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README.md

@@ -1,2 +1,62 @@
-# atlas
-👁‍🗨Hallucination detector for Large Language Models.
+# ATLAS 🌍
+
+Final year project by [Jesse Amarquaye](mailto:jesseamarquayelegendary@gmail.com "Send email") and Greatman Akomea,
+computer engineering students from [Ghana Communication Technology University](https://www.gctu.edu.gh "GCTU").
+
+## Table Of Contents
+
+- [Introduction](#introduction)
+  - [Why work on hallucination in LLMs?](#why-work-on-hallucination-in-llms)
+  - [Why Atlas?](#why-atlas)
+  - [Aims or Objectives](#aims-or-objectives)
+- [Methodology](#methodology)
+
+## Introduction
+
+Atlas is a hallucination detector for Large Language Models.
+Its main focus is on **generative text** as that is the most widely used medium for interacting with LLMs.
+
+### Why work on hallucination in LLMs?
+
+Large language models (LLMs) are revolutionizing human-computer interaction, generating increasingly _fluent_ and
+_human-like text_.
+However, a significant challenge in LLMs is their tendency to produce **hallucinations**, or factually incorrect,
+nonsensical, or misleading content.
+As humans become increasingly reliant on LLMs for information and decision-making, ensuring their reliability and
+accuracy is crucial.
+This project aims to address this challenge by developing a software for **detecting** and **mitigating**
+hallucinations in LLMs so users can rely on LLM outputs with greater confidence, leading to wider adoption and
+societal benefits and also reduces the risk of misinformation to promote responsible use of LLMs.
+
+### Why Atlas?
+
+The story of Atlas in Greek mythology is closely tied to his role in supporting the heavens. According to one myth,
+during the _Titanomachy; the war between the Titans and the Olympian gods_, Atlas sided with the Titans. After their
+defeat, Zeus condemned Atlas to bear the weight of the heavens on his shoulders for eternity.
+
+The name **Atlas** symbolizes the software's commitment to bearing the responsibility of overseeing the cognitive
+aspects of language models, maintaining their stability, and preventing them from collapsing into inaccuracies or
+hallucinations. The association with Atlas also conveys _strength_, _resilience_, and _reliability_, suggesting a
+software that can handle the weight of complex language processing tasks with steadfastness and precision.
+
+### Aims or Objectives
+
+- [x] Explore techniques for mitigating hallucinations in LLMs.
+- [ ] Develop a software for automatic detection of hallucinations in LLMs.
+- [ ] Evaluate the effectiveness of the developed tool in different LLMs.
+
+## Methodology
+
+Our approach will be the design and implementation of a software to detect or flag and mitigate
+hallucinations in LLMs.
+The ultimate objective is the creation of a browser extension to actively scan the output from LLMs and
+compare them with results from trusted sources on the web and inform the user of any occurrence of hallucinations.
+An additional feature (probably in the future) will be to find the sources of the response the LLM generated.
+
+<details>
+
+<summary> View Flow Diagram </summary>
+
+![Flow diagram](docs/img/flow.svg)
+
+</details>