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When ChatGPT Flipped the Script on Language Research
- The transformer model introduced in 2017 initially seemed like a clever hack to many researchers in the language domain.
- The arrival of Google's BERT model in 2018, built on transformers, revolutionized language tasks and sparked a surge of interest in 'BERTology.'
- The launch of OpenAI's GPT-3 in 2020, significantly larger than its predecessor, amazed researchers with its capabilities and scale.
- The field of NLP started dividing between those emphasizing scaling models and others raising concerns about ethics and neglected languages.
- The introduction of ChatGPT in 2022 had a seismic impact, erasing entire research areas and leading to shifts in focus for many researchers.
- Some researchers felt disillusioned by the corporate atmosphere surrounding GPT-3 and the benchmark-driven culture.
- The evolving landscape of NLP prompted varied reactions, with some embracing the advancements while others emphasized the limitations of large language models.
- By 2024, NLP was undergoing a period of consolidation and adaptation, with researchers grappling with the implications of money and corporate involvement.
- The emergence of LLMs led to a flood of attention and scrutiny, propelling researchers like Ellie Pavlick into the limelight.
- The future of NLP remains uncertain, with debates on whether the field is experiencing a paradigm shift or simply an evolution of existing ideas.
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