Learn About Natural Language Processing

Understand how machines process and generate human language — from tokenization and word embeddings to transformers, GPT, and the technology behind modern chatbots.

Google's Word2Vec algorithm, published in 2013 by Tomas Mikolov and colleagues, was a watershed moment for NLP, demonstrating that words could be represented as dense vectors in a mathematical space where semantic relationships emerged naturally — the famous example being that "king" minus "man" plus "woman" approximately equals "queen." BERT (Bidirectional Encoder Representations from Transformers), released by Google in October 2018, revolutionized NLP by pre-training on massive text corpora and then fine-tuning for specific tasks, achieving state-of-the-art results on 11 different benchmarks simultaneously and becoming the backbone of Google Search's understanding of queries. The GPT series pushed the boundaries further with GPT-4 demonstrating near-human performance on professional exams, while the underlying tokenization methods — byte-pair encoding, WordPiece, and SentencePiece — remain critical engineering decisions that determine how models break text into processable units and directly impact multilingual performance.

Superlore makes learning about Natural Language Processing effortless with AI-generated audio lessons. Listen during your commute, workout, or downtime — and absorb complex ideas at your own pace. Every lesson includes citations so you can dive deeper into the sources.