You might have heard terms like Artificial Intelligence (AI) and Machine Learning (ML). The newest stars in their world are Large Language Models, or LLMs. What are these LLMs? How are they going to influence our digital lives? Let's understand them simply.

What are Large Language Models (LLM)?

Large Language Models are a type of Artificial Intelligence program capable of understanding language, responding, and creating new content, much like humans. They are called "large" because they are trained on data containing billions of words and sentences. Just like a child learns a language, these models learn the relationships between words, grammatical rules, and contexts from this vast amount of data.

Their main capabilities include:

●   Answering questions.

●     Writing poems, articles, and stories.

●     Translating from one language to another.

●     Engaging in conversations (chatbots).

●     Preparing summaries.

●    Providing coding instructions.

Why are LLMs so Important?

The advent of LLMs is bringing revolutionary changes to many areas of technology. They help us find information, communicate, and perform creative tasks. LLMs can have a significant impact in all fields, including education, research, business, and entertainment. It's noteworthy that their potential in regional languages like Malayalam is also increasing.

Large Language Models (LLM): A Simple Introduction and Key Comparisons

Different Types of LLMs and Their Differences Numerous organizations and researchers have developed LLMs. Let's get acquainted with some of the important ones:

GPT (Generative Pre-trained Transformer) Series - OpenAI:

OpenAI's GPT models are among the most famous LLMs. ChatGPT is an example of this.

• Key Feature: The ability to provide highly human-like responses and prepare various types of written content.
• Difference: Gains more power and efficiency through continuous new versions (e.g., GPT-3, GPT-4, GPT-4o). These are usually commercially available models.

Gemini - Google:

Gemini is Google's latest and most powerful LLM.

• Key Feature: Multimodal capabilities to understand and respond not just to text, but also to images, audio, and video.
• Difference: It has the capability to work in conjunction with various Google services like Search. It is capable of performing more complex tasks.

Llama Series - Meta:

This LLM was developed by Meta, the parent company of Facebook.

• Key Feature: It is an open-source model. This means researchers and developers can use it for free and make modifications.
• Difference: Being open-source, it has significant community support. It helps in building powerful AI applications at a relatively lower cost.

Claude - Anthropic:

Claude is a model developed by Anthropic, an AI safety research company.

• Key Feature: Special attention to avoiding harmful or misleading responses, and a more ethical approach.
• Difference: It is trained using the "Constitutional AI" concept to reduce harmful outputs. It prioritizes safe AI usage.

Mistral/Mixtral - Mistral AI:

These are models developed by the France-based company Mistral AI.

Key Feature: Efficient and fast open-source models. Uses innovative technologies like "Mixture of Experts" (MoE).

• Difference: Capable of delivering excellent performance with less computing power, they are creating significant waves in the open-source field.
• Besides these, many other LLMs like Cohere, AI21 Labs Jurassic, Yi, and Qwen (Alibaba) are available today. Efforts are also underway for Malayalam language-focused models like "MalayaLLM."

Key Differences Between LLMs at a Glance:

1. Training Data: The amount and diversity of data used to train each model will vary. This influences their capabilities and responses.
2. Model Size (Parameters): The number of parameters in a model is a factor that influences its performance. More parameters usually help in better performance but require more computing power.
3. Open Source vs. Proprietary: Some models like Llama and Mistral are open-source. This allows anyone to use and modify them. GPT, Gemini, and Claude are proprietary models, and their full control rests with the companies that developed them.
4. Specialized Abilities: Some models may excel in specific areas. For instance, some might be excellent at coding, while others focus on creative writing. Models like Gemini stand out for their multimodal capabilities.
5. Access and Cost: Some models may need to be used via an API by paying a fee, some might be available for free in a limited capacity, and open-source models can be installed and used on one's own servers.

Summary Table

LLM	Developed by	Key Feature	Availability	Notable Use
GPT Series	OpenAI	Excellent general capabilities, human-like responses	Proprietary (via API, ChatGPT has a free tier)	ChatGPT, various AI applications
Gemini	Google	Multimodal capabilities (text, image, audio)	Proprietary (in Google products, via API)	Google AI services, complex tasks
Llama Series Meta	Open-source, great performance, large community support	Open-source, great performance, large community support	Open-source	Research, custom AI applications
Claude	Anthropic	AI safety, reduction of harmful content	Proprietary (via API)	Safe conversational AI, data analysis
Mistral/Mixtral	Mistral AI	Efficient open-source models, MoE architecture	Open-source	Efficient AI applications, research

Large Language Models have ushered in a new era of technology. Although they are still in the early stages of development, it is expected that they will bring significant changes to all areas of our lives in the future. Continuing efforts to enhance their capabilities in regional languages like Malayalam will help bring the benefits of this technology to more people. Try to learn more about this amazing world!