September 9, 2019Quiz
Watson began as a question-answering computer system capable of answering 1) ___ 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, industrialist Thomas J. Watson. The computer system was initially developed to answer questions on the quiz show Jeopardy and, in 2011, the Watson computer system competed on Jeopardy against legendary champions Brad Rutter and Ken Jennings winning the first place prize of $1 million.
In February 2013, IBM announced that Watson software system's first commercial application would be for utilization management decisions in lung cancer treatment at Memorial Sloan Kettering Cancer Center, New York City, in conjunction with WellPoint (now Anthem). At Memorial, Watson trained to be a PA (physician's 2)___). Manoj Saxena, IBM Watson's then business chief, said in 2013 that 90% of nurses in the field who use Watson, now follow its guidance.
High-level architecture has been used to develop IBM's DeepQA used in Watson, their AI system. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. The key difference between QA technology and document search is that document search takes a keyword query and returns a list of documents, ranked in order of relevance to the query (often based on popularity and page ranking), while QA technology takes a question expressed in natural language, seeks to understand it in much greater detail, and returns a precise answer to the question.
When created, IBM stated that, more than 100 different techniques are used to analyze natural language, identify sources, find and generate hypotheses, find and score evidence, and merge and rank hypotheses. In recent years, the Watson capabilities have been extended and the way in which Watson works has been changed to take advantage of new deployment models (Watson on IBM Cloud) and evolved machine 3) ___ capabilities and optimized hardware available to developers and researchers. It is no longer purely a question answering (QA) computing system designed from Q&A pairs but can now ?see', ?hear', ?read', ?talk', ?taste', ?interpret', ?learn' and ?recommend'.
Watson can process 500 gigabytes, the equivalent of a million books, per second. It has been estimated that Watson's hardware cost at about three million dollars. All content was stored in Watson's RAM for the Jeopardy game because data stored on hard drives would be too slow to be competitive with human Jeopardy champions. The sources of information for Watson include encyclopedias, dictionaries, thesauri, newswire articles and literary works. Watson 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. The computer's techniques for unravelling clues involved zeroing in on keywords in a clue, then combing its memory (in Watson's case, a 15-terabyte databank of human knowledge) for clusters of associations with those words. It rigorously checks the top hits against all the contextual information it can muster: the category name; the kind of answer being sought; the time, place, and gender hinted at in the clue; and so on. And when it feels sure enough, it decides to buzz. This is all an instant, intuitive process for a human Jeopardy player.
Watson parses questions into different keywords and sentence fragments in order to find statistically related phrases. Watson's main innovation was not in the creation of a new algorithm for this operation but rather its ability to quickly execute hundreds of proven language analysis algorithms simultaneously. The more 4) ___ that find the same answer independently the more likely Watson is to be correct. Once Watson has a small number of potential solutions, it is able to check against its database to ascertain whether the solution makes sense or not. Watson's basic working principle is to parse keywords in a clue while searching for related terms as responses. This gives Watson some advantages and disadvantages compared with human Jeopardy. Watson has deficiencies in understanding the contexts of the clues. As a result, human players usually generate responses faster than Watson, especially to short clues. Watson's programming prevents it from using the popular tactic of buzzing before it is sure of its response. Watson has consistently better reaction time on the buzzer once it has generated a response, and is immune to human players' psychological tactics, such as jumping between categories on every clue.
In a sequence of 20 mock games of Jeopardy, human participants were able to use the average six to seven seconds that Watson needed to hear the clue and decide whether to signal for responding. During that time, Watson also has to evaluate the response and determine whether it is sufficiently confident in the result to signal. Part of the system used to win the Jeopardy contest was the electronic circuitry that receives the ready signal and then examined whether Watson's confidence level was great enough to activate the buzzer. Given the speed of this circuitry compared to the speed of human reaction times, Watson's reaction time was faster than the human contestants except when the human anticipated (instead of reacted to) the ready signal. After signaling, Watson speaks with an electronic voice and gives the responses in Jeopardy's question format.
Development of Watson, so far:
Since Deep Blue's victory over Garry Kasparov in chess in 1997, IBM had been on the hunt for a new challenge. Initially there was trouble finding any research staff willing to take on what looked to be a much more complex challenge than the wordless game of chess. 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 problems posed by the game show were deemed to be impossible to solve. In initial tests run during 2006, Watson was given 500 clues from past Jeopardy programs. While the best real-life competitors buzzed in half the time and responded correctly to as many as 95% of clues, Watson's first pass could get only about 15% correct. During 2007, the IBM team was given three to five years and a staff of 15 people to solve the problems. By 2008, the developers had advanced Watson such that it could compete with Jeopardy champions. By February 2010, Watson could beat human Jeopardy contestants on a regular basis.
During the game, Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage including the full text of the 2011 edition of Wikipedia, but was not connected to the Internet. For each clue, Watson's three most probable responses were displayed on the television screen. Watson consistently outperformed its human opponents on the game's signaling device, but had trouble in a few categories, notably those having short clues containing only a few words.
Although the system is primarily an IBM effort, Watson's development involved faculty and graduate students from Rensselaer Polytechnic Institute, Carnegie Mellon University, University of Massachusetts Amherst, the University of Southern California's Information Sciences Institute, the University of Texas at Austin, the Massachusetts Institute of Technology, and the University of Trento, as well as students from New York Medical College. In 2008, IBM representatives communicated with Jeopardy about the possibility of having Watson compete against Ken Jennings and Brad Rutter, two of the most successful contestants on the show, and the program's producers agreed. Watson's differences with human players had generated conflicts between IBM and Jeopardy staff during the planning of the competition. IBM repeatedly expressed concerns that the show's writers would exploit Watson's cognitive deficiencies when writing the clues, thereby turning the game into a Turing test. To alleviate that claim, a third party randomly picked the clues from previously written shows that were never broadcast. Jeopardy staff also showed concerns over Watson's reaction time on the buzzer. Originally Watson signaled electronically, but show staff requested that it press a button physically, as the human contestants would. Even with a robotic finger pressing the buzzer, Watson remained faster than its human competitors.
A journalist who recorded Watson's development in his book Final Jeopardy, reported that the conflict between IBM and Jeopardy became so serious in May 2010 that the competition was almost canceled. As part of the preparation, IBM constructed a mock set in a conference room at one of its technology sites to model the one used on Jeopardy. Human players, including former Jeopardy contestants, also participated in mock games against Watson. About 100 test matches were conducted with Watson winning 65% of the games.
To provide a physical presence in the televised games, Watson was represented by an avatar of a globe, inspired by the IBM smarter planet symbol. The artist who designed the avatar for the project, explained that there are 36 triggerable states that Watson was able to use throughout the game to show its confidence in responding to a clue correctly; he had hoped to be able to find forty-two, to add another level to the Hitchhiker's Guide reference, but he was unable to pinpoint enough game states. In the end, Watson won, beating the two best human Jeopardy players.
IBM sees a future in which fields like medical diagnosis, business analytics, and tech support are automated by question-answering software like Watson.
According to some philosophers, Watson - despite impressive capabilities - cannot actually 5) ___. 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 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.
On January 30, 2013, it was announced that Rensselaer Polytechnic Institute would receive a successor version of Watson, which would be housed at the Institute's technology park and be available to researchers and students. By summer 2013, Rensselaer had become the first university to receive a Watson computer.
In November 2013, IBM announced it would make Watson's API available to software application providers, enabling them to build apps and services that are embedded in Watson's capabilities. To build out its base of partners who create applications on the Watson platform, IBM consults with a network of venture capital firms, which advise IBM on which of their portfolio companies may be a logical fit for what IBM calls the Watson Ecosystem. Thus far, roughly 800 organizations and individuals have signed up with IBM, with interest in creating applications that could use the Watson platform. On February 6, 2014, it was reported that IBM plans to invest $100 million in a 10-year initiative to use Watson and other IBM technologies to help countries in Africa address development problems, beginning with healthcare and education.
OmniEarth, Inc. uses Watson computer vision services to analyze satellite and aerial imagery, along with other municipal data, to infer water usage on a property-by-property basis, helping water districts in drought-stricken California improve water conservation efforts.
In September 2016, Conde Nast started using IBM's Watson to help build and strategize social influencer campaigns for brands. Using software built by IBM and Influential, Conde Nast's clients will be able to know which influencer's demographics, personality traits and more, best align with a marketer and the audience it is targeting.
In healthcare, Watson's natural language, hypothesis generation, and evidence-based learning capabilities are being investigated to see how Watson may contribute to clinical decision support systems and the increase in artificial intelligence in healthcare for use by medical professionals. To aid physicians in the treatment of their patients, once a physician 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 healthcare providers, research materials, clinical studies, journal articles and patient information.
The pharmaceutical or medical industry has involved production and lots of human resources (e.g. patient care) but with robotics, software guided medicine and also AI supported diagnostics there is a huge market for these classical industries to expand into. We're moving from linear problem solving to 6) ___ or scale-up models. When looking at Amazon as an example, it's clear that they were able to use technology to scale their business model. This so-called scalability is a very important aspect of digital business models. Basically, it means that you can generate more output per unit the more you sell; e.g. as a consultant you can generate 1 billed hour per 1 hour invested, this is a non-scaling business model. In contrast, a scaling business model would be an app. You program it once and afterwards you don't have to invest more hours but you get the revenues coming in. The input for maintenance and development are not growing proportional to the revenues you might get for this app as the app can have an unlimited number of users with potentially unlimited income while your costs can stay the same no matter how many people download and use your app.
In February 2011, it was announced that IBM would be partnering with Nuance Communications for a research project to develop a commercial product during the next 18 to 24 months, designed to exploit Watson's clinical decision support capabilities. Physicians at Columbia University would help to identify critical issues in the practice of 7) ___ where the system's technology may be able to contribute, and physicians at the University of Maryland would work to identify the best way that a technology like Watson could interact with medical practitioners to provide the maximum assistance. In September 2011, IBM and WellPoint (now Anthem) announced a partnership to utilize Watson's data crunching capability to help suggest treatment options to physicians. Then, in February 2013, IBM and WellPoint gave Watson its first commercial application, for utilization management decisions in lung cancer treatment at Memorial Sloan-Kettering Cancer Center.
IBM announced a partnership with Cleveland Clinic in October 2012. The company sent Watson to the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, where it increased its health expertise and assisted medical professionals in treating patients. The medical facility will utilize Watson's ability to store and process large quantities of 8) ___ to help speed up and increase the accuracy of the treatment process. In 2013, IBM and MD Anderson Cancer Center began a pilot program to further the center's mission to eradicate cancer. However, after spending $62 million, the project did not meet its goals and it has been stopped. On February 8, 2013, IBM announced that oncologists at the Maine Center for Cancer Medicine and Westmed Medical Group in New York have started to test the Watson supercomputer system in an effort to recommend treatment for lung 9) ___.
On July 29, 2016, IBM and Manipal Hospitals (a leading hospital chain in India) announced the launch of IBM Watson for Oncology, for cancer patients. This product provides information and insights to physicians and cancer patients to help them identify personalized, evidence-based cancer care options. Manipal Hospitals is the second hospital in the world to adopt this technology and first in the world to offer it to patients online as an expert second opinion through their website. On January 7, 2017, IBM and Fukoku Mutual Life Insurance entered into a contract for IBM to deliver analysis to compensation payouts via its IBM Watson Explorer AI, this resulted in the loss of 34 jobs and the company said it would speed up compensation payout analysis via analyzing claims and medical record and increase productivity by 30%. The company also said it would save in running costs.
IBM Watson Group
On January 9, 2014 IBM announced it was creating a business unit around Watson. 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 Engagement Advisor, and Watson Explorer. Watson Discovery Advisor will focus on research and development projects in pharmaceutical industry, publishing, and biotechnology, Watson Engagement Advisor will focus on self-service applications using insights on the basis of natural language questions posed by business users, and Watson Explorer will focus on helping enterprise users uncover and share data-driven insights based on federated search more easily. The company is also launching a $100 million venture fund to spur application development for cognitive applications. According to IBM, the cloud-delivered enterprise-ready Watson has seen its speed 10) ___ 24 times over a 2,300% improvement in performance and its physical size shrank by 90% - from the size of a master bedroom to three stacked pizza boxes.
ANSWERS: 1) questions; 2) assistant; 3) learning; 4) algorithms; 5) think; 6) exponential; 7) medicine; 8) information; 9) cancer; 10) increase