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      Unveiling the evolution of generative AI (GAI): a comprehensive and investigative analysis toward LLM models (2021–2024) and beyond

      Journal of Electrical Systems and Information Technology
      Springer Science and Business Media LLC

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          Abstract

          This comprehensive exploration of recent breakthroughs in artificial intelligence (AI) traversed the realms of language models, computer vision, and generative models, unraveling the intricacies of cutting-edge technologies such as GPT-3.5, GPT-4, Pix2Seq, and multimodal models in terms of generative AI. In this multifaceted journey, the focus extended beyond technological prowess to ethical considerations, emphasizing responsible AI practices guided by Google's AI Principles. The nuanced discussions encapsulated the transformative impact of AI on user experiences across various Google products and toolsets, paving the way for a future where natural language interaction, creative content generation, and multimodal understanding redefine human–computer interactions. The research investigation showcased not only the advancements themselves but also the critical lens through which these innovations are approached, underscoring the importance of ethical and responsible AI in shaping the technological landscape.

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          Most cited references22

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          Art and the science of generative AI

          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. One prominent application thus far is the production of high-quality artistic media for visual arts, concept art, music, and literature, as well as video and animation. For example, diffusion models can synthesize high-quality images ( 1 ), and large language models (LLMs) can produce sensible-sounding and impressive prose and verse in a wide range of contexts ( 2 ). The generative capabilities of these tools are likely to fundamentally alter the creative processes by which creators formulate ideas and put them into production. As creativity is reimagined, so too may be many sectors of society. Understanding the impact of generative AI—and making policy decisions around it—requires new interdisciplinary scientific inquiry into culture, economics, law, algorithms, and the interaction of technology and creativity.
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            Healthcare predictive analytics using machine learning and deep learning techniques: a survey

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              ‘ChatGPT et al.’: The ethics of using (generative) artificial intelligence in research and science

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Journal of Electrical Systems and Information Technology
                Journal of Electrical Systems and Inf Technol
                Springer Science and Business Media LLC
                2314-7172
                December 2024
                June 12 2024
                : 11
                : 1
                Article
                10.1186/s43067-024-00145-1
                bb908b7c-bdba-416f-a101-0f8bc7f1b53b
                © 2024

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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