AI/LLM topics — agents, prompts
NotebookLM is Google's source-first AI notebook. It only answers from the PDFs, Google Docs, web pages, YouTube videos, and audio files you upload — so hallucinations are far rarer than a generic chatbot. Where 04-gemin…
Google AI Studio (aistudio.google.com) is the in-browser home for the Gemini family. It started as a prompt playground, but since 2024 it has grown into a notebook + app builder + auto-deploy environment — squarely in t…
Gemini is the model series Google DeepMind released in late 2023. Multimodal input — handling images · audio · video · code alongside text — and the very long context that came in with 1.5 are the often-cited features.
An embedding is the result of mapping text (or images · code) to fixed-dimensional real-valued vectors. On top of the assumption that semantically close items sit close in the vector space, search · clustering · classif…
The trend of running large language models directly on personal computers has taken hold rapidly since 2023. Where there used to be only cloud APIs, the combination of quantization formats like GGUF, inference runtimes…
A prompt is closer to the design of an input interface itself than just a string sent to an LLM. Message structure · reasoning patterns · sampling parameters · security all entangle at once.
RAG (Retrieval-Augmented Generation) is an approach to supplement an LLM's limited training cutoff and memory limits with external knowledge. By separating retrieval and generation, you can handle new material without r…
The word "agent" is used in several senses, which is a confusing situation. Script automation is called an agent, and so is the shape of an LLM calling tools.
The LLM market shifts fast. Closed-API and open-weight, English-centric and multilingual, cloud and self-hosted, models specialized for Korean — all sit alongside each other.