LLMs are large language models which are kind of deep learning models where it predicts single token or sequence of token that are relatable to each other. A token can be a word, a subword or a character.
These are built on a type of neural network architecture called transformers. Currently, ChatGPT, Gemini, Perplexity etc. all are based on it. These transformers are very large in size because of parameters billions in size. It uses encoders and decoders. Transformers use self-attention techniques where self is for input sequence and self-attention weighs the relation between tokens in the input sequence.
Training and Fine-tuning are other factors that contribute to better working of LLMs. NLPs (Natural Language Processing) are also important for the LLMs.
Issues with LLMs
LLMs have issue of hallucinating, biases and using a lot of computational and energy resources. AI companies are massively using these which are creating shortage for common people.
Popular LLMs
GPT-5, GPT-4o, Deepseek -v3.2, Gemini 3.0, Claude Opus 4.5 and many more. These are also coming up with Agentic AI.
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