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Dusseault & Lee: Other than Hawaii's, no education department has publicly focused on policies governing artificial intelligence in the classroom.
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In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine-tuned LLMs, called Llama 2-Chat, are optimized for dialogue use cases. Our models outperform open-source chat models on most benchmarks we tested, and based on our human evaluations for helpfulness and safety, may be a suitable substitute for closed-source models. We provide a detailed description of our...
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Low-powered mobile devices such as Raspberry Pis and tablets can be used as micro-servers to implement offline Learning Management Systems (LMS). Despite their potential, especially for low-income countries, such as Tanzania, no research is available detailing the affordances of these devices for supporting LMS features. This study investigated the suitability of various low-cost micro-servers for deploying LMSs. It compared the performance of the Raspberry Pi, Android tablet, and Chromebook...
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The repository aims to create an overview and comparison of software used for systematically screening large amounts of textual data using machine learning.
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Abstract Background Evidence synthesis organisations worldwide are trying to meet commissioners’ need for rapid responses to their evidence synthesis commissions. In this project we piloted an intensive process, working to complete an evidence synthesis within six-weeks, rather than the standard lead time of 4-6 months. There were three objectives: 1) To develop a plan for and conduct an evidence synthesis in six weeks or less (“intensive pilot”) 2) To register time used for the intensive...
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The infographic presents different options explored so far for possible modifications that could be implemented in classrooms in Tanzania. The interventions chosen will depend on the conditions of each classroom studied in the ‘Improving Learning Conditions through Classroom Experience’ programme.
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We show for the first time that large-scale generative pretrained transformer (GPT) family models can be pruned to at least 50% sparsity in one-shot, without any retraining, at minimal loss of accuracy. This is achieved via a new pruning method called SparseGPT, specifically designed to work efficiently and accurately on massive GPT-family models. We can execute SparseGPT on the largest available open-source models, OPT-175B and BLOOM-176B, in under 4.5 hours, and can reach 60% unstructured...
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GPT based autonomous agent that does online comprehensive research on any given topic
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An output of the Open Development & Education, https://opendeved.net/
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An output of the EdTech Hub, https://edtechhub.org
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An output of the Open Development & Education, https://opendeved.net/
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Identifying the frames of news is important to understand the articles' vision, intention, message to be conveyed, and which aspects of the news are emphasized. Framing is a widely studied concept in journalism, and has emerged as a new topic in computing, with the potential to automate processes and facilitate the work of journalism professionals. In this paper, we study this issue with articles related to the Covid-19 anti-vaccine movement. First, to understand the perspectives used to...
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The theoretical positioning of a review is of the utmost importance in terms of its contribution to knowledge. This paper clarifies the significance of this design principle for different types of review i.e. for describing, understanding, explaining or testing purposes. Furthermore, new tools now mean that it is both possible and relevant for bibliometrics novices to use bibliometrics to support literature reviews. Applying the BIBGT method and combining two bibliometric techniques –...
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