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There exists a growing discourse around the domination of Big Tech on thelandscape of artificial intelligence (AI) research, yet our comprehension ofthis phenomenon remains cursory. This paper aims to broaden and deepen ourunderstanding of Big Tech's reach and power within AI research. It highlightsthe dominance not merely in terms of sheer publication volume but rather in thepropagation of new ideas or \textit{memes}. Current studies often oversimplifythe concept of influence to the share of affiliations in academic papers,typically sourced from limited databases such as arXiv or specific academicconferences.  The main goal of this paper is to unravel the specific nuances of suchinfluence, determining which AI ideas are predominantly driven by Big Techentities. By employing network and memetic analysis on AI-oriented paperabstracts and their citation network, we are able to grasp a deeper insightinto this phenomenon. By utilizing two databases: OpenAlex and S2ORC, we areable to perform such analysis on a much bigger scale than previous attempts.  Our findings suggest, that while Big Tech-affiliated papers aredisproportionately more cited in some areas, the most cited papers are thoseaffiliated with both Big Tech and Academia. Focusing on the most contagiousmemes, their attribution to specific affiliation groups (Big Tech, Academia,mixed affiliation) seems to be equally distributed between those three groups.This suggests that the notion of Big Tech domination over AI research isoversimplified in the discourse.  Ultimately, this more nuanced understanding of Big Tech's and Academia'sinfluence could inform a more symbiotic alliance between these stakeholderswhich would better serve the dual goals of societal welfare and the scientificintegrity of AI research.

Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation