Timo Honkela: Introducing the book Encyclopedia of Artificial Intelligence (in Finnish)

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The book "Encyclopedia of Artificial Intelligence" (Tekoälyn ensyklopedia), edited by Eero Hyvönen, Ilkka Karanta and Markku Syrjänen (1993), was an important landmark in the Finnish AI research and development. Finland has been and remains an important country in this field. Many of the authors were already prominent figures at that time, especially Professor and later Academician Teuvo Kohonen. Since then many authors have become processors in different universities. One of the authors, Tuomas Sandholm received in 2003 the IJCAI Computers and Thought Award and serves as a professor at Carnegie Mellon University.

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Timo Honkela: Introducing the book Encyclopedia of Artificial Intelligence (in Finnish)

Professor Timo Honkela's Studia Generalia presentation for the Society of Futures Studies at Turku University, Finland, on Thursday 27th of October, 2016. The title of the talk is "Threats and opportunities related to artificial intelligence and machine learning". The topics include 1) an introduction to AI and ML, 2) information on why AI and ML are societally relevant just in this moment of history, 3) natural language processing based on ML, 4) presentation of meta-analysis in humanities (cf. Helsinki Studia Generalia presentation a week earlier), 5) AI and intuition, and 6) discussion on the positive and negative scenarios related to AI and ML.

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Abstract: Models of linguistic semantics can be viewed through representation and reasoning. This distinction concerns questions on how do we represent the world that we refer to by linguistic expressions and what kind of reasoning do we apply based on these representations. It has been commonplace to assume that each word or expression has one or a limited number of different, distinct senses. The classification task of disambiguation has been devised to find the right reference in each case. It is also possible to represent the world using a high-dimensional continuous space. In that case, we do not need to assume that the world is represented as a network of nodes and their connections. These mathematical representations go beyond the capacities provided by symbolic logic. The word embeddings has history that stems from vector space representations in information retrieval. When a framework of multidimensional continuous spaces is available, it is possible to study nuances of meaning that go beyond conducting disambiguation or choosing between alternatives within a logical framework. In the present work, it is postulated that semantic processes are essentially subjective and thus individual. When high-dimensional continuous spaces are used to represent meanings and defining contextual distributions, subjective aspects can be modelled. It is possible to measure subjectivity of meaning. This can be studied, for instance, in the framework of brain research (Saalasti et al. 2019) or motions tracking (Honkela & Förger 2013). The methodology or measuring subjective contextually grounded meaning has been been presented, for instance, in Raitio et al. 2014. Further methodological work and an empirical demonstration is presented in Sintonen et al. (2014). When it is possible to represent individually contextual meaning of expressions, it is consequently possible to analyse the differences of meaning between two individuals. A hypothesis is that suitable data for the purpose of meaning negotiation can be collected, computational algorithms devised and applied in real world contexts that helps in meaning negotiations. An alternative view is to aim at defining the meaning of words in a precise way and to teach all people to use these definition. In this present work, it is claimed that that objectivity can be reached only to a degree as it would require vast human cognitive and time resources and the mapping between words and the world is doomed to be partial. This concern has implications both in scientific and in real world communication and representation and has been applied in building the Peace Machine framework. Meaning negotiations as phenomena and as LT challenges Timo Honkela University of Helsinki with Iiro Jääskeläinen (Aalto University) on the Study of Individualized Meanings using Brain Research University of Helsinki, Topelia, F211 4th of April, 2019

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Slide 1: Title Slide Extrachromosomal Inheritance Slide 2: Introduction to Extrachromosomal Inheritance Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus. Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids. Slide 3: Mitochondrial Inheritance Mitochondria: Organelles responsible for energy production. Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria. Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring. Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy. Slide 4: Chloroplast Inheritance Chloroplasts: Organelles responsible for photosynthesis in plants. Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts. Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species. Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA. Slide 5: Plasmid Inheritance Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes. Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation. Significance: Important in biotechnology for gene cloning and genetic engineering. Slide 6: Mechanisms of Extrachromosomal Inheritance Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance. Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells. Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression. Slide 7: Examples of Extrachromosomal Inheritance Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells. Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration. Slide 8: Importance of Extrachromosomal Inheritance Evolution: Provides insight into the evolution of eukaryotic cells. Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases. Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification. Slide 9: Recent Research and Advances Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA. Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases. Slide 10: Conclusion Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology. Future Directions: Continued research and technological advancements hold promise for new treatments and applications. Slide 11: Questions and Discussion Invite Audience: Open the floor for any questions or further discussion on the topic.

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