Lesson 1062 of 1570
Why GPT, Claude, and Gemini All 'Hallucinate' (and Always Will)
Models predict the next word that's most likely to fit — they don't 'know' anything. That's why they make stuff up.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The big idea
- 2hallucination
- 3next-token prediction
- 4ungrounded output
Concept cluster
Terms to connect while reading
Section 1
The big idea
When a model 'hallucinates' (makes up a fake fact, fake citation, fake API), it's not lying — it's doing exactly what it was trained to do: predict the next plausible word. Plausible-sounding wrong is a feature of the architecture, not a bug. No model — GPT, Claude, Gemini — will ever fully stop hallucinating. The cure is verification, not better models.
Some examples
- Claude invents a Python library called `easyparse` that doesn't exist — sounds plausible, isn't real.
- ChatGPT cites a paper 'Smith et al. 2019' that no human ever wrote.
- Gemini gives you a phone number that's almost the right format but wrong digits.
- Reasoning models hallucinate less but still do — there is no zero-hallucination model.
Try it!
Ask any model 'cite 5 papers about [your hobby].' Check whether the papers exist. Count the fakes.
Key terms in this lesson
End-of-lesson quiz
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