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By putting in place climate change adaptation measures, NATO has an opportunity to both strengthen operational resilience and adapt to the impacts of climate change.
This paper catalogues current efforts to address climate change within multilateral economic and financial institutions and related organizations. It also proposes a minimum set of policy measures that need to be prioritized by such institutions to support climate change mitigation and adaptation. The proposals include expanding public climate finance via multilateral development banks, doing more to mobilize private investment, mainstreaming climate considerations across institutional operations, making climate disclosures mandatory, and addressing sovereign debt distress to unlock private climate finance.
We investigate the potential implications of large language models (LLMs), such as Generative Pretrained Transformers (GPTs), on the U.S. labor market, focusing on the increased capabilities arising from LLM-powered software compared to LLMs on their own. Using a new rubric, we assess occupations based on their alignment with LLM capabilities, integrating both human expertise and GPT-4 classifications. Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted. We do not make predictions about the development or adoption timeline of such LLMs. The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software. Significantly, these impacts are not restricted to industries with higher recent productivity growth. Our analysis suggests that, with access to an LLM, about 15%
Pet cats kill songbirds by the million, as well as rodents and other wildlife. But how much of a threat do they really pose, and should they be kept indoors? Expert opinion is divided
