已发表文本的社会演化与通过大语言模型实现的人工智能涌现，以及毒性与偏见问题
Social Evolution of Published Text and The Emergence of Artificial Intelligence Through Large Language Models and The Problem of Toxicity and Bias
AI总结：
该研究从历史社会视角客观梳理大语言模型驱动的AI涌现进展，指出其存在的毒性、幻觉等问题，并提出AI与人类智能均为规模带来的涌现现象的观点。
摘要：
我们对人工智能与深度学习领域的快速发展给出了宏观概览，正是这些发展推动了人工智能在大语言模型（Large Language Models, LLM）中的突破性涌现。本研究的目的是将所有这些发展置于务实、更广阔的历史社会视角下，既不夸大其词，也不抱有曾在20世纪70年代至90年代引发“人工智能寒冬”的悲观态度。同时，我们也指出了当前存在的毒性、偏见、记忆问题、谄媚性、逻辑不一致性、幻觉等问题，仅作为对过度乐观者的警示。我们在此指出，正如人工智能的这种涌现似乎发生在神经连接或权重数量达到某个阈值的节点上，已有研究也观察到，人类大脑尤其是大脑皮层并没有什么特殊或非同寻常之处，它不过是灵长类大脑的放大版本，甚至人类智能看起来也像是一种由规模带来的涌现现象。
英文摘要：
We provide a birds eye view of the rapid developments in AI and Deep Learning that has led to the path-breaking emergence of AI in Large Language Models. The aim of this study is to place all these developments in a pragmatic broader historical social perspective without any exaggerations while at the same time without any pessimism that created the AI winter in the 1970s to 1990s. We also at the same time point out toxicity, bias, memorization, sycophancy, logical inconsistencies, hallucinations that exist just as a warning to the overly optimistic. We note here that just as this emergence of AI seems to occur at a threshold point in the number of neural connections or weights, it has also been observed that human brain and especially the cortex region is nothing special or extraordinary but simply a case of scaled-up version of the primate brain and that even the human intelligence seems like an emergent phenomena of scale.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
