The Quanta Podcast When ChatGPT Broke an Entire Field
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Jul 29, 2025 John Pavlus, a contributing writer for Quanta Magazine, dives into the transformative journey of natural language processing (NLP) since the arrival of large language models like ChatGPT. He shares insights from interviews with 19 NLP researchers, revealing their mixed emotions—some excitement and some concern—about the rapid changes in their field. The discussion touches on how traditional research methods are becoming obsolete, the ethical dilemmas posed by AI, and how advancements in NLP are driving new scientific discoveries.
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Transformers Revolutionized NLP
- The 2017 "Attention Is All You Need" paper introduced transformers, revolutionizing natural language processing.
- Transformers enabled large language models by using attention mechanisms to better relate input data parts.
Debate Over LLM Understanding
- The NLP field split philosophically over whether large language models truly understand language.
- Emily Bender believes these models simulate understanding without actual comprehension, sparking intense debate.
Philosophy Meets NLP Reality
- The intense debate around LLM comprehension touched philosophical and theoretical questions about machine understanding.
- NLP community confronted real-world implications of longstanding computational linguistics theories.