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29 components of labs and 1 index are not listed: data a lab works on, held because its lab is; pages of links that point at teaching material without being any. Show them

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In the fast-evolving field of information retrieval (IR), the integration of generative AI technologies such as large language models (LLMs) is transforming how users search for and interact with information. Recognizing this paradigm shift at the intersection of IR and generati…

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The pervasive application of artificial intelligence and machine learning algorithms is transforming many industries and aspects of the human experience. One very important industry trend is the move to convert existing human dwellings to smart buildings, and to create new smart…

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The relentless pursuit of technological advancements has ushered in a new era where artificial intelligence (AI) is not only a powerful tool but also a critical economic driver. At the forefront of this transformation is Generative AI, which is catalyzing a paradigm shift across…

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In the ever-evolving landscape of Artificial Intelligence (AI), the synergy between generative AI and Software Engineering emerges as a transformative frontier. This whitepaper delves into the unexplored realm, elucidating how generative AI techniques can revolutionize software …

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This document contains the outcome of the first Human behaviour and machine intelligence (HUMAINT) workshop that took place 5-6 March 2018 in Barcelona, Spain. The workshop was organized in the context of a new research programme at the Centre for Advanced Studies, Joint Researc…

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The interdisciplinary research domain of Artificial Intelligence in Education (AIED) has a long history of developing Intelligent Tutoring Systems (ITSs) by integrating insights from technological advancements, educational theories, and cognitive psychology. The remarkable succe…

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Generative AI research has increasingly evaluated factuality, citation, coverage, and report structure. Yet passing such local checks does not by itself show that a humanistic interpretation has been established. This paper asks how an interpretation comes to be recognized withi…

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Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs). Although architects recognize t…

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The rapid development of generative artificial intelligence (AI) technologies raises concerns about the accountability of sociotechnical systems. Current generative AI systems rely on complex mechanisms that make it difficult for even experts to fully trace the reasons behind th…

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The integration of generative Artificial Intelligence (AI) chatbots in higher education institutions (HEIs) is reshaping the educational landscape, offering opportunities for enhanced student support, and administrative and research efficiency. This study explores the future imp…

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With the upcoming AI regulations (e.g., EU AI Act) and rapid advancements in generative AI, new challenges emerge in the area of Human-Centered Responsible Artificial Intelligence (HCR-AI). As AI becomes more ubiquitous, questions around decision-making authority, human oversigh…

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Sparked by innovations in generative artificial intelligence (AI), the field of protein design has undergone a paradigm shift with an explosion of new models for optimizing existing enzymes or creating them from scratch. After more than one decade of low success rates for comput…

arXiv HTML Narrative text
VerifAI: Verified Generative AI
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Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as inaccurate decision-making, the spread of false information, privacy violations, legal liabilities…

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Researchers are constantly leveraging new forms of data with the goal of understanding how people perceive the built environment and build the collective place identity of cities. Latest advancements in generative artificial intelligence (AI) models have enabled the production o…

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The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, fil…

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Intrusion Detection Systems (IDSs) are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Internet of Things (IoT), enterprise, and distributed network environments. However, developing reliable IDS models remains challenging …

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The tendency of generative artificial intelligence (AI) systems to "hallucinate" false information is well-known; AI-generated citations to non-existent sources have made their way into the reference lists of peer-reviewed publications. Here, I propose a solution to this problem…

GitHub Markdown microsoft/generative-ai-for-beginners
Local Setup 🖥️
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Inferred Use this guide if you prefer to run everything on your own laptop. You have two paths: (A) native Python + virtual-env or (B) VS Code Dev Container with Docker. Choose whichever feels easier—both lead to the same lessons.

GitHub Markdown Exercise microsoft/generative-ai-for-beginners
Choosing & Configuring an LLM Provider 🔑
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Inferred Assignments may also be setup to work against one or more Large Language Model (LLM) deployments through a supported service provider like OpenAI, Azure or Hugging Face. These provide a hosted endpoint (API) that we can access programmatically with the right credentials (API key…

GitHub Markdown Narrative text Objectives microsoft/generative-ai-for-beginners
Introduction to Generative AI and Large Language Models
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Inferred In this curriculum, we’ll explore how our startup leverages generative AI to unlock new scenarios in the education world and how we address the inevitable challenges associated with the social implications of its application and the technology limitations.

GitHub Notebook microsoft/generative-ai-for-beginners
Introduction to Prompt Engineering
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Inferred Prompt engineering is the process of designing and optimizing prompts for natural language processing tasks. It involves selecting the right prompts, tuning their parameters, and evaluating their performance. Prompt engineering is crucial for achieving high accuracy and efficien…