Results 21 to 30 of about 4,316,857 (220)
Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts
International Conference on Human Factors in Computing Systems, 2023 Pre-trained large language models (“LLMs”) like GPT-3 can engage in fluent, multi-turn instruction-taking out-of-the-box, making them attractive materials for designing natural language interactions.
J.D. Zamfirescu-Pereira +3 more
semanticscholar +1 more source
Regulating ChatGPT and other Large Generative AI Models [PDF]
Conference on Fairness, Accountability and Transparency, 2023 Large generative AI models (LGAIMs), such as ChatGPT, GPT-4 or Stable Diffusion, are rapidly transforming the way we communicate, illustrate, and create.
P. Hacker, A. Engel, M. Mauer
semanticscholar +1 more source
Learning Health Systems, Volume 7, Issue 1, January 2023., 2023 Abstract Introduction Artificial‐intelligence (AI)‐based predictive analytics provide new opportunities to leverage rich sources of continuous data to improve patient care through early warning of the risk of clinical deterioration and improved situational awareness.Part of the success of predictive analytic implementation relies on integration of the ...
Jessica Keim‐Malpass +4 more
wiley +1 more source
Macedonian Veterinary Review, 2020 The present study aimed to evaluate whether the induction and the formation of an accessory corpus luteum (CL) after AI might increase the pregnancy per AI (P/AI) in heat stressed dairy cows.
Boris Stojanov +9 more
doaj +1 more source
Optimizations of Process Parameter for Erosion Wear Using Sustainable Machine Learning Approach [PDF]
E3S Web of Conferences, 2023 Aim of current study is to utilize different sustainable artificial intelligence (AI) tools to check the influence of test factors on erosion wear. Bottom ash is taken as erodent at different solid concentration while brass is considered as base material.
Kumar Kaushal +8 more
doaj +1 more source
Journal of Medical Imaging and Radiation Oncology, Volume 66, Issue 8, Page 1029-1034, December 2022., 2022 Abstract Introduction Incorporating artificial intelligence (AI) in diagnostic medical imaging reports has the potential to improve efficiency. Although perception of radiologists, radiographers, medical students and patients on AI use in image reporting has been explored, there is limited literature on non‐radiologist clinicians' opinion on this topic.
Sophie Soyeon Lim +7 more
wiley +1 more source
Art and the science of generative AI [PDF]
Science, 2023 Understanding shifts in creative work will help guide AI’s impact on the media ecosystem The capabilities of a new class of tools, colloquially known as generative artificial intelligence (AI), is a topic of much debate.
Ziv Epstein +13 more
semanticscholar +1 more source
Permeability and selectivity prediction of poly (4-methyl 1-pentane) membrane modified by nanoparticles in gas separation through artificial intelligent systems [PDF]
Polyolefins Journal, 2020 In this work, the effects of operative parameters on CH4, CO2, O2, and N2 membrane gas separation for poly (4-methyl-1-pentane) (PMP) membrane modified by adding nanoparticles of TiO2, ZnO, and Al2O3 are assessed and investigated.
Afshar Alihosseini +1 more
doaj +1 more source
Computational literature – creation under the auspices of AI and GPT models [PDF]
Dialogica: Revistă de Studii Culturale și Literatură, 2023 In this article is presented the impact of GPT natural language processing models and the evolution of AI on the computational literature. Analyzing the structuring and functioning of these neural networks based on observation, learning (pre-training ...
Rodica Gotca
doaj +1 more source
Education sciences, 2023 Over the last decade, technological advancements, especially artificial intelligence (AI), have significantly transformed educational practices. Recently, the development and adoption of Generative Pre-trained Transformers (GPT), particularly OpenAI’s ...
Simone Grassini
semanticscholar +1 more source