LLM Optimisation
Deterministic vs Probabilistic Search: Google vs ChatGPT
Search is shifting from rule based to probabilistic. Google still retrieves; ChatGPT predicts. For brands, visibility now depends on influencing how AI thinks, not just how it searches.
10 October 2025
8 min read
Search used to be simple.
You typed something in, and the engine gave you a ranked list of results. Same input, same output.
That was a deterministic system: logical, rule based, and predictable.
But AI has changed the physics of discovery.
ChatGPT, Claude, Gemini and others don’t “retrieve and rank.” They predict and generate.
That shift makes the new world of AI search fundamentally probabilistic.
1. Google: Deterministic Core, Probabilistic Surface
Under the hood, Google Search is still rooted in determinism.
The indexing and retrieval layer is rule based, so identical queries on the same index snapshot return identical results.
But the moment you move into ranking, things start to bend.
Machine learning models weigh hundreds of relevance signals such as click through probability, satisfaction likelihood, freshness, and authority. These weights shift dynamically.
Personalisation adds another layer of probability, influenced by your location, device, and history.
Then, with AI Overviews and the Search Generative Experience, Google adds a generative surface: a layer that samples text probabilistically, just like ChatGPT.
So while it starts deterministic, it ends probabilistic.
Google predicts what to show.
2. ChatGPT: Purely Probabilistic by Design
ChatGPT doesn’t look up answers, it predicts them.
Every word is a probability decision, selected from a distribution of possible tokens based on everything written before it.
That means the same question can produce slightly different answers every time.
You can turn the temperature down to make it more consistent, but it never becomes fully deterministic.
ChatGPT isn’t ranking the web; it’s modelling language, producing what’s most likely to be said next.
ChatGPT predicts what to say.
3. Why This Matters for Brands
In deterministic search, optimisation meant working to a fixed logic: keywords, structure, backlinks, schema.
You played to the rules of the algorithm.
In probabilistic search, there are no fixed rules.
You’re not optimising for an index; you’re shaping the probability of inclusion.
That means designing language, data, and structure so that your brand is more likely to be referenced, quoted, or surfaced in generated answers.
This is semantic optimisation, not keyword optimisation. It’s about probability of mention rather than position.
The Takeaway
Google is deterministic at its core and probabilistic at its edges.
ChatGPT is probabilistic all the way down.
For brands, the future of visibility isn’t about ranking against fixed logic. It’s about influencing probabilistic systems that generate the language of discovery itself.
Owning your AI shelf space means understanding not just how search works, but how it thinks.
You typed something in, and the engine gave you a ranked list of results. Same input, same output.
That was a deterministic system: logical, rule based, and predictable.
But AI has changed the physics of discovery.
ChatGPT, Claude, Gemini and others don’t “retrieve and rank.” They predict and generate.
That shift makes the new world of AI search fundamentally probabilistic.
1. Google: Deterministic Core, Probabilistic Surface
Under the hood, Google Search is still rooted in determinism.
The indexing and retrieval layer is rule based, so identical queries on the same index snapshot return identical results.
But the moment you move into ranking, things start to bend.
Machine learning models weigh hundreds of relevance signals such as click through probability, satisfaction likelihood, freshness, and authority. These weights shift dynamically.
Personalisation adds another layer of probability, influenced by your location, device, and history.
Then, with AI Overviews and the Search Generative Experience, Google adds a generative surface: a layer that samples text probabilistically, just like ChatGPT.
So while it starts deterministic, it ends probabilistic.
Google predicts what to show.
2. ChatGPT: Purely Probabilistic by Design
ChatGPT doesn’t look up answers, it predicts them.
Every word is a probability decision, selected from a distribution of possible tokens based on everything written before it.
That means the same question can produce slightly different answers every time.
You can turn the temperature down to make it more consistent, but it never becomes fully deterministic.
ChatGPT isn’t ranking the web; it’s modelling language, producing what’s most likely to be said next.
ChatGPT predicts what to say.
3. Why This Matters for Brands
In deterministic search, optimisation meant working to a fixed logic: keywords, structure, backlinks, schema.
You played to the rules of the algorithm.
In probabilistic search, there are no fixed rules.
You’re not optimising for an index; you’re shaping the probability of inclusion.
That means designing language, data, and structure so that your brand is more likely to be referenced, quoted, or surfaced in generated answers.
This is semantic optimisation, not keyword optimisation. It’s about probability of mention rather than position.
The Takeaway
Google is deterministic at its core and probabilistic at its edges.
ChatGPT is probabilistic all the way down.
For brands, the future of visibility isn’t about ranking against fixed logic. It’s about influencing probabilistic systems that generate the language of discovery itself.
Owning your AI shelf space means understanding not just how search works, but how it thinks.