So, AI is everywhere — your feed, your fridge, and maybe even your future job. But what do all these “AI bros” keep talking about? What’s a model? Is LLM a vibe? And does GPT mean “Get Pizza Tonight”? Let’s decode the top 10 AI terms that everyone’s hyping about — but in a way that doesn’t fry your brain.
What Gen-Z Thinks: “Oh that’s like Jarvis or Siri, right?” What It Actually Means: AI is a computer doing “thinking-ish” things humans do — like learning, solving problems, or recommending your next playlist. 💡 Real-life Vibe: Netflix telling you exactly what you’re in the mood for at 2 AM = AI being your digital bestie.
Not Just Buzzwords: ML is how AI actually learns. You give it data → it finds patterns → it predicts stuff. Analogy: ML is like that one kid who doesn’t study from the book but aces the test just by seeing past papers. Over and over. And better each time. 🔥 IRL Use: Spotify figuring out you’re sad before you do.
Sounds scary but it’s 🔥: This is like ML with 10 cups of coffee. It uses “neural networks” to mimic how your brain works. 🧠 Imagine this: A deep learning model watches 10,000 hours of TikTok and then creates one that could go viral — and yes, maybe even steal your followers. Used in: Self-driving cars, voice assistants, facial recognition.
It’s giving brain vibes. A neural network is a computer system kinda shaped like your brain (nodes + connections). It processes info like a human — but faster, colder, and without needing coffee. Simple version: • Input: A photo of a dog • Hidden layers: “Hmm… ears? tail? nose?” • Output: “This is definitely a Shiba Inu.”
What even is this: It’s how AI understands what humans say (and type) — including slang, typos, and Gen-Z lingo. 💬 Think of it like: Siri or ChatGPT replying when you type: “bruh, what’s the weather in Delhi but like for real?” 🧃 Bonus: AI now even understands sarcasm (yikes).
AKA the engine behind ChatGPT. LLMs are trained on massive amounts of text — like everything from Wikipedia to your old blog posts. They don’t “know” things, but they’re really good at predicting what should come next. 👀 Why It’s Cool: You say: “Write a roast for my boss but make it sound poetic.” LLM: “Oh thou who CCs in vain…”
AKA the engine behind ChatGPT. LLMs are trained on massive amounts of text — like everything from Wikipedia to your old blog posts. They don’t “know” things, but they’re really good at predicting what should come next. 👀 Why It’s Cool: You say: “Write a roast for my boss but make it sound poetic.” LLM: “Oh thou who CCs in vain…”
Where AI gets its knowledge from. Imagine if you learned life only through memes. You’d think dogs rule the world and Mondays suck. That’s kind of how training data works. If the data’s biased or broken, the AI will be too. ⚠️ Moral of the story: Garbage in = garbage out. Even for robots.
Oof. This one’s important. AI can pick up stereotypes from its training data. If you only train a model on photos of male doctors and female nurses, guess what it assumes? 🙄 📢 Why It Matters: Bias in AI affects hiring, policing, healthcare — real lives. So yeah, we need ethical AI. Not just efficient AI.
THE buzzword of 2023–2025. This is the cool kind of AI that creates stuff — like images, videos, poems, songs, even code. You’ve seen it in DALL·E, Midjourney, and of course, ChatGPT. 🧙♂️ It’s Like This: You say: “Show me Pikachu as a Bollywood villain.” And boom — AI gives you art that slaps harder than Arijit Singh’s high notes.
💬 TL;DR (Too Long; Didn’t Read) AI is no longer just a tech thing. It’s a life thing. Term What It Does