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Researchers, educators and companies are experimenting with ways to turn flawed but famous large language models into trustworthy, accurate ‘thought partners’ for learning.
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The Global Convening on Education Evidence Labs, hosted by Jacobs Foundation in partnership with the Foreign, Commonwealth, and Development Office (FCDO), alongside support from On Think Tanks (OTT), brought together stakeholders from Ministries of Education, EdLab implementing units, research institutions, multilateral agencies, and global funders. The event, held in mid-October 2023, aimed to address the […]
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Abstract Reviews have long been recognized as among the most important forms of scientific communication. The rapid growth of the primary literature has further increased the need for reviews to distill and interpret the literature. This review on Reviews and Reviewing: Approaches to Research Synthesis encompasses the evolution of the review literature, taxonomy of review literature, uses and users of reviews, the process of preparing reviews, assessment of review quality and...
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Many organisations struggle to keep pace with public health evidence due to the volume of published literature and length of time it takes to conduct literature reviews. New technologies that help automate parts of the evidence synthesis process can help conduct reviews more quickly and efficiently to better provide up-to-date evidence for public health decision making. To date, automated approaches have seldom been used in public health due to significant barriers to their adoption. In...
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web-based citation screening tool
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AI assistants are changing how we interact with technology, helping us with tasks like answering questions and creating content. Google and Bing have already added AI like Bard and Bing Chat to their platforms. However, there’s a new player in the market: Perplexity AI. In this post, we will look at Perplexity AI and its […]
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As the original AI qualitative data analysis software, NVivo has fine-tuned the autocoding feature that lets researchers conduct text data analysis with AI to detect and code themes and sentiments.
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Emerging tools bring forth fresh approaches to work, and the field of natural science is no different. In natural science, traditional manual, serial, and labour-intensive work is being augmented by automated, parallel, and iterative processes driven by artificial intelligence-based experimental automation and more. To add new capabilities in natural science, enabling the acceleration and enrichment of automation of the discovery process, we present DARWIN, a series of tailored LLMs for...
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Employees describe the psychological trauma of reading and viewing graphic content, low pay and abrupt dismissals
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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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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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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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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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Whilst the ability of generative AI to produce text in English has been widely covered, the implications of its ability to translate and act as a cultural broker into English have received less att…
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We recently published a novel categorization of studies related to virtual reality (VR) in your journal, European Heart Journal—Digital Health.1 Our categorization is based on the usage of VR devices, where type A studies refer to those in which healthcare providers use VR devices and type B studies refer to those in which patients use them. Using this simple definition, we clarified the study trends and characteristics of the two research directions. In this study, we used a classical...
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