Natural Language Processing
Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial-intelligence concerned with the interactions between computers and human language.
Key Developments & Models
- GPT-3: Represents a significant leap in model scale, demonstrating emergent-abilities not present in smaller predecessors like gpt-2.
- Focuses on unprecedented scaling laws and their impact on language model capabilities.
- Detailed analysis available in GPT-3: Unprecedented Scaling and Emergent Language Model Capabilities.
- Discussed in the context of model size and performance by Computerphile in their video analysis GPT-3: Unprecedented Scaling and Emergent Language Model Capabilities(https://www.youtube.com/watch?v=_8yVOC4ciXc).
Core Concepts
- Transformer Architecture: The underlying neural network architecture powering modern LLMs.
- Large Language Models (LLMs): Models trained on vast datasets to predict the next token in a sequence.
- Zero-shot/Few-shot Learning: Capabilities enabled by scaling, allowing models to perform tasks without explicit fine-tuning.
References
- Computerphile. “GPT3: An Even Bigger Language Model.” GPT-3: Unprecedented Scaling and Emergent Language Model Capabilities(https://www.youtube.com/watch?v=_8yVOC4ciXc).