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Abstract While global warming has generally increased the occurrence of extreme precipitation, the physical mechanisms by which climate change alters regional and local precipitation extremes remain uncertain, with debate about the role of changes in the atmospheric circulation. We use a convolutional neural network (CNN) to analyze large‐scale circulation patterns associated with U.S. Midwest extreme precipitation. The CNN correctly identifies 91% of observed precipitation...
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Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify the residential status of urban buildings in low and middle income countries. A recently developed ensemble machine learning building classification model is applied for the first time to the Democratic Republic of the Congo, and to Nigeria. The...
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Pretrained general-purpose language models can achieve state-of-the-art accuracies in various natural language processing domains by adapting to downstream tasks via zero-shot, few-shot and fine-tuning techniques. Because of their success, the size of these models has increased rapidly, requiring high-performance hardware, software, and algorithmic techniques to enable training such large models. As the result of a joint effort between Microsoft and NVIDIA, we present details on the training...
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Abstract Although Climate Change is a global phenomenon, the impact in Africa is anticipated to be greater than in many other parts of the world. This expectation is supported by many factors, including the relatively low shock tolerance of many African countries and the relatively high percentage of African workers engaged in the agricultural sector. High-income countries are increasingly turning their focus to climate change adaptation, and Artificial Intelligence (AI) is a...
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Greetings, if our institution opts for the Tier 3 plan for the ChatGPT API, allowing students to utilize our API, and the usage either surpasses or falls below the predefined limits of Tier 3, how does it influence the monthly pricing? To clarify, if usage exceeds the Tier 3 limits, will our monthly payment remain fixed at $1000, or will the pricing be adapted according to our actual usage? You can refer to the link provided for details on the tier plans: https://platform.openai.com/docs/guides/...
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Advances in virtual reality (VR) technology afford creation of immersive virtual learning environments that simulate real-life learning contexts with increasing fidelity. When supported by sufficiently advanced artificial intelligence (AI)-based tutoring software, such environments may facilitate asynchronous, embodied learning approaches for learning hard, procedural skills in industrial settings – addressing timeliness, accuracy, and scalability issues common in the industry.
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We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. We find that current large language models are significantly undertrained, a consequence of the recent focus on scaling language models whilst keeping the amount of training data constant. By training over 400 language models ranging from 70 million to over 16 billion parameters on 5 to 500 billion tokens, we find that for compute-optimal training, the model size...
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The scholarly information-seeking process for behavioral research consists of three phases: searching, accessing, and processing of past research. Existing IT artifacts, such as Google Scholar, have in part addressed the searching and accessing phases, but fall short of facilitating the processing phase, creating a knowledge inaccessibility problem. We propose a behavioral ontology learning from text (BOLT) design framework that presents concrete prescriptions for developing systems capable...
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The extensive and frequently severe impact of AI systems on society cannot be fully addressed by the human rights legal framework. Many issues involve community choices or individual autonomy requiring a contextual analysis focused on societal and ethical values. The social and ethical consequences of AI represent a complementary dimension, alongside that of human rights, that must be properly investigated in AI assessment, to capture the holistic dimension of the relationship between humans...
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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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