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IBM Watson

IBM Watson is a computer system capable of answering questions posed in natural language. It was developed as a part of IBM's DeepQA project by a research team, led by principal investigator David Ferrucci. Watson was named after IBM's founder and first CEO, industrialist Thomas J. Watson.

Description
), evolved machine learning capabilities, and optimized hardware available to developers and researchers. Software Watson uses IBM's DeepQA software and the Apache UIMA (Unstructured Information Management Architecture) framework implementation. The system was written in various languages, including Java, C++, and Prolog, and runs on the SUSE Linux Enterprise Server 11 operating system using the Apache Hadoop framework to provide distributed computing. Other than the DeepQA system, Watson contained several strategy modules. For example, one module calculated the amount to bet for Final Jeopardy, according to the confidence score on getting the answer right, and the current scores of all contestants. One module used the Bayes rule to calculate the probability that each unrevealed question might be the Daily Double, using historical data from the J! Archive as the prior. If a Daily Double is found, the amount to wager is computed by a 2-layered neural network of the same kind as those used by TD-Gammon, a neural network that played backgammon, developed by Gerald Tesauro in the 1990s. The parameters in the strategy modules were tuned by benchmarking against a statistical model of human contestants fitted on data from the J! Archive, and selecting the best one. which it uses to generate hypotheses, gather massive evidence, and analyze data. IBM master inventor and senior consultant Tony Pearson estimated Watson's hardware cost at about three million dollars. Its Linpack performance stands at 80 TeraFLOPs, which is about half as fast as the cut-off line for the Top 500 Supercomputers list. According to Rennie, all content was stored in Watson's RAM for the Jeopardy game because data stored on hard drives would be too slow to compete with human Jeopardy champions. The IBM team provided Watson with millions of documents, including dictionaries, encyclopedias and other reference material, that it could use to build its knowledge. == Operation ==
Operation
Watson parses questions into different keywords and sentence fragments in order to find statistically related phrases. The more algorithms 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. As a result, human players usually generate responses faster than Watson, especially to short clues. After signaling, Watson speaks with an electronic voice and gives the responses in Jeopardy! question format. The Jeopardy! staff used different means to notify Watson and the human players when to buzz, Watson was notified by an electronic signal and could activate the buzzer within about eight milliseconds. The humans tried to compensate for the perception delay by anticipating the light, but the variation in the anticipation time was generally too great to fall within Watson's response time. Watson did not attempt to anticipate the notification signal. == History ==
History
Development Since Deep Blue's victory over Garry Kasparov in chess in 1997, IBM had been on the hunt for a new challenge. In 2004, IBM Research manager Charles Lickel, over dinner with coworkers, noticed that the restaurant they were in had fallen silent. He soon discovered the cause of this evening's hiatus: Ken Jennings, who was then in the middle of his successful 74-game run on Jeopardy!. Nearly the entire restaurant had piled toward the televisions, mid-meal, to watch Jeopardy!. Intrigued by the quiz show as a possible challenge for IBM, Lickel passed the idea on, and in 2005, IBM Research executive Paul Horn supported Lickel, pushing for someone in his department to take up the challenge of playing Jeopardy! with an IBM system. Though he initially had trouble finding any research staff willing to take on what looked to be a much more complex challenge than the wordless game of chess, eventually David Ferrucci took him up on the offer. 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. InformationWeek described Kelly as "the father of Watson" and credited him for encouraging the system to compete against humans on Jeopardy!. By 2008, the developers had advanced Watson such that it could compete with Jeopardy! champions. During the game, Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage but was not connected to the Internet. as well as students from New York Medical College. Among the team of IBM programmers who worked on Watson was 2001 Who Wants to Be a Millionaire? top prize winner Ed Toutant, who himself had appeared on Jeopardy! in 1989 (winning one game). Jeopardy! Preparation In 2008, IBM representatives communicated with Jeopardy! executive producer Harry Friedman 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. Stephen Baker, 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 cancelled. 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. Jennings described the computer's avatar as a "glowing blue ball crisscrossed by 'threads' of thought—42 threads, to be precise", and stated that the number of thought threads in the avatar was an in-joke referencing the significance of the number 42 in Douglas Adams' ''Hitchhiker's Guide to the Galaxy''. First match The first round was broadcast February 14, 2011, and the second round, on February 15, 2011. The right to choose the first category had been determined by a draw won by Rutter. Watson, represented by a computer monitor display and artificial voice, responded correctly to the second clue and then selected the fourth clue of the first category, a deliberate strategy to find the Daily Double as quickly as possible. Watson's guess at the Daily Double location was correct. At the end of the first round, Watson was tied with Rutter at $5,000; Jennings had $2,000. Watson also demonstrated complex wagering strategies on the Daily Doubles, with one bet at $6,435 and another at $1,246. Watson took a commanding lead in Double Jeopardy!, correctly responding to both Daily Doubles. Watson responded to the second Daily Double correctly with a 32% confidence score. However, during the Final Jeopardy! round, Watson was the only contestant to miss the clue in the category U.S. Cities ("Its largest airport was named for a World War II hero; its second largest, for a World War II battle"). Rutter and Jennings gave the correct response of Chicago, but Watson's response was "What is Toronto?????" with five question marks indicating a lack of confidence. Ferrucci offered reasons why Watson would appear to have guessed a Canadian city: categories only weakly suggest the type of response desired, the phrase "U.S. city" did not appear in the question, there are cities named Toronto in the U.S., and Toronto in Ontario has an American League baseball team. Chris Welty, who also worked on Watson, suggested that it may not have been able to correctly parse the second part of the clue, "its second largest, for a World War II battle" (which was not a standalone clause despite it following a semicolon, and required context to understand that it was referring to a second-largest airport). Eric Nyberg, a professor at Carnegie Mellon University and a member of the development team, stated that the error occurred because Watson does not possess the comparative knowledge to discard that potential response as not viable. The game ended with Jennings with $4,800, Rutter with $10,400, and Watson with $35,734. In the first round, Jennings was finally able to choose a Daily Double clue, while Watson responded to one Daily Double clue incorrectly for the first time in the Double Jeopardy! Round. After the first round, Watson placed second for the first time in the competition after Rutter and Jennings were briefly successful in increasing their dollar values before Watson could respond. Nonetheless, the final result ended with a victory for Watson with a score of $77,147, besting Jennings who scored $24,000 and Rutter who scored $21,600. Final outcome The prizes for the competition were $1 million for first place (Watson), $300,000 for second place (Jennings), and $200,000 for third place (Rutter). As promised, IBM donated 100% of Watson's winnings to charity, with 50% of those winnings going to World Vision and 50% going to World Community Grid. Similarly, Jennings and Rutter donated 50% of their winnings to their respective charities. In acknowledgement of IBM and Watson's achievements, Jennings made an additional remark in his Final Jeopardy! response: "I for one welcome our new computer overlords", paraphrasing a joke from The Simpsons. Jennings later wrote an article for Slate, in which he stated: IBM has bragged to the media that Watson's question-answering skills are good for more than annoying Alex Trebek. The company sees a future in which fields like medical diagnosis, business analytics, and tech support are automated by question-answering software like Watson. Just as factory jobs were eliminated in the 20th century by new assembly-line robots, Brad and I were the first knowledge-industry workers put out of work by the new generation of 'thinking' machines. 'Quiz show contestant' may be the first job made redundant by Watson, but I'm sure it won't be the last. Drawing on his Chinese room thought experiment, Searle claims that Watson, like other computational machines, is capable only of manipulating symbols, but has no ability to understand the meaning of those symbols; however, Searle's experiment has its detractors. Match against members of the United States Congress On February 28, 2011, Watson played an untelevised exhibition match of Jeopardy! against members of the United States House of Representatives. In the first round, Rush D. Holt, Jr. (D-NJ, a former Jeopardy! contestant), who was challenging the computer with Bill Cassidy (R-LA, later Senator from Louisiana), led with Watson in second place. However, combining the scores between all matches, the final score was $40,300 for Watson and $30,000 for the congressional players combined. IBM's Christopher Padilla said of the match, "The technology behind Watson represents a major advancement in computing. In the data-intensive environment of government, this type of technology can help organizations make better decisions and improve how government helps its citizens." == Applications ==
Applications
After the national press attention gained by the 2011 Jeopardy! appearance, IBM sought out partnerships from education to weather and cancer to retail chatbots in order convince business about Watson's alleged capabilities. This ultimately led to the failure of Watson to find a profit-making product for the company. In 2011, the IBM general counsel wrote in The National Law Review arguing that the law profession will become more efficient and better with Watson. After the national attention Jeopardy! afforded them, began an ultimately unsuccessful and expensive project that began when the Memorial Sloan Kettering Cancer Center tried to use Watson to help doctors diagnose and treat cancer patients. Ultimately, the division cost $4 billion to develop but was sold for a quarter of that—$1 billion, in 2022. By 2023, Watson resulted in IBM losing 10% of its stock value, costing four times more than what it brought to the company and resulting in mass layoffs. • retail shopping, • medical equipment purchasing, • cooking and recipes, • water conservation, • hospitality management, • human genetic sequencing, • weather forecasting • to sell ads with weather forecasts, • to tutor students, • and tax preparations, In 2021, technology reporter at The New York Times for Steve Rohr, explained: Writing in The Atlantic in 2023, Mac Schwerin argued that IBM's leadership fundamentally did not understand the technology, leading to the hardship and strain caused by the project, saying: In the end, IBM's initial vision for Watson as a transformative technology capable of revolutionizing industries did not materialize as anticipated. Watson's capabilities were primarily suited to specific tasks, like natural language processing for trivia games, rather than generalized commercial problem-solving. Watson's mismatch between capabilities and IBM's marketing contributed significantly to Watson's commercial struggles and eventual decline. The overstated claims about Watson's abilities also caused public sentiment to turn against the idea of Watson and artificial intelligence. When a physician submitted a query to Watson, the system started a multi-step process by parsing the input to identify key information, examining patient data to uncover relevant medical and hereditary history, and finally compare various data sources to form and test hypotheses. In fact, a study of 1,000 challenging patient cases found that Watson's recommendations matched those of human doctors in an impressive 99% of cases. IBM established partnerships with the Cleveland Clinic, and in 2013, Watson was deployed in its first commercial application for utilization management decisions in lung cancer treatment at Memorial Sloan-Kettering Cancer Center. The Cleveland Clinic collaboration aimed to enhance Watson's health expertise and support medical professionals in treating patients more effectively. However, the MD Anderson Cancer Center pilot program, initiated in 2013, ultimately failed to meet its goals and was discontinued after $65 million in investment. In 2016, IBM launched "IBM Watson for Oncology", a product designed to provide personalized, evidence-based cancer care options to physicians and patients. The company ultimately faced challenges in the healthcare market, with no profit and increased competition. IBM Watson Group will have headquarters in New York City'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. In 2017, IBM and MIT established a new joint research venture in artificial intelligence. IBM invested $240 million to create the MIT–IBM Watson AI Lab in partnership with MIT, which brings together researchers in academia and industry to advance AI research, with projects ranging from computer vision and NLP to devising new ways to ensure that AI systems are fair, reliable and secure. In March 2018, IBM's CEO Ginni Rometty proposed "Watson's Law", the "use of and application of business, smart cities, consumer applications and life in general." == See also ==
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