AI basics: What it is and how it works
Curated by the Inblix editorial team
Artificial intelligence is a broad category of software that can recognize patterns, learn from data, and produce outputs — think map apps rerouting around traffic or chatbots answering questions. Within AI, models are trained systems that specialize in tasks like speech, vision, or language. The most popular right now are large language models (LLMs), like the ones behind ChatGPT. They don’t truly “know” things; they predict the next likely word based on context, powered by massive text datasets. Training happens in two stages: pre-training, where the model learns general skills like summarizing from huge amounts of text (like a new employee reading all the manuals), and post-training, where it’s coached to follow instructions better and avoid harmful outputs — this is where safety checks are built in. LLMs are made available through products like ChatGPT or APIs for developers. Why it matters: Understanding the difference between AI as a category and the specific models within it helps you pick the right tool without getting lost in hype.
💡 Key Takeaways
- AI is a broad category of software that includes specialized models for tasks like language, vision, and forecasting.
- Large language models learn patterns from massive text datasets but don't have real understanding — they predict likely responses based on context.
- Training has two phases: pre-training builds broad skills, and post-training refines instruction-following and adds safety guardrails.
Keep reading: See related articles below for more coverage on this topic.
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