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n which case academic recognition may, or may not be, a significant motive. Intellectual conflict is a subclass of cultural conflict,[1] a conflict that tends to grow over time due to different cultural values and beliefs. Conflict in a group often follows a specific course. Routine group interaction is first disrupted by an initial conflict within the group, often caused by internal differences of opinion, disagreements between its members, or scarcity of resources available to the group. At this point, the group is no longer united, and may split into coalitions. This period of conflict escalation in some cases gives way to a conflict resolution stage, after which the group can eventually return to routine group interaction or split. Definitions M. Afzalur, a professor at Western Kentucky University,[2] notes there is no single universally accepted definition of conflict.[3] He notes that one issue of contention is whether the conflict is a situation or a type of behaviour.[4] Citing a review of definitions of organizational conflicts in 1990 by Robert A. Baron,[5] Afzalur notes that all definitions of conflict include known opposing interests and the process of trying to stop the opposing view or views. Building on that, the proposed definition of conflict by Afzalur is "an interactive process manifested in incompatibility, disagreement or dissonance within or between social entities." Afzalur also notes that a conflict may be limited to one individual, who is conflicted within himself (the intrapersonal conflict). Afzalur lists some manifestations of conflict behavior, starting with disagreement followed by verbal abuse and interference.[2] Another definition of conflict is proposed by Michael Nicholson, professor of Internal Relation at the University of Sussex,[6] who defines it as an activity which takes place when conscious beings (individuals or groups) wish to carry out mutually inconsistent acts concerning their wants, needs or obligations.[7] Conflict is an escalation of a disagreement, which is its common prerequisite, and is characterized by the existence of conflict behavior, in which the beings are actively trying to damage one another.[7] A key player in inter-group relations and conflict is the collective sentiment a person's own group (in-group) feels toward another group (out-group). These inter-group emotions are usually negative, and range in intensity from feelings of discomfort when interacting with a member of a certain other group to full on hatred for another group and its members. For example, in Fischer's organizational research at the University of Oxford, inter-group conflict was so 'heated' that it became mutually destructive and intractable, resulting in organizational collapse.[8][9] Out-group-directed emotions can be expressed both verbally and non-verbally, and according to the stereotype content model, are dictated by two dimensions: the perceived warmth (friendliness) and competence of the other group

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Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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