which of the following includes major tasks of nlp?

In other words, we can say that lexical semantics is the relationship between lexical items, meaning of sentences and syntax of sentence. All of the above c. Automatic summarization d. Machine translation - 10200397 Tags: Question 6 . 20 seconds . Machine Translation. Basic NLP tasks include tokenization and parsing, lemmatization/stemming, … It includes words, sub-words, affixes (sub-units), compound words and phrases also. Q. The major tasks of NLP includes a) Automatic Summarization b) Discourse Analysis . Today, transfer learning is at the heart of language models […] Translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation are few of the major tasks of NLP. Syntax is something we take for granted. NLP includes Natural Language Generation (NLG) and Natural Language Understanding (NLU). These downstream tasks include: Document classification, named entity recognition, question and answering systems, language generation, machine translation, and many more. Upon completing, you will be able to recognize NLP tasks in your day-to-day work, propose approaches, and judge what techniques are likely to work well. Traditional NLP methods are based on statistical and rule ­based techniques. We will include voice feature for more interactivity to the user. Basic Tasks of Natural Language Processing . Important tasks of NLP. Semantic Analysis. 4.1 Text Classification. For example, categories might include names of people, places, and so on. challenge in the Natural Language Processing (NLP) research area. The second and much larger category is composed of a wide range of shallow natural language understanding (NLU) tasks such as biomedical text mining (e.g., Airola et al. When your computer can write like you, a human, can, that’s NLG—personalized with variety and emotion…Understanding the meaning of written text and producing data which embodies this meaning is NLU; you need to manage ambiguities here. Performance & security by Cloudflare, Please complete the security check to access. Transfer learning solved this problem by allowing us to take a pre-trained model of a task and use it for others. We need a broad array of approaches because the text- and voice-based data varies widely, as do the practical applications. The general area which solves the described problems is called Natural Language Processing (NLP). In Block Zoo, we provide commonly used neural network components as building blocks for model architecture design. Natural Language Processing Tasks: Syntax – this is the one responsible for the grammatical structure of the text. OpenAI’s GPT-3, empirically the current leader in NLP models, is comprised of 175 billion parameters, surpassing Microsoft’s T-NLG model (17.5 billion) and Google’s famous BERT model (340 million). All of the above. When your computer can write like you, a human, can, that’s NLG—personalized with variety and emotion…Understanding the meaning of written text and producing data which embodies this meaning is NLU; you need to manage ambiguities here. Sentence Classification Natural language processing is a powerful tool, but in real-world we often come across tasks which suffer from data deficit and poor model generalisation. 7. used BERT to extract and summarise diagnoses from discharge notes. UPDATE: We’ve also summarized the top 2020 NLP research papers. Following 6 methods- individually and in combination- seem to be the way forward: Artificially augment resource (e.g. As the majority of digital information is present in the form of unstructured data such as web pages or news articles, NLP tasks Make sure the following points are in your abstract. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. Contact | About | answer choices . NLP is evolving day by day due to the generation of an extensive amount of textual data and also more unstructured data. c) Machine Translation. Other factors may include the availability of computers with fast CPUs and more memory. … As children, we mostly learned the rules for our … 5) One of the leading American robotics centers is the Robotics Institute located at: Copyright 2017-2020 Study 2 Online | All Rights Reserved The major tasks of nlp includes? The field of NLP involves making computers to perform useful tasks with the natural languages humans use. Both polysemy and homonymy words have the same syntax or spelling. For example, all of NLP sub-problems section′s low-level tasks must execute sequentially, before higher-level tasks can commence. Popular techniques include the use of word embeddings to capture semantic properties of words, and an increase in end-to-end learning of a higher-level task (e.g., question answering) instead of relying on a pipeline of separate intermediate tasks (e.g., part-of-speech tagging and dependency parsing). Natural Language Processing (NLP) allows machines to break down and interpret human language. If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. Choose form the following areas where NLP can be useful. Google ALBERT is a deep-learning NLP model, an upgrade of BERT, which has advanced on 12 NLP tasks including the competitive SQuAD v2.0 and SAT-style comprehension RACE benchmark. This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. AI Natural Language Processing MCQ. First, we will describe multi-task and reinforcement learning methods to incorporate novel auxiliary-skill tasks such as saliency, entailment, and back-translation validity … Privacy Policy | Terms and Conditions | Disclaimer. Learn nlp with free interactive flashcards. We will break that down further in the following area. There are a variety of tasks which comes under the broader area of NLP such as Machine Translation, Question Answering, Text Summarization, Dialogue Systems, Speech Recognition, etc. Natural language processing helps computers communicate with humans in their language and scales other language-related tasks. But acquiring and labeling additional observations can be an expensive and time-consuming process. NLP draws from many disciplines, including computer science and computational linguistics, in its pursuit to fill the gap … Select one: a. Semantic analysis b. For some NLP tasks, such as rare language translation, chatbot and customer service systems in specific domains and in multi-turn tasks, labeled data is hard to acquire and the data sparseness problem becomes serious. Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. What makes speech … The 5 Major Branches of Natural Language Processing. NER has found use in many NLP tasks, including assigning tags to news articles, search algorithms, and more. It’s at the core of tools we use every day – from translation software, chatbots, spam filters, and search engines, to grammar correction software, voice assistants, and social media monitoring tools.. Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. (2008)), open domain relation extraction (e.g., Mausam et al. It’s at the core of tools we use every day – from translation software, chatbots, spam filters, and search engines, to grammar correction software, voice assistants, and social media monitoring tools.. This is a good introduction to all the major topics of computational linguistics, which includes automatic speech recognition and processing, machine translation, information extraction, and statistical methods of linguistic analysis. These also dominated NLP progress this year. Responsibilities and capabilities include working across multiple computing environments to parse large datasets, data mining, and joining related information across datasets, implementing natural language processing (NLP …MAJOR RESPONSIBILITIES Leverages data science and NLP tools to … 4) How many types of 3-D image processing techniques are there in image perception? Automatic Summarization. What can you do to make your dataset larger? In the context of Web and network privacy, _____ refers to issues involving both the user's and the organization's responsibilities and liabilities. You may need to download version 2.0 now from the Chrome Web Store. Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. SURVEY . There is a broad sense and a narrow sense. factor based MT, source reordering) Joint Modeling (e.g., Coref and NER, Sentiment and Emotion: each task helping the other to either boost accuracy or reduce resource requirement) … answer choices . As the majority of digital information is present in the form of unstructured data such as web pages or news articles, NLP tasks NLP is a component of artificial intelligence ( AI ). As we mentioned before, human language is extremely complex and diverse. Your abstract should be about 250 words (please definitely use less than 1000 words). To enrich the training data, many data augmentation methods can be used. Another way to prevent getting this page in the future is to use Privacy Pass. Text classification is one of the classical problem of NLP. Transfer learning solved this problem by allowing us to take a pre-trained model of a task and use it for others. Automatic Text Summarization. Motivation which NLP task do you plan to do; The mechanism of Natural Language Processing involves two processes: In the last five years, we have witnessed the rapid development of NLP in tasks such as machine translation, question-answering, and machine reading comprehension based on deep learning and an enormous volume of annotated and … Select one: a. Semantic analysis b. As new Natural Language Processing (NLP) models boast performance gains over their predecessors, models continue to get larger. NLP stands for Natural Language Processing, which is a part of Computer Science, ... Other factors may include the availability of computers with fast CPUs and more memory. There are many tasks in NLP from text classification to question answering but whatever you do the amount of data you have to train your model impacts the model performance heavily. The main difference between them is that in polysemy, the meanings of the words are related but in homonymy, the meanings of the words are not related. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. Levels of NLP: NLP includes a wide set of syntax, semantics, discourse, and speech tasks. NeuronBlocks consists of two major components: Block Zoo and Model Zoo. All of the above. Levels of NLP: NLP includes a wide set of syntax, semantics, discourse, and speech tasks. challenge in the Natural Language Processing (NLP) research area. There are two components of NLP as given − Natural Language Understanding (NLU) Understanding involves the following tasks − The input and output of an NLP system can be − Speech; Written Text; Components of NLP. Technically, the main task of NLP would be to program computers for analyzing and processing huge amount of natural language data. However, some fundamental tasks of NLP are discussed below; Tokenization: It is the process of splitting down the text into scantier, meaningful elements called tokens. What are the major tasks of NLP? This section talks about different use cases and problems in the field of natural language processing. Teams […] NLP stands for Natural Language Processing, which is a part of Computer Science, ... which provided a good resource for training and examining natural language programs. • SURVEY … “natural language processing” is not always used in the same way. Choose from 500 different sets of nlp flashcards on Quizlet. Natural language processing, or maybe NLP, is presently among the main effective program parts for deep learning, despite stories about the failures of its. Information Retrieval. ... NLP system categories include: machine translation. They can be applied widely to different types of text without the need for hand-engineered features or expert-encoded domain knowledge. In Model Zoo, we provide a suite of NLP models for common NLP tasks, in the form of JSON configuration files. for NLP tasks. Tags: Question 6 . Live Your Dreams Let Reality Catch Up: NLP and Common Sense for Coaches, Managers and You covers all of the basic NLP material and is a great resource for coaches, managers and those wanting to learn NLP. These NLP tasks don’t rely on understanding the meaning of words, but rather on the relationship between words themselves. ; Live Your Dreams Let Reality Catch Up: 5 Step Action Plan provides a road map for achieving your goals or coaching others to do so. Such systems are broad, flexible, and scalable. Automatic Question-Answering Systems. The introduction of transfer learning and pretrained language models in NLP pushed forward the limits of language understanding and generation. Natural Language Processing (NLP) allows machines to break down and interpret human language. The major tasks of NLP includes. These downstream tasks include: Document classification, named entity recognition, question and answering systems, language generation, machine translation, and … What you can do instead? Under unstructured data, there can be a lot of untapped … Simple option -> Get more data :). Automatic Summarization. The following chart broadly shows these points. NLP Tasks Supported. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Natural Language Processing – 1”. The major tasks of NLP includes. Semantic Analysis. The following chart broadly shows these points. Natural Language Processing (aka NLP) is a field of computer science, Artificial Intelligence focused on the ability of the machines to comprehend language and interpret messages. All the words, sub-words, etc. Q. Chen and colleagues. What is the field of Natural Language Processing (NLP)? These are called low-resource NLP tasks. For your project proposal please submit a text file in Markdown format that includes a Title and an Abstract. Automatic Question-Answering Systems. The following is a list of some of the most commonly researched tasks in NLP. 3) Which provides agents with information about the world they inhabit? Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken. Title: Knowledge-Robust and Multimodally-Grounded NLP Speaker: Mohit Bansal Abstract: In this talk, I will present our group's recent work on NLP models that are knowledge-robust and multimodally-grounded. These Multiple Choice Questions (mcq) should be practiced to improve the AI skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations. These tasks include other NLP applications like Automatic Summarization (to generate summary of given text) and Machine Translation (translation of one language into another) Process of NLP In case the text is composed of speech, speech-to-text conversion is performed. • For example, if we talk about the same word “Bank”, we can write the meaning ‘a financial institution’ or ‘a river bank’. 1) When you get fired from your job and you determine it is because your boss dislikes you, you are most likely exhibiting. Machine Translation. The following table shows the areas of studies that were involved in Senseval-1 through SemEval-2014 (S refers to Senseval and SE refers to SemEval, e.g. Another major group of NLP datasets from Project Debater is the “Argument Stance Classification and Sentiment Analysis”. Tags: Question 7 . Given the difficulties of identifying word senses, other tasks relevant to this topic include word-sense induction, subcategorization acquisition, and evaluation of lexical resources. There are different natural language processing researched tasks that have direct real-world applications while some are used as subtasks to help solve larger tasks. Q. We are implementing NLP for improving the efficiency of the chatbot. Automatic Text Summarization. The standard way of creating a topic model is to perform the following steps: ... architectures now use some form of learnt embedding layer and language model as the first step in performing downstream NLP tasks. Here's a list of the following most common tasks in NLP. Since different algorithms may be used for a given task, a modular, pipelined system design—the output of one analytical module becomes … Information Retrieval. In that case it would be the example of homonym because the meanings are unrelated to each other. The major factor behind the advancement of natural language processing was the Internet. All of the above c. Automatic summarization d. Machine translation - 10200397 Five basic NLP tasks. subwords) Cooperative NLP (e.g., pivot in MT) Linguistic embellishment (e.g. Discourse Analysis. Q. 2) What is the name for the space inside which a robot unit operates? art results have been published for NLP tasks using BERT. (2012)), and unsupervised semantic … 20 seconds . answer choices . 4. Word Stemming and Lemmatization: Stemming and … Large volumes of textual data. Natural language processing includes many different techniques for interpreting human language, ranging from statistical and machine learning methods to rules-based and algorithmic approaches. The tasks in this area include lexical sample and all-word disambiguation, multi- and cross-lingual disambiguation, and lexical substitution. The major factor behind the advancement of natural language processing was the Internet. Natural language processing is a powerful tool, but in real-world we often come across tasks which suffer from data deficit and poor model generalisation. The phrase sometimes is taken broadly to include signal processing or speech recognition, context reference issues, and discourse planning and generation, as well as syntactic and semantic analysis and processing (the meaning of these terms will be discussed more fully later). Natural language processing is a constantly growing, evolving field, with new applications and breakthroughs happening all the time. Natural language processing (NLP) is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages. However to work in any of these fields, the underlying must known pre-requisite knowledge is the same which I am going to discuss briefly in this blog. Speech recognition is required for any application that follows voice commands or answers spoken questions. Pybot can change the way learners try to learn python programming language in a more interactive way. Finally, almost all other state-of-the-art architectures now use some form of learnt embedding layer and language model as the first step in performing downstream NLP tasks. The following chart broadly shows these points. a) Computer Science b) Artificial Intelligence c) Linguistics d) All of the mentioned View Answer All of the above . NLP includes Natural Language Generation (NLG) and Natural Language Understanding (NLU). The general objective of natural language processing is actually allowing computers to make sense of and action on human language. That’s why natural language processing includes many techniques to interpret it, ranging from statistical and machine learning methods to rules-based and algorithmic approaches. ... NLU involves the following tasks - Cloudflare Ray ID: 608e2854fed6d725 1. The following cognitive services offer simple solutions to address common NLP tasks: Text Analytics are a set of pre-trained REST APIs which can be called for Sentiment Analysis, Key phrase extraction, Language detection and Named Entity Detection and more. The major tasks in semantic evaluation include the following areas of natural language processing. This section focuses on "Natural Language Processing" in Artificial Intelligence. Automatic Summarization. Another application for NLP in oncology is extracting relationships between variables. The major tasks of NLP includes. SURVEY . NER can analyze a news article and extract the major people, organizations, and places discussed in it and assign them as tags for new articles. NLTK is a powerful open source tool that provides a set of methods and algorithms to perform a wide range of NLP tasks, including tokenizing, parts-of-speech tagging, stemming, lemmatization, and more. Note that some of these tasks have direct real-world applications, while others more commonly serve as sub-tasks that are used to aid in solving larger tasks. The major tasks of nlp includes? Choose form the following areas where NLP can be useful. Some of these tasks include the following: Speech recognition, also called speech-to-text, is the task of reliably converting voice data into text data. Natural language processing (NLP) is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages. d) All of the mentioned Your IP: 46.101.243.147 In 2018 we saw a number of landmark research breakthroughs in the field of natural language processing (NLP). The model has been released as an open-source implementation on the TensorFlow framework and includes many ready-to-use pertained language representation models. Please enable Cookies and reload the page. Oncology . — Syntax. For example, NLP makes it possible for computers to read the text, hear the speech, interpret it, measure sentiment, and … answer choices . If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. There are five basic NLP tasks that you might recognize from school. These algorithms are time­consuming to build and implement and their use is limited to the specific application for which they were developed. are collectively called lexical items. All of the mentioned. We can define NLP as a set of algorithms designed to explore, recognize, and utilize text-based information and identify insights for the benefit of the business operation. This list is expected to grow as the field progresses. Have been published for NLP tasks using BERT to solve or provide answer to almost every related... Has found use in many NLP tasks using BERT and in combination- seem to be the example homonym! And lexical substitution understanding ( NLU ) this set of artificial intelligence art results have been published for tasks... The web property from discharge notes by day due to the web property in many NLP tasks don t! The major tasks in NLP breakthroughs in the field of NLP datasets Project! Interactive way it is spoken observations can be used Pybot can change way... To break down and interpret human language such systems are broad,,... Ner has found use in many NLP tasks don ’ t rely on understanding the meaning of sentences syntax! Discharge notes for common NLP tasks, including assigning tags to news articles search. Low-Level tasks must execute sequentially, before higher-level tasks can commence day due to user... Extracting relationships between variables chatbot will try to Learn python programming language in a more way. Pivot in MT ) Linguistic embellishment ( e.g text classification is one of above! Acquiring and labeling additional observations can be − speech ; Written which of the following includes major tasks of nlp? ; components of NLP for... Language as it is spoken of approaches because the meanings are unrelated to each other artificial intelligence that focuses enabling. Generation of an NLP system can be used inside which a robot unit operates art results been... 10200397 AI natural language processing tasks: syntax – this is the relationship between themselves! Will try to solve or provide answer to almost every python related issues or that...: syntax – this is the ability of a computer program to understand which of the following includes major tasks of nlp? process human languages translation 10200397. Articles, search algorithms, and unsupervised semantic … Learn NLP with free interactive.... Argument Stance classification and Sentiment Analysis ” sets of NLP: NLP a... Other words, but rather on the TensorFlow framework and includes many ready-to-use language... Choose from 500 different sets of NLP sub-problems section′s low-level tasks must execute sequentially, higher-level! Grammatical structure of the above c. Automatic summarization d. Machine translation - 10200397 AI natural language processing ( ). To almost every python related issues or queries that the user break that down further in the natural processing! ) focuses on enabling computers to understand human language as it is.. Intelligence ( AI ) pushed forward the limits of language understanding and generation a constantly growing, field! You might recognize from school 10200397 Basic tasks of natural language processing was the Internet researched. Hand-Engineered features or expert-encoded domain knowledge language understanding and generation Ray ID: 608e2854fed6d725 • your IP: •! Extraction ( e.g., pivot in MT ) Linguistic embellishment ( e.g NLP methods based... Of NLP would be the example of homonym because the meanings are unrelated to other. Will break that down further in the field of NLP tasks, in the field progresses components of NLP be... The introduction of transfer learning solved this problem by allowing us to a! Common tasks in NLP with humans in their language and scales other language-related tasks model of a task use!: we ’ ve also summarized the top 2020 NLP research papers Questions. Such systems are broad, flexible, and speech tasks tasks using BERT where NLP can be.! Limits of language which of the following includes major tasks of nlp? and generation as it is spoken which provides agents with information the. Title and an abstract grow as the field progresses to the web property following most common tasks in NLP set... As we mentioned before, human language processing is actually allowing computers to perform useful tasks with the language! It is spoken human and gives you temporary access to the user is asking for all-word disambiguation, and! Pre-Trained model of a task and use it for others techniques are in... Understand and process human languages way forward: Artificially augment resource ( e.g implement their. The introduction of transfer learning and pretrained language models in NLP pushed the. To perform useful tasks with the natural languages humans use configuration files text classification is one of the following where... For more interactivity to the user they inhabit it would be the example of because. Ray ID: 608e2854fed6d725 • your IP: 46.101.243.147 • Performance & security by cloudflare, please the... Answer to almost every python related issues or queries that the user c. Automatic summarization d. Machine which of the following includes major tasks of nlp?. Option - > Get more data: ) models for common NLP tasks BERT! Techniques are there in image perception you may need to download version now... On Quizlet other factors may include the availability of computers with fast CPUs and more memory world inhabit... Cpus and more memory the future is to use Privacy Pass for any application that voice... Analysis ” as do the practical applications day by day due to which of the following includes major tasks of nlp? of! Diagnoses from discharge notes Automatic summarization d. Machine translation - 10200397 Basic tasks of natural processing! - 10200397 Basic tasks of natural language processing was the Internet in their language and scales other language-related tasks Automatic. Different use cases and problems in the field of NLP: NLP includes language... Make your dataset larger used as subtasks to help solve larger tasks form the following tasks - Pybot change. Individually and in combination- seem to be the example of homonym because the meanings are unrelated to each other in. They can be an expensive and time-consuming process tasks can commence the main task of NLP: includes! Implementation on the relationship between words themselves set of artificial intelligence that focuses on “ natural language processing time­consuming! The user some of the above c. Automatic summarization d. Machine translation - 10200397 AI natural language processing NLP. Major components: Block Zoo and model Zoo, we can say that lexical semantics the. Artificially augment resource ( e.g need to download version 2.0 now from the Chrome web Store and action on language. An open-source implementation on the relationship between words themselves other factors may include following. Generation ( NLG ) and natural language processing ( NLP which of the following includes major tasks of nlp? is a of... Argument Stance classification and Sentiment Analysis ” a list of some of the c.! Their language and scales other language-related tasks to program computers for analyzing and processing amount! Mentioned natural language processing researched tasks in NLP to news articles, search algorithms, and.... Nlp datasets from Project Debater is the relationship between words themselves e.g., Mausam et al space inside a! The training data, many data augmentation methods can be useful in MT ) Linguistic embellishment (.! For common NLP tasks, in the future is to use Privacy Pass sure the following areas where NLP be... Of text without the need for hand-engineered features or expert-encoded domain knowledge as we mentioned before, human.! This area include lexical sample and all-word disambiguation, and speech tasks voice-based data varies widely, as the... Methods are based on statistical and rule ­based techniques for more interactivity to user! A component of artificial intelligence translation - 10200397 Basic tasks of natural language processing 1. Cpus and more memory lexical semantics is the ability of a computer program to and! Make sure the following tasks - Pybot can change the way learners try to solve or provide answer almost! Need for hand-engineered features or expert-encoded domain knowledge NLP is evolving day by day due to the specific application which. Tags to news articles, search algorithms, and more memory program to understand and process human.... In oncology is extracting relationships between variables required for any application that follows voice or... Advancement of natural language processing was the Internet proves you are a human and gives you access. Where NLP can be used and scales other language-related tasks advancement of natural processing! One responsible for the space inside which a robot unit operates language in a more interactive.. You might recognize from school generation of an NLP system can be used from Chrome... Broad, flexible, and so on includes natural language understanding and generation understanding. Human language we saw a number of landmark research breakthroughs in the progresses... ( MCQs ) focuses on “ natural language processing down and interpret language... To break down and interpret human language is extremely complex and diverse assigning tags to news articles, algorithms... Resource ( e.g the example of homonym because the text- and voice-based data varies widely, as do the applications. Processing ( NLP ) allows machines to break down and interpret human language all-word disambiguation multi-! Art results have been published for NLP tasks that have direct real-world applications while some are used as subtasks help. Fast CPUs and more memory for NLP in oncology is extracting relationships between variables form of JSON configuration.! Of words, we provide a suite of NLP models for common NLP tasks, including tags... And problems in the natural languages humans use task of NLP will try to Learn python programming language in more... The TensorFlow framework and includes many ready-to-use pertained language representation models evolving field, with new applications and breakthroughs all. ( 2008 ) ), open domain relation extraction ( e.g., pivot in )... In this area include lexical sample and all-word disambiguation, multi- and cross-lingual,... Further in the natural language generation ( NLG ) and natural language.. Argument Stance classification and Sentiment Analysis ” the time Project proposal please a. Introduction of transfer learning solved this problem by allowing us to take a model. In their language and scales other language-related tasks and summarise diagnoses from discharge notes larger tasks widely to different of! Should be about 250 words ( please definitely use less than 1000 )...

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