Model Basics · 1:15
Chat Model vs Reasoning Model
Compare fast, predictive chat models with slower reasoning models that think through problems.
- A chat model responds quickly like an enthusiastic intern, taking input and returning output.
- A reasoning model behaves like a senior colleague that plans how to solve a problem.
- Reasoning models use a chain of thought to figure out problems independently.
| Aspect | Chat Model | Reasoning Model |
|---|---|---|
| Analogy | Enthusiastic intern | Senior colleague |
| Response | Very quick input and output | Takes longer while thinking |
| Process | Predicts likely output | Plans and works through a chain of thought |
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What analogy does Lisa use for a chat model?
An enthusiastic intern.
What analogy does Lisa use for a reasoning model?
A senior colleague.
00:00 If you're working or playing with AI, you might have come across this concept of a reasoning or a research model. What we're going to talk about here is the idea of what we've been working with so far as a chat model. There are some other words used for this. It's called an LLM, GPT model. I'm sticking with chat model here because I think it's the clearest thing in explaining this. So if you are using AI, generative AI, as
00:23 we've noted up until now, it tends to kind of like take your input and then very quickly come back with the output as if it's a enthusiastic intern is kind of the analogy we've always used for that. Hence the little keen puppy here. A reasoning model is more like a senior colleague. It's more like somebody who's very experienced in an area rather than just sort of taking the input and going,
00:48 "Yep, here's what I know. Here's what I think. Bang. Back to you. The reasoning model is a senior colleague who's able to go, hm, how will I go about solving that problem? It's taking that input. It's figuring out. It's going through a chain of thought. How will I solve that problem once I find things? What else does that mean? And actually kind of independently doing that research for
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