The foundational technology behind all modern AI assistants, chatbots, and coding tools.
Large Language Models (LLMs) are neural networks trained on vast corpora of text to predict and generate human language. The transformer architecture, introduced in the 2017 paper 'Attention Is All You Need', underpins every modern LLM from GPT to Claude to LLaMA. LLMs learn patterns, facts, reasoning chains, and writing styles from training data — enabling them to answer questions, write code, summarize documents, translate languages, and more. The field is advancing rapidly: model sizes grow from billions to trillions of parameters, context windows expand from 4K to 2M tokens, and capabilities stretch from text to image, audio, and video.
Internal benchmarks allegedly show GPT-5 achieving near-human performance on graduate-level STEM tasks, with a 92% pass rate on the GPQA Diamond benchmark — a 34-point jump over GPT-4o.
The open-source release includes three model sizes and a new mixture-of-experts architecture. Developers are already fine-tuning it for specialized use cases within hours of release.
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