AI often sounds like a complex, almost sci-fi concept reserved for tech geniuses. But the truth is, AI is already part of our daily lives, whether we notice it or not. Like it or not, it’s something we all need to start exploring, regardless of our backgrounds.
I’ll be honest: I’ve found myself overwhelmed by the flood of AI jargon out there. Every day there’s a new name —ChatGPT o3, o4-mini, o4-high, Opus 4, Gemini 2.5— and it’s hard to keep track. Which one is newer? Which one is smarter? Meanwhile, bosses and companies are rushing to “install AI” as if it were just another app like Word or Excel.
But AI isn’t an app.
It’s more like a skill — or even a mindset.
Sure, you’ve probably heard a lot of ChatGPT at first. I did too. But what if I told you this is not the only one. Gemini, Claude, and other models are also out there, each with their own strengths, peculiarities, and even “personalities.” They all use something called LLMs (Large Language Models) to reason and generate answers, often working in two broad modes: reasoning and inference (I’ll break down these two concepts below).
In this article, I want to give you a beginner-friendly tour through this fascinating landscape — so you can understand not just what AI is, but also who’s building it, how these different models compare, and why it all matters.
Full article can be found here
Top comments (1)
The AI race is getting more interesting every quarter 🚀
ChatGPT continues to lead in usability + ecosystem.
Gemini pushes Google’s distribution advantage.
Claude stands out with alignment and long-context handling.
Copilot is quietly making Microsoft Office and GitHub smarter.
No single player “owns” AI yet — it feels more like parallel sprints where each model solves a different piece of the puzzle.
I’ve been collecting insights and experiments around these shifts at 👉 aiwebix.com