Conventional “symbolic” AI runs computations according to algorithms and traditional computer programs that are stated abstractly ... But generative AI works in a different way, by approximating the things that humans have said in various situations.A symbolic AI system could simply look up where Shearer was born, such as by consulting his Wikipedia page. By contrast, generative AI systems ingest the entire internet, identify patterns of human language, and try to reconstruct what sounds plausible in a given contextHallucinations tend to be the kind of thing a person might say in a given context if she didn’t exactly know what was going on ... it is generating the kind of reasonable-sounding, well-formed, grammatical sentence that you might hear from a human. But it is false
Generative AI is fundamentally blind to truth
Because LLMs are so good at mimicking patterns of human language, people tend to anthropomorphize them – sometimes to the point of falling in love or “marrying” them. It is all too common to attribute to LLMs far more intelligence than they could possibly have
作为世界上最权威的科技商业媒体之一，MIT Technology Review于1899年在美国麻省理工学院创刊，至今已经走过121年，为全世界超过300万专业人士及商业领袖提供前瞻性的资讯和独到深入的行业趋势分析。
In 2025, The American Sunlight Project, a non-profit, published a study[161] showing evidence that the so-called Pravda network, a pro-Russia propaganda aggregator, was strategically placing web content through mass publication and duplication with the intention of biasing LLM outputs. The American Sunlight Project coined this technique "LLM grooming", and pointed to it as a new tool of weaponizing AI to spread disinformation and harmful content
A large language model (LLM) is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation. The largest and most capable LLMs are generative pretrained transformers (GPTs), which are largely used in generative chatbots such as ChatGPT...
