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Travaux d'Humanisme et Renaissance. In the narratives in vernacular prose printed in the Renaissance, form created meaning: the printing choices established links between texts, the narrative paragraph took the place of linguistic unity, and division into chapters conditioned reading practices. Write your review. Les Angoisses douloureuses et le cercle de Janot A.

Les acteurs de la publication des Angoisses douloureuses : Janot et ses collaborateurs B. Lieu de naissance des Angoisses douloureuses : le milieu des imprimeurs-libraires du Palais C. Titres de chapitres, manchettes et manicules B. Titres de chapitres et titres de parties IV.

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Combinaison des initiales et effets de sens II. Longueur des paragraphes et production du sens B. Redistribution des masses textuelles B. Subdivision interne des paragraphes D. Edition First Edition. Volume Collection Travaux d'Humanisme et Renaissance. A signifier may be a sound, a black mark on white paper, a trace or a gesture.

The relationship between the signifier and the signified is conventional and depends on which symbolic system the symbol belongs to in this case, the English language. We use different signifiers to indicate the same signified in different languages. Furthermore, the concepts symbolized by languages depend on the environment and culture of their speakers. However, it is in the context of a speech act that the interlocutor understands the referent of the word: is it a syntactic tree, a palm tree, a Christmas tree…? A language is a general symbolic system that allows humans to think reflexively, ask questions, tell stories, dialogue and engage in complex social interactions.

Each one of us is biologically equipped to speak and recognize languages. Our linguistic ability is natural, genetic, universal and embedded in our brain. By contrast, any language like English, French, etc. Languages mix and change according to the transformations of demographic, technological, economic, social and political contexts. Our natural linguistic abilities multiply our cognitive faculties.

They empower us with reflexive thinking, making it easy for us to learn and remember, to plan in the long-term and to coordinate large-scale endeavors. Language is also the basis for knowledge transmission between generations. Koko the famous gorilla will never ask you for an appointment for the first Tuesday of next month, nor will it communicate to you where its grandfather was born.

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In animal cognition, the categories that organize perception and action are enacted by neural networks. In human cognition, these categories may become explicit once symbolized and move to the forefront of our awareness. Ideas become objects of reflection. With human language comes arithmetic, art, religion, politics, economy, and technology. Compared to other social animal species, human collective intelligence is most powerful and creative when it is supported and augmented by its linguistic abilities. Therefore, when working in artificial intelligence or cognitive computing, it would be paramount to understand and model the functioning of neurons and neurotransmitters common to all animals, as well as the structure and organization of language, unique to our species.

I will now describe briefly how we shape meaning through language. Firstly, we will review what the grammatical units are words, sentences, etc. Secondly, we will explore the semantic networks between these units, and thirdly, what are the pragmatic interactions between language and extralinguistic realities. A natural language is made of recursively nested units: a phoneme which is an elementary sound, a word , a chain of phonemes, a syntagm, a chain of words and a text, a chain of syntagms.

A language has a finite dictionary of words and syntactic rules for the construction of texts. With its dictionary and set of syntactic rules, a language offers its users the possibility to generate — and understand — an infinity of texts. They can only pronounce one sound at a time. So languages have to obey the constraint of sequentiality. A speech is a chain of phonemes with an acoustic punctuation reflecting its grammatical organization. Phonemes are meaningless sounds without signification 1 and generally divided into consonants and vowels.

Despite the great diversity of sounds used to pronounce human languages, the number of conventional sounds in a language is limited: the order of magnitude is between thirty and one hundred. The first symbolic grammatical unit is the word, a signifier with a signified. By word, I mean an atomic unit of meaning. Languages contain nouns depicting structures or entities, and verbs describing actions, events, and processes. Depending on the language, there are other types of words like adjectives, adverbs , prepositions or sense units that orient grammatical functions, such as gender, number, grammatical person, tense and cases.

It depends. The largest English dictionary counts , words, Latin has 50, words, Chinese 30, characters and biblical Hebrew amounts to 6, words. The French classical author Jean Racine was able to evoke the whole range of human passions and emotions by using only 3, words in 13 plays. Most linguists think that whatever the language is, an educated, refined speaker masters about 10, words in his or her lifetime.

Note that a word alone cannot be true or false. Its signifier points to its signified an abstract category and not to a state of things. It is only when a sentence is spoken in a context describing a reality — a sentence with a referent — that it can be true or false.

A syntagm a topic, sentence, and super-sentence is a sequence of words organized by grammatical relationships. When we utter a syntagm, we leave behind the abstract dictionary of a language to enter the concrete world of speech acts in contexts. We can distinguish three sub-levels of complexity in a syntagm: the topic , the sentence , and the super-sentence. Firstly, a topic is a super-word that designates a subject, a matter, an object or a process that cannot be described by just a single word, i.

By relating several topics together a sentence brings to mind an event, an action or a fact, i. Finally, a super-sentence evokes a network of relations between facts or events, like in a theory or a narrative. The relationships between sentences can be temporal after , spatial behind , causal because , logical therefore or underline contrasts but, despite… , and so on.

The highest grammatical unit is a text : a punctuated sequence of syntagms. The signification of a text comes from the application of grammatical rules by combining its signifieds. The text also has a referent inferred from its temporal, spatial and social context. When we hear a speech, we are actually transforming a chain of sounds into a semantic network , and from this network, we infer a new mental model of a situation.

Conversely, we are able to transform a mental model into the corresponding semantic network and then from this network, back into a sequence of phonemes. Semantics is the back and forth translation between chains of phonemes and semantic networks. Semantic networks themselves are multi-layered and can be broken down into three levels: paradigmatic, syntagmatic and textual.

Figure: Hierarchy of grammatical units and semantic relations. In linguistics, a paradigm is a set of semantic relations between words of the same language. They may be etymological, taxonomical relations, oppositions or differences. Languages may comprise paradigms to indicate verb tenses past, present, future or mode active, passive. The notion of paradigm also indicates a set of words which cover a particular functional or thematic area. For instance, most languages include paradigms for economic actions buy, sell, lend, repay… , or colors red, blue, yellow….

A speaker may transform a sentence by replacing one word from a paradigm by another from the same paradigm and get a sentence that still makes sense. Two words from the same paradigm may be opposites if you are buying, you are not selling but still related buying and selling can be interchangeable. The English dictionary describes a horse as a particular case of animal. In general, the conceptual relationships between words from a dictionary may be qualified as paradigmatic.

By contrast, syntagmatic relations describe the grammatical connections between words in the same sentence. Since those words are inversed in the syntagmatic structure, the sentences have distinct meanings. At the text level, which includes several syntagms, we find semantic relations like anaphoras and isotopies.

When reading a pronoun it, he , we resolve the anaphora when we know which noun — mentioned in a previous or following sentence — it is referring to. On the other hand , isotopies are recurrences of themes that weave the unity of a text: the identity of heroes characters , genres love stories or historical novels , settings, etc.

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The notion of isotopy also encompasses repetitions that help the listener understand a text. Pragmatics weave the triadic relation between signs symbols, speeches or texts , beings interpreters, people or interlocutors and things referents, objects, reality, extra-textual context. On the pragmatic level of communication, speeches point to — and act upon — a social context.

A speech act functions as a move in a game played by its speaker. So, distinct from semantic meaning, that we have analyzed in a previous section, pragmatic meaning would address questions like: what kind of act an advice, a promise, a blame, a condemnation, etc. Is a speech spoken in a play on a stage or in a real tribunal? The pragmatic meaning of a speech also relates to the actual effects of its utterance, effects that are not always known at the moment of the enunciation.

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Have you kept your word? The sense of a speech can only be understood after its utterance and future events can always modify it. A speech act is highly dependent on cultural conventions, on the identity of speakers and attendees, time and place, etc. But I have to be someone relevant or important like the president of that assembly to do so.

In other cases, if an utterance does something instead of describing a state of things, it has a pragmatic force instead of a truth value. Now, we are going to examine the ambiguities that may arise during the reading or listening of a text in a natural language. How do we go from to the sound of a chain of phonemes to the understanding of a text?

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From a sequence of sounds, we build a multi-layered paradigmatic, syntagmatic and textual semantic network. To what paradigm does it belong? Which one of its meanings should I consider? Finally, we comprehend the text by recognizing the anaphoras and isotopies that connect its sentences. Our understanding of a text is based on this three-layered network of sense units. Furthermore , ambiguities or uncertainties of meaning in languages can happen on all three levels and can multiply their effects.

Moreover, who has the telescope?

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Mary or the woman? On a higher level of complexity, textual relations can be even more ambiguous than paradigmatic and syntagmatic ones because rules for anaphoras and isotopies are loosely defined. But some pragmatic aspects of a text may remain unknown. Understanding a text implies building and comparing complex and dynamic mental models of text and context. On the other hand, natural language processing a sub-discipline of artificial intelligence compensates for the irregularity of natural languages by using a lot of statistical calculations and deep learning algorithms that have been trained on huge corpora.

Depending on its training set, an algorithm can interpret a text by choosing the most probable semantic network amongst those compatible within a chain of phonemes. Imperatively, the results have to be validated and improved by human reviewers. That meeting was of great interest to me: I learned a lot about the current state of cloud computing and artificial intelligence. Contrary to other big tech companies, IBM already existed when I was born in The company was in the business of computing even before the transistors.

IBM adapted itself to electronics and dominated the industry in the era of big central mainframes. It survived the PC revolution when Microsoft and Apple were kings. They navigated the turbulent waters of the social Web despite the might of Google, Facebook, and Amazon. IBM is today one of the biggest players in the market for cloud computing, artificial intelligence and business consulting.

In the seventies, when I was a young philosopher and new technology enthusiast, IBM was the epitome of the grey suit, blue tie, black attache-case corporate America.

Instead of proprietary technology, IBM promotes open-source software. Innovation is mainly about entrepreneurship: self-confidence, audacity, tenacity, resilience and market orientation. As for the disruption, it is inevitable, not only because of the speed of digital transformation but also because of the cultural shifts and the sheer succession of generations.

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So their argument is fairly simple: instead of being disrupted, be the disruptor! The overall atmosphere of the Forum was positive and inspirational and it was a pleasure to participate. In addition, a lot of stands, product demonstrations and informative mini-talks on various subjects enabled the attendees to learn about current issues like e-health and hospital applications, robotics, data management, social marketing, blockchain and so on.

Their conversation about innovation in Canada today was both instructive and entertaining. From my point of view as a philosopher specialized in computing, Bryson Koehler CTO for IBM cloud and Watson made a wonderful presentation, imbued with simplicity and clarity, yet full of interesting content. These algorithms are now taught in universities and implemented in open source programs.

So what makes the difference in IA today is not the technique but the quality and quantity of the datasets in use to train the algorithms. Since every big player has access to the public data on the web and to the syndicated data on markets, news, finance, etc. So what is the competitive advantage of IBM?

Bryson Koehler sees it in the trust that the company inspires to its clients, and their willingness to confide their data to its cloud. Everything boils down to confidence. At lunchtime, with a dozen of other influencers, I had a conversation with researchers at Watson. Their idea is that the value is not created by replicating the human mind in a computer but in amplifying human cognition in real-world situations. It does not want to replace people with machines but help its clients to make better decisions in the workplace.

There is a growing flow of data from which we can learn about ourselves and the world. Therefore we have no other choice than to automate the process of selecting the relevant information, synthesize its content and predict, as much as possible, our environment. In this process of cognitive augmentation, nothing is perfect or definitive: people make errors, machines too, and there is always room for improvement of our models. Machines are just here to help.

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Pierre Levy's Blog. Categories English , Semantic Sphere. Tags communication , IEML , internet , linguistics , semantics. Est-ce que les machines peuvent devenir autonomes? Tags artificial intelligence , semantics. Categories French. Tags chatbot , digital transformation. Categories English , IBM. Language and Signification: How does Meaning Work?