How does OneAdvanced AI work?

In this article, we are going to explore some of the technology behind OneAdvanced AI.

Large Language Model

OneAdvanced AI makes use of a Large Language Model (LLM). This is a type of artificial intelligence (AI) that is trained on massive amounts of text data. This training allows it to generate human quality level text, translate languages, write different kinds of creative content and answer questions in an informative way.  

You can think of an LLM as being like a library, with an ability to quickly retrieve information from its vast knowledge base. An LLM can also be compared to a skilled writer, who can quickly generate text on a wide range of topics, from simple answers to complex essays.

Meta Llama

Llama is an LLM developed by Meta, designed to process and generate human-like language. It's a type of AI model that can understand and respond to natural language inputs. It's been trained on a massive dataset of text from various sources, including books, articles, and websites, which allows it to learn patterns and relationships in language.

One of the key features of Llama is its ability to generate human-like responses to a wide range of questions and prompts. It can answer questions, provide explanations, and even engage in conversation, all while trying to mimic the style and tone of a human.

However, it's worth noting that Llama is not a perfect model, and it can make mistakes or provide responses that are not entirely accurate. But it's still a powerful tool for generating human-like language, and it has many potential applications in areas like customer service, content generation, and more.

How does OneAdvanced AI work?

Let's break down how the AI works in a simple way. Let's think of the AI as a student learning to understand and write language.

How it Understands (Technical Overview)

1. You give it a question: Like asking "What is a cat?"
2. Breaking it down: The AI chops your question into small pieces, like individual words ("What", "is", "a", "cat"). These pieces are called "tokens."
3. Understanding the meaning: These tokens go through a special part of the AI (called the "encoder") that tries to understand the meaning of each word and how they relate to each other. It creates a kind of "meaning-picture" of your question.
4. Forming an answer: Another special part (called the "decoder") takes this "meaning-picture" and starts building an answer word by word.
5. Paying attention: When it's building the answer, the decoder has a way of looking back at your original question and focusing on the most important parts to make sure its answer makes sense. It's like a student highlighting key phrases in a question before answering.
6. Giving you the answer: Finally, the AI gives you its answer as a sequence of words, like "A cat is a small furry animal..."

How it Learns (Masked Language Modelling)

Imagine the AI learning like this:

1. Lots of reading material: It reads tonnes of text from books, websites, and articles.
2. Cutting out words: During its learning, it plays a game where some words in a sentence are hidden (masked).
3. Guessing the missing word: The AI tries to guess the missing word based on the other words in the sentence.
4. Checking its answers: It then checks if its guess was correct. If not, it adjusts its "understanding" of language.
5. Repeating over and over: It does this hiding and guessing game millions of times. This helps it learn how words connect, what makes sense in a sentence, and how to predict the next word.

In short, the AI learns by reading a lot and practicing filling in missing words. When you ask it something, it breaks down your question, understands the meaning, focuses on the important parts, and then builds its answer word by word based on everything it has learned.