From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the
  Generative Artificial Intelligence (AI) Research Landscape
Timothy R. McIntosh Teo Susnjak Tong Liu Paul Watters Malka N. Halgamuge
This comprehensive survey explored the evolving landscape of generative
Artificial Intelligence (AI), with a specific focus on the transformative
impacts of Mixture of Experts (MoE), multimodal learning, and the speculated
advancements towards Artificial General Intelligence (AGI). It critically
examined the current state and future trajectory of generative Artificial
Intelligence (AI), exploring how innovations like Google's Gemini and the
anticipated OpenAI Q* project are reshaping research priorities and
applications across various domains, including an impact analysis on the
generative AI research taxonomy. It assessed the computational challenges,
scalability, and real-world implications of these technologies while
highlighting their potential in driving significant progress in fields like
healthcare, finance, and education. It also addressed the emerging academic
challenges posed by the proliferation of both AI-themed and AI-generated
preprints, examining their impact on the peer-review process and scholarly
communication. The study highlighted the importance of incorporating ethical
and human-centric methods in AI development, ensuring alignment with societal
norms and welfare, and outlined a strategy for future AI research that focuses
on a balanced and conscientious use of MoE, multimodality, and AGI in
generative AI.