Original Paper: https://arxiv.org/abs/2206.07682

By: Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus

Abstract:

Scaling up language models has been shown to predictably improve performance and sample efficiency on a wide range of downstream tasks. This paper instead discusses an unpredictable phenomenon that we refer to as emergent abilities of large language models. We consider an ability to be emergent if it is not present in smaller models but is present in larger models. Thus, emergent abilities cannot be predicted simply by extrapolating the performance of smaller models. The existence of such emergence implies that additional scaling could further expand the range of capabilities of language models.

Summary Notes

Exploring the New Powers of Large Language Models

The field of artificial intelligence (AI) is advancing quickly, especially with the growth of language models.

These larger models are not just performing better across various tasks; they're also showing new abilities that we didn't see coming. For AI Engineers working in big companies, understanding these new powers is crucial.

What's New with Large Language Models (LLMs)?

Emergence is when a system does something unexpected that its parts can't do on their own. In LLMs, this means that when the models get bigger, they start to show new abilities.

Key New Abilities of LLMs

Two abilities, in particular, are changing the game for future tasks:

• Few-Shot Learning: LLMs can now learn and perform tasks with very few examples, much less than before.
• Better Understanding of Language: Larger models can understand language in a deeper, more nuanced way, allowing for more complex interactions.

These abilities indicate a significant leap in what models can do.

The Challenge and Opportunity of Unpredictability

The new abilities of LLMs are unpredictable, which can be both tricky and exciting. Traditional ways of measuring performance don't always help us understand these new powers, suggesting there's much more to discover.

Why and How New Abilities Emerge

The exact reasons why LLMs are showing new abilities are still being studied. However, it's thought that the sheer scale of these models allows them to understand language nuances in ways smaller models can't.

Looking Ahead

Research into these new abilities is vital. Future studies might focus on:

• How model size, design, and training data contribute to new abilities.
• Whether other AI and machine learning models show similar behaviors.

This research could lead to more predictable and controlled development of LLMs' new abilities.

Conclusion

The new abilities of Large Language Models are changing how we understand and use machine learning. This opens up exciting opportunities for innovation in AI but also presents challenges in leveraging these abilities for real-world applications.

For AI Engineers at big companies, this is a thrilling, complex area in advancing NLP technologies. We're just starting to uncover the potential of LLMs, pointing to a future filled with extraordinary possibilities in AI.