A new measure of firm-level AI investments is proposed, using a unique combination of worker resume and job postings datasets, which reveals a stark increase in AI investments across sectors.
It is found that frontier model performance on GDPval is improving roughly linearly over time, and that the current best frontier models are approaching industry experts in deliverable quality.
USAID funding has significantly contributed to the reduction in adult and child mortality across low-income and middle-income countries over the past two decades and, unless the abrupt funding cuts announced and implemented in the first half of 2025 are reversed, a staggering number of avoidable deaths could occur by 2030.
It is found that few studies actually use AI to address normative or transformative dimensions of sustainability science, limiting the potential of relevant AI applications.
This study systematically reviews Model-Agnostic Explainable AI techniques, which can be applied across different types of ML models in finance, to evaluate their effectiveness, scalability, and practical applicability, and identifies key challenges.
This study applies advanced machine learning techniques such as deep learning, regression models, and ensemble learning to improve forecasting accuracy aimed at achieving efficient resource allocation and investigates fault prediction in New Energy Vehicles and its implications for grid stability and energy demand management.
The economic burden of cardiovascular risk factors and overt cardiovascular disease in the United States is projected to increase substantially in the coming decades and development and deployment of cost-effective programs and policies to promote cardiovascular health are urgently needed to rein in costs and to equitably enhance population health.
This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem, and investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations.
It is found that Q-learning can learn collusive equilibria only on timescales irrelevant to the firm’s objective, and criteria for practically relevant, explicitly and tacitly colluding pricing algorithms that would constitute a threat to competition are given.
The mean cost of developing a new drug from 2000 to 2018 was $172.7 million but increased to $515.8 million when cost of failures was included and to $879.3 million when both drug development failure and capital costs were included.
This study estimates the annual cost of PRRSV-related productivity losses using US data from 2016 to 2020 and highlights the continuous and growing burden of PRRSV on US swine production.
The study underscores the need for targeted investments, faculty training, policy development, and regional collaboration to accelerate AI adoption and maximize its benefits across MENA higher education institutions.
A health-augmented macroeconomic model is used to calculate the macroeconomic burden of ADODs for 152 countries or territories, accounting for the effect on labour supply of reduced working hours of informal caregivers, and the effect on labour supply of ADODs-related mortality and morbidity.
It is shown that a rising Bitcoin price is followed by entry of new users, in particular among more risk-seeking segments of the population, and that when prices rise larger holders sell, likely making a return at retail users’ expense.
This paper illustrates how AI could augment existing SDM tools and provides empirical evidence that current large language models can generate and evaluate strategies at a level comparable to entrepreneurs and investors, and proposes a framework connecting AI use in SDM to firm outcomes.
This work synthesizes China’s current policies toward promoting healthy longevity in the general population, focusing on social health insurance, long-term care insurance, community and home-based care and palliative care, as well as gerontological research, public health prevention, nutritional and medical interventions, while identifying strengths and gaps.
The distribution of healthcare utilization in Indonesia is largely equitable as predisposing factors and health need were found to greatly influence the utilization of different types of health services, however, enabling factors were also found to be associated with inequity in utilization of hospital services.
It is demonstrated that AI is not merely an abstract idea but an actual technology stack encompassing infrastructure, models, applications, and an ecosystem of applications and companies relying on this stack encompassing infrastructure, models, applications, and an ecosystem of applications and companies relying on this stack.
Estimating the impact of US funding cuts on deaths and other outcomes for four health areas that have been a focus of a substantial amount of US foreign assistance suggests sharp increases in avoidable mortality for the poorest countries could lead to sharp increases in avoidable mortality for the poorest countries.
The modelling suggested that termination of USAID funding might lead to 1·4 million (95% uncertainty interval 1·1-1·7) excess tuberculosis episodes and 537 700 (451 900-662 300) excess deaths by 2035, compared to the scenario of termination of USAID funding.
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