In these early days of artificial intelligence, you might find yourself staring at an answer, wondering: how on Earth did the model get to that? With Google’s newest experimental model, you can pull back the curtain on how AI thinks, as it’s designed to show you its thoughts.
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Toggle See an AI Model’s Reasoning With Gemini 2.0 Flash Thinking
Building on its speedy Gemini 2.0 Flash experimental model, Google has just dropped Gemini 2.0 Flash Thinking, a version that not only offers fast solutions to complex questions, but also presents its reasoning in getting to that solution. According to Google DeepMind’s Jeff Dean, the new experimental model was “trained to use thoughts to strengthen its reasoning.”
While Gemini 2.0 Flash Experimental is available directly on the standard Gemini desktop app, Gemini 2.0 Flash Thinking Experimental is only available on Google’s AI Studio. That being said, it’s easy (and free) to get started on this platform. At the time of writing, you can present the model with up to 1500 requests per day without paying a dime.
![Peer Inside the Mind of Google's AI With This New Experimental Gemini Model 1 A user asks a math question using Gemini 2.0 Flash Thinking](https://i0.wp.com/static1.makeuseofimages.com/wordpress/wp-content/uploads/2024/12/gemini-2-0-flash-thinking-example-question.png?resize=900%2C450&ssl=1)
You don’t need a subscription to Gemini Advanced to use either of these experimental models.
What’s the Use (Case)?
According to Google, this new experimental model is most useful when you need to understand the steps an AI model takes in getting to a response, such as when you have to “tackle difficult code and math problems.”
![Peer Inside the Mind of Google's AI With This New Experimental Gemini Model 2 Specs listed for Gemini 2.0 Flash Thinking Experimental, including its rate limits and latency](https://i0.wp.com/static1.makeuseofimages.com/wordpress/wp-content/uploads/2024/12/gemini-2-0-flash-thinking-specs.png?resize=900%2C450&ssl=1)
I can imagine how seeing the model’s thoughts could be helpful in double-checking its work. For instance, if you were unsure about a response, you can review the model’s step-by-step reasoning to either feel more confident about the resolution, or find the exact point where things went wrong.
Students could likely also benefit from this model. Say you have a fairly complicated physics problem. Instead of merely copying and pasting an AI-generated response, you could also review the steps involved in getting that result. That being said, there’s still no way to know for sure that the answer or the reasoning is accurate. That’s because these AI models are also still students, to some extent.
I don’t know about you, but these recent Google releases are starting to feel like 12 Days of Christmas: Gemini Edition. It feels like Google drops an experimental model or Gemini upgrade every day, and I have to wonder if OpenAI’s ChatGPT Search coming from Google’s job has anything to do with it. In any case, it’s a good sign for progress, as every AI update leads to stronger models.