Understanding Large Language Models in AI

Modified on Sat, 16 Mar 2024 at 12:33 AM

Chatbots rely on something called a Large Language Model (LLM) to help them recognize and create language that sounds like it came from a person. Engineers train an LLM on huge amounts of text. This process allows it to recognize patterns and structures in language.

It all starts with collecting a massive amount of internet data from books, articles, websites, social media, and more. This data is then fed into a deep learning model that uses artificial neural networks. The model learns to recognize patterns and relationships between words, phrases, and sentences.

After this initial training, the model is fine-tuned. This fine-tuning uses smaller, specialized datasets. It optimizes the LLM for specific tasks like answering questions, writing text, or figuring out the mood of a piece of writing. The resulting LLM can then be used to power AI tools like ChatGPT, virtual assistants, or content creation tools.

When you ask a chatbot a question, it looks at all the times those words have been mentioned together on the internet. It uses that information to assemble an answer that sounds like it came from an expert. But the chatbot doesn't understand the concepts behind your words like a person does.

While LLMs have revolutionized the way AI handles language, they do have some limitations:

1. Bias and hallucinations: LLMs can pick up biases from the data they're trained on. They can also replicate incorrect information from the internet. In some cases, they fabricate things like events which never occurred. 

2. Lack of common sense: LLMs may struggle with tasks that require common sense or real-world knowledge.

3. Computational resources: Training and using large-scale LLMs requires a lot of computational power and energy. This can be expensive and challenging for the environment.

LLMs have become a cornerstone of modern AI systems. As they continue to improve, they'll likely play an even bigger role. But we must be aware of their limitations. Use them responsibly, and always double-check the information they provide.

For more information, check out this video:

Large Language Models (LLMs) AI Explained by Common Craft 

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