The post reframes token-based models such as LLMs not as “understanders” of meaning but as statistical simulators that predict the next token from learned patterns. This lens demystifies capabilities, clarifies limits, and points to practical, high-impact uses when paired with grounding, evaluation, and human oversight.
The post reframes token-based models such as LLMs not as “understanders” of meaning but as statistical simulators that predict the next token from learned patterns. This lens demystifies capabilities, clarifies limits, and points to practical, high-impact uses when paired with grounding, evaluation, and human oversight.