Computer Science. The English Language Perspective - Беликова (1176925), страница 40

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There is no widespread agreement yet on exactly whatComputational intelligence (CI) is, but it is agreed that itincludes neural networks and fuzzy computing.2. Answer the following questions:1.2.3.4.5.6.7.What are the ways to classify Artificial Intelligence?How does an expert system work?What are the four steps in case-based reasoning?What tasks do the layers of a BBAI system perform?Where are Bayesian networks applied?What are the working principles of a neural network?How does fuzzy logic differ from Boolean logic?3. Translate into English:Эпименид Кносский с острова Крит – полумифическийпоэт и философ, живший в VI в. до н.э., однажды заявил:«Все критяне – лжецы!».

Так как он и сам был критянином,то его помнят как изобретателя так называемого критскогопарадокса.237В терминах аристотелевой логики, в которойутверждение не может быть одновременно истинным иложным, и подобные самоотрицания не имеют смысла.Если они истинны, то они ложны, но если они ложны, тоони истинны.И здесь на сцену выходит нечеткая логика, гдепеременные могут быть частичными членами множеств.Истинность или ложность перестают быть абсолютными –утверждения могут быть частично истинными и частичноложными.

Использование подобного подхода позволяетстрого математически доказать, что парадокс Эпименидаровно на 50% истинен и на 50% ложен.Таким образом, нечеткая логика в самой своей основенесовместима с аристотелевой логикой, особенно вотношении закона Tertium non datur («Третьего не дано» –лат.), который также называют законом исключения среднего.Если сформулировать его кратко, то звучит он так: еслиутверждение не является истинным, то оно являетсяложным. Эти постулаты настолько базовые, что их частопросто принимают на веру.Более банальный пример пользы нечеткой логикиможно привести в контексте концепции холода.Большинство людей способно ответить на вопрос:«Холодно ли вам сейчас?».

В большинстве случаев людипонимают, что речь не идет об абсолютной температуре пошкале Кельвина. Хотя температуру в 0 K можно, безсомнения, назвать холодом, но температуру в +15 C многиехолодом считать не будут.Но машины не способны проводить такую тонкуюградацию. Если стандартом определения холода будет«температура ниже +15 C», то +14,99 C будет расцениватьсякак холод, а +15 C – не будет!4. Give the summary of the text using the key terms.238CURRENT TRENDSRead the following words and word combinations and usethem for understanding and translation of the text:hype - навязчивая (агрессивная) реклама, рекламнаяшумиха, раскруткаacquisitions - приобретениеbuzz word - модное словцоcognitive computing - когнитивные вычисления,познавательные вычисленияpredictive analytics - прогнозная аналитикаtwo-voice counterpoint - двухголосая полифония(контрапункт)visual cue - визуальная подсказкаto underpin - лежать в основеbig data - большие данные, супермассив данныхto sift through - перелопатитьevidence - реальные факты, полученные сведенияto leverage - выгодно использовать, по-новому применятьrelevantinformationнеобходимая(актуальная)информацияIt looks like the beginning of a new technology hype forartificial intelligence (AI).

The media has started flooding thenews with product announcements, acquisitions, andinvestments. AI is capturing the attention of tech firm andinvestor giants such as Google, Microsoft, and IBM. The buzzwords are great too: cognitive computing, deep learning, AI2.For those who started their careers in AI and left indisillusionment or data scientists today, the consensus is oftenthat artificial intelligence is just a new fancy marketing term forgood old predictive analytics. They point to the reality ofApple’s Siri to listen and respond to requests as adequate butmore often frustrating.

Or, IBM Watson’s win on Jeopardy asdata loading and brute force programming.239But, is this fair? No. New AI breaks the current rule thatmachines must be better than humans: they must be smarter,faster analysts, or manufacture things better and cheaper.New AI says: The question is sometimes more important than the answer.Suggestions don’t always need to be answers, they canbe questions.

Eric Horvitz of Microsoft told MITTechnology Review, “…Another possibility is to buildsystems that understand the value of information,meaning they can automatically compute what the nextbest question to ask is....” Improvisation is the true meaning of adaptation. Search on‘artificial intelligence’ and ‘improvisation’ and you get alot of examples of AI being linked to music. The head ofFacebook’s AI lab and musician, Yan Lecun, says,“Ihave always been interested in Jazz because I havealways been intrigued by the intellectual challenge ofimprovising music in real time”. Linking the two, hewrote a program that automatically composed twovoice counterpoint for a college artificial intelligenceproject. Collaboration produces better results. Guy Hoffman at theMedia Innovation Lab, School of Communication, IDCHerzliya introduced a robot that could not onlycompose music independently, but also collaborate withanother musician (Guy himself) to create a new piece ofmusic.

The robot provided visual cues, reacting andcommunicating the effect of the music and creativeprocess for lifelike interaction between robot andcomposer.This is game changing, both in how organizations operate andstrategize as well as the impact on customer experience. Thesethree principles are the foundation for customer andorganizational engagement. Today AI is like a super smartmagic eight ball. Tomorrow AI supports and creates a dialog240between companies and customers, managers and employees,and business to business.We’re now seeing the emergence of cognitive computing, anew era of computing systems that will understand the worldin the way that humans do: through senses, learning, andexperience.These new cognitive systems will help us think. They will relateto us and answer questions using the language we humans useevery day.

They will learn from their interactions with data andwith us, basically adapting their behavior automatically basedon new knowledge.That’s what makes this third major era of computing such ahuge leap forward. The first era was made up of tabulatingmachines and the second of programmable computers.

Whilethe programmable era will continue perhaps indefinitely andcertainly underpin the next era of computing, cognitive systemsrepresent a whole new approach to solving complex data andinformation analysis problems that goes beyond justcomputing.Data is available everywhere, all the time. It’s piling up, simplywaiting to be used. Which is why we need computing systemsthat we can interact with using human language, rather thanprogramming language. We need computers that can dish upadvice, rather than waiting for commands.How will these systems work? IBM Watson, one of the firstsystems built as a cognitive computing system, applies deepanalytics to text and other unstructured big data sources to pullmeaning out of the data by using inference, probability, andreasoning to solve complex problems.

Watson is a first steptoward cognitive computing, expanding the reaches of humanunderstanding by helping us quickly and efficiently siftthrough massive amounts of data, pinpointing the informationand insights that are now trapped within these sources.Watson does this by using hundreds of analytics, whichprovide it with capabilities such as natural languageprocessing, text analysis, and knowledge representation and241reasoning to make sense of huge amounts of complexinformation in split seconds, rank answers based on evidenceand confidence, and learn from its mistakes.

And, of course,this capability is deployed in the cloud and made available toapplications as a cognitive service.One of the first domains for Watson is healthcare. ClevelandClinic is working to explore how Watson can be used to betterleverage valuable information trapped in large electronic healthrecords. Watson’s analytics can sift through unstructuredclinical notes in a patient’s health record, reason over thatinformation, and connect it with other structured information inthe health record to produce summaries, deeper insights, andfaster access to relevant information.A new application of Watson, called WatsonPaths, is able toanalyze complex medical scenarios and propose relationshipsand connections to possible diagnoses extracted from theunderlying medical literature.

Medical students can interactwith WatsonPaths to both learn from Watson and teach Watsonby grading Watson’s recommendations."Right now the science of cognitive computing is in theformative stages," says IBM Research's Ton Engbersen. "Tobecome machines that can learn, computers must be able toprocess sensory as well as transactional input, handleuncertainty, draw inferences from their experience, modifyconclusions according to feedback, and interact with people in anatural, human-like way."Watson is a first step, but it points to what will be possible andhow the age of cognitive computing will transform how wework with computers and what we expect out of them, helpingremake our industries, economies and societies.Notes:deep learning is a set of algorithms in machine learning thatattempt to model high-level abstractions in data by usingarchitectures composed of multiple non-linear transformations.[242brute force programming - программирование методом"грубой силы", неэффективный с точки зрениярасходованиявычислительныхресурсовстильпрограммирования, решение "в лоб", когда программистполагается только на производительность компьютера,вместо того чтобы попытаться упростить задачу, - поэтомупрограммы получаются громоздкими, тяжеловесными,неэлегантными.

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