight core processor,
with four threads per core. In total, the system has 2,880 POWER7 processor cores and
has 16 terabytes of RAM.
6. DATA:
The sources of information for Watson include encyclopedias, dictionaries, thesauri,
newswire articles, and literary works. Watson has also used databases, taxonomies, and
ontologies.
The IBM team provided Watson with millions of documents, including dictionaries,
encyclopedias, and other reference material that it could use to build its knowledge .
It contained 200 million pages of structured and unstructured content consuming four
terabytes of disk storage, including the full text of Wikipedia.
Watson was not connected to the Internet during the game to play a honest game with
participated humans and other computers.
We can set the intelligence of Watson according to requirement to play against kids,
adults and computers.
7. OPERATION
When playing Jeopardy! all players must wait until host Alex Trebek reads each clue in
its entirety, after which a light is lit as a "ready" signal; the first to activate their buzzer
button wins the chance to respond.
Watson received the clues as electronic texts at the same moment they were made
visible to the human players.
It would then parse the clues into different keywords and sentence fragments in order to
find statistically related phrases.
Its ability to quickly execute thousands of proven language analysis algorithms
simultaneously helps WATSON to find the correct answer.
The more algorithms that find the same answer independently the more likely Watson is
to be correct.
After finding correct answer, Watson speaks with an electronic voice and gives the
responses in Jeopardy!'s question format.
8. FUTURE APPLICATION
According to IBM, “The goal is to have computers start to interact in natural human terms
across a range of applications and processes, understanding the questions that humans
ask and providing answers that humans can understand and justify.”
It has been suggested by Robert C. Weber, IBM's general counsel, that Watson may be
used for legal research.
The company also intends to use Watson in other information-intensive fields, such as
telecommunications, financial services, and government .
The other future applications are as follows:
1. Health care
2. IBM Watson Group
9. HEALTH CARE:
In healthcare, Watson's natural language, hypothesis generation, and evidence-based
learning capabilities allow it to function as a clinical decision support system for use by
medical professionals.
Watson helps physicians in the treatment of their patients, once a doctor has posed a
query to the system describing symptoms and other related factors, Watson first parses
the input to identify the most important pieces of information; then mines patient data to
find facts relevant to the patient's medical and hereditary history; then examines
available data sources to form and test hypotheses; and finally provides a list of
individualized, confidence-scored recommendations.
The sources of data that Watson uses for analysis can include treatment guidelines,
electronic medical record data, notes from doctors and nurses, research materials,
clinical studies, journal articles, and patient information.
10. IBM WATSON GROUP:
On January 9, 2014 IBM announced it is creating a business unit around Watson, led by
senior vice president Michael Rhodin. IBM Watson Group will have headquarters in New
York's Silicon Alley and will employ 2,000 people. IBM has invested $1 billion to get the
division going.
Watson Group will develop three new cloud-delivered services: Watson Discovery
Advisor, Watson Analytics, and Watson Explorer:
• Watson Discovery Advisor will focus on research and development projects in
pharmaceutical industry, publishing and biotechnology.
• Watson Analytics will focus on Big Data visualization and insights on the basis of
natural language questions posed by business users.
• Watson Explorer will focus on helping enterprise users uncover and share data-driven
insights more easily.
11. FIVE WAYS WATSON WILL CHANGE COMPUTING
Watson, IBM’s artificial intelligence computing platform, is changing the way we
compute:
1. Watson Will Make Your Doctor Smarter:
• To do so, IBM is feeding Watson massive amounts of texts and records to make it
“smarter.”
• “Doctors are trained on a set of information in med school and go through internships
and residencies.
• But when they’re practicing, they only have so much time to catch up with new
information.
• When you add in something like low cost DNA sequencing in genomics, it's simply
overwhelming,” Rhodin says. Doctors and nurses are already using Watson in the
field, and soon it will become an even more reliable advisor.
12. 2. Watson Will Transform Entire Industries:
• Rhodin confirmed that IBM is considering the oil and gas industries as potential
Watson consumers. Another job listing for a product manager confirms that IBM
wants to position Watson in government and the financial sector.
• Rhodin cites wealth management as one category he sees a particular niche for
Watson in.
• As a company, IBM is far more comfortable dealing with enterprise customers and
large corporate or institutional clients than the consumer market, which it traditionally
has had issues reaching. Early Watson efforts have been concentrated on health
care, which is a perfect example of an industry dominated by relatively few
institutional players. Rhodin told me the company wants to hire anyone who, as he
puts it, “has domain level expertise.”
13. 3. Watson Could Think Like A Human:
• The backend of Watson—the servers, software architecture, and API which allow
developers to build apps, relies on a process called “cognitive computing.”
• In layman’s terms, cognitive computing allows software to mimic perceptive,
cognitive, and interactive aspects of the human brain.
• Earlier this month, IBM announced a $3 billion R&D investment in computer
hardware that mimics the human brain.
• In an increasingly cloud-driven world where diverse arrays of companies rely on a
remote infrastructure (See: Amazon Web Services, Salesforce, and the Google
ecosystem), IBM is positioning themselves as a major player for cognitive software.
14. 4. Watson Will Be Inside Your Phones, Tablets, And Toys:
• IBM held a Watson mobile challenge at this year’s Mobile World Congress as a way
of finding case studies for Watson outside of desktop computers.
• The three winners were a tablet based trainer for in-store retail personnel called Red
Ant, a personal health care wellness assistance tool called GenieMD, and a
company called Majestyk Apps which made a prototype stuffed animal called FANG
(Friendly Anthromorphic Network Genome).
• There has been speculation by many industry observers that the recent Apple-IBM
partnership could ease the way for iOS developers to work in the Watson ecosystem.
But as we’re about to see, IBM is already laying plans for a massive Watson
ecosystem.
15. 5. Tomorrow's Programmers Are Building Apps For Watson:
• One thing Rhodin seemed especially happy about during the interview was IBM’s
work building partnerships with universities to steer developers towards Watson.
• Rhodin told Fast Company that this fall, 10 U.S. universities would begin offering
Watson-based computing classes including Carnegie Mellon, Ohio State, the
University of Texas-Austin, the University of Michigan and New York University.
• As he put it, “A large number of top schools in North America will train people on how
to build cognitive applications and be the next generation of cognitive entrepreneurs
in market.”
• IBM has also been giving outsiders access to Watson’s API (though applicants have
complained of a glacial pace in approvals) to build out applications across a variety
of industries.
16. “All the problems of the world could be settled
easily if men were only willing to think.”
- Thomas J. Watson
Reference: www.wikipedia.org | www.fastcompany.com
. . . T h a n k Y o u . . .