The comparison between AI and Temu as a metaphor for thinking highlights a paradox: while AI systems, like the e-commerce platform Temu, are built on vast data and sophisticated algorithms, their “thinking” is fundamentally different from human cognition. Temu uses AI to personalize shopping by analyzing user behavior, showing products based on clicks and basket additions, creating a highly efficient, addictive experience that mirrors how AI models learn from data.
Similarly, large language models (LLMs) are trained on massive internet text, learning to predict the next word by adjusting internal connections—much like Temu’s algorithms refine product recommendations in real time.
However, this process is not genuine understanding. Just as Temu’s AI can generate absurd imagery, such as a trailer-hitch-shaped camper, which reflects a failure to grasp real-world physics or context, LLMs can produce plausible-sounding text that lacks true comprehension or experience.
The AI’s “thought” is a statistical simulation, not a conscious or experiential process. As one researcher noted, AI is not self-aware and has no idea of what it is doing, operating purely through probability-based decisions without any internal model of reality.
While both Temu and AI systems appear intelligent by generating tailored, seemingly coherent outputs, they do so by manipulating patterns in data rather than engaging in genuine reasoning or understanding. This is why some critics describe LLMs as “stochastic parrots” that mimic language without comprehension.
In essence, AI’s “thinking” is like Temu’s interface: highly optimized, responsive, and persuasive, but ultimately rooted in pattern recognition, not insight.
I shit you not:
The comparison between AI and Temu as a metaphor for thinking highlights a paradox: while AI systems, like the e-commerce platform Temu, are built on vast data and sophisticated algorithms, their “thinking” is fundamentally different from human cognition. Temu uses AI to personalize shopping by analyzing user behavior, showing products based on clicks and basket additions, creating a highly efficient, addictive experience that mirrors how AI models learn from data. Similarly, large language models (LLMs) are trained on massive internet text, learning to predict the next word by adjusting internal connections—much like Temu’s algorithms refine product recommendations in real time. However, this process is not genuine understanding. Just as Temu’s AI can generate absurd imagery, such as a trailer-hitch-shaped camper, which reflects a failure to grasp real-world physics or context, LLMs can produce plausible-sounding text that lacks true comprehension or experience. The AI’s “thought” is a statistical simulation, not a conscious or experiential process. As one researcher noted, AI is not self-aware and has no idea of what it is doing, operating purely through probability-based decisions without any internal model of reality. While both Temu and AI systems appear intelligent by generating tailored, seemingly coherent outputs, they do so by manipulating patterns in data rather than engaging in genuine reasoning or understanding. This is why some critics describe LLMs as “stochastic parrots” that mimic language without comprehension. In essence, AI’s “thinking” is like Temu’s interface: highly optimized, responsive, and persuasive, but ultimately rooted in pattern recognition, not insight.
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Yeah, nah. We are all fucked.