GoKawiilAI is moving at a breakneck pace, and frankly, it's hard to keep up. Sure, it's cool to have a chatbot that acts like it has a Ph.D. in everything, but the reality is a lot messier. You can't turn around without running into ChatGPT, Gemini or Meta AI. We're drowning in a sea of AI slop, fretting about data centers and watching job markets shift in real time.
If it all feels like too much, that could be because the vocabulary of artificial intelligence is evolving as fast as the code and the dizzying array of products. And if you want to do more than just stare at a blinking cursor, you've got to speak the language. You can't exactly navigate a 2026 job interview (or even a casual happy hour) if you're stumped by LLM, hallucination or claw.
We're past the "gee-whiz" phase of AI and into the era where it's basically the new plumbing of the internet. If you're tired of just nodding along when the talk gets techie, it's time for a crash course. We've rounded up the essential terms you actually need to know so you can stop guessing and start sounding like you know exactly where the future is headed.
This glossary is regularly updated.
agent, agentic: AI that executes a task, often autonomously, is an agent, while agentic is the umbrella term for that software category. An AI agent may engage disparate systems to perform that work -- for instance, reading your grocery list in a notes app and then placing an order, and paying for it, using other apps.
AI ethics: Principles aimed at preventing AI from harming humans, achieved through means like determining how AI systems should collect data or deal with bias.
AI psychosis: A phenomenon in which individuals become overly fixated, enamored or self-aggrandized by AI chatbots, leading to delusions of grandeur, deep emotional connections and a break from reality. It is not a clinical diagnosis.
AI safety: An interdisciplinary field that's concerned with the long-term impacts of AI and how it could progress suddenly to a super intelligence that could be hostile to humans.
algorithm: A series of instructions that allow a computer program to analyze data in a particular way, such as recognizing patterns, and then in turn accomplish a task such as sorting results or making recommendations.
alignment: Tweaking an AI to better produce the desired outcome. This can refer to anything from moderating content to maintaining positive interactions with humans.
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