首页|Findings from University of Antioquia Yields New Data on Artificial Intelligence (Embodied Human Language Models Vs. Large Language Models, or Why Artificial In telligence Cannot Explain the Modal be Able To)
Findings from University of Antioquia Yields New Data on Artificial Intelligence (Embodied Human Language Models Vs. Large Language Models, or Why Artificial In telligence Cannot Explain the Modal be Able To)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Artificial In telligence have been published. According to news reporting originating from Med ellin, Colombia, by NewsRx editors, the research stated, "This paper explores th e challenges posed by the rapid advancement of artificial intelligence specifica lly Large Language Models (LLMs). I show that traditional linguistic theories an d corpus studies are being outpaced by LLMs' computational sophistication and lo w perplexity levels." Our news editors obtained a quote from the research from the University of Antio quia, "In order to address these challenges, I suggest a focus on language as a cognitive tool shaped by embodiedenvironmental imperatives in the context of Ag entive Cognitive Construction Grammar. To that end, I introduce an Embodied Huma n Language Model (EHLM), inspired by Active Inference research, as a promising a lternative that integrates sensory input, embodied representations, and adaptive strategies for contextualized analysis and conceptual utility maximization. By incorporating Active Inference, which sees perception as inferring the world's s tate from sensory data, the findings reveal that the characterization of the Eng lish modal be able to, as a triadic construction encoding biological intelligent agency, introduces a more plausible theoretical basis for the positing of lingu istic constructions." According to the news editors, the research concluded: "This emphasizes the cruc ial role of embodied human language models in the comprehension of how humans co nstruct preferred futures through language."
MedellinColombiaSouth AmericaArtif icial IntelligenceEmerging TechnologiesMachine LearningUniversity of Antio quia
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