A tutorial on building a transformer-based language model in R from scratch, covering tokenization, self-attention, and text generation.
Explains AI transformers, tokens, and embeddings using a simple LEGO analogy to demystify how language models process and understand text.
An AI-generated, alliterative rewrite of Genesis 1 where every word starts with the letter 'A', created using GPT-4.
A technical guide to coding the self-attention mechanism from scratch, as used in transformers and large language models.
A curated reading list of key academic papers for understanding the development and architecture of large language models and transformers.
An analysis of GPT-3's capabilities, potential for misuse in generating fake news and spam, and its exclusive licensing by Microsoft.
A tutorial on text data classification using the BBC news dataset and PHP-ML for machine learning, covering data loading and preprocessing.
Explains the word2vec algorithm and the famous 'king - man + woman = queen' analogy using vector arithmetic and word co-occurrences.
