Summary of Engineering a Large Language Model From Scratch, by Abiodun Finbarrs Oketunji
Engineering A Large Language Model From Scratch
by Abiodun Finbarrs Oketunji
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Computers and Society (cs.CY); Machine Learning (cs.LG); Software Engineering (cs.SE)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a novel Transformer-based neural network called Atinuke, designed to optimize performance across various natural language processing (NLP) tasks. By integrating sequential processing layers with attention mechanisms, Atinuke can emulate human-like language understanding and generation capabilities. The architecture’s unique configuration allows for feature extraction and complex mapping learning. As a modular, extensible system that integrates seamlessly with existing machine learning pipelines, Atinuke achieves state-of-the-art results on NLP tasks while remaining interpretable and robust. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Atinuke is a new kind of computer program that can understand and create human language really well. It’s like a super smart AI that can learn from us and make sense of words, sentences, and even pictures! The program uses special math tricks to figure out what’s important in what we’re saying or writing. This helps it become really good at understanding language, just like humans do. |
Keywords
* Artificial intelligence * Attention * Feature extraction * Language understanding * Machine learning * Natural language processing * Neural network * Nlp * Transformer
