ChatGPT Quiz: Test Your OpenAI IQ

Explore ChatGPT’s GPT models, OpenAI milestones, viral features, and AI breakthroughs in this challenging quiz for chatbot fans worldwide. Test your AI IQ

May 22, 2026 - 12:48
May 22, 2026 - 13:29
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1. Which company developed "ChatGPT"?

ChatGPT was built by a research lab founded in San Francisco in 2015. The organisation started as a non-profit but later shifted to a capped-profit model. It is backed by major technology investors and focuses on building AI that is both capable and safe for widespread public use.

OpenAI
Google DeepMind
Meta AI
Anthropic

2. What does "GPT" stand for in "ChatGPT"?

The name behind ChatGPT points to a specific type of neural network architecture that became popular in the late 2010s. This architecture changed how machines process and produce language, replacing older sequential models. The approach involves pre-training on large text datasets before being adapted for specific tasks.

Generalised Pre-trained Transformer
General Purpose Text
Generative Pre-trained Transformer
Global Processing Technology

3. In which year was "ChatGPT" publicly launched?

ChatGPT was made available to the public during a period of rapid growth in conversational AI tools. Its release sparked widespread debate about the future of writing, education, and work. Within days of going live, it became one of the fastest-growing consumer applications in internet history.

2020
2022
2023
2021

4. Which version of "GPT" powered "ChatGPT" at its initial public launch?

When ChatGPT first went live, it did not run on the most advanced model available at the time. The underlying version had already been used in various tools before ChatGPT launched. It was later upgraded, but the original version was what millions of early users experienced first.

GPT-4
GPT-3
GPT-2
GPT-3.5

5. What reinforcement learning technique was central to aligning ChatGPT's outputs with human preferences?

To make ChatGPT respond in ways people actually found helpful, its developers used a training method that incorporates direct input from human reviewers. Trainers ranked different responses, and those rankings shaped how the model learnt to behave. This process helped reduce unhelpful, harmful, or misleading replies over time.

Proximal Policy Optimisation
RLHF
Direct Preference Optimisation
Q-Learning

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ANAND SWAMI Anand Swami is a Senior Content Manager and quiz content writer with 7+ years of writing quizzes, blogs, and articles that have driven over 150 million organic visits. From General Knowledge, history, science, and technology to business, personality, lifestyle, and travel, he has covered it all and built genuine audience engagement along the way. Outside of work, Anand is a certified tabla player and a TKFI karate player, two disciplines that keep him sharp, focused, and creative.