What you need to know
- Google’s Gemini 2.0 Flash Thinking lets you see how it tackles tough problems, giving you a peek into its thought process.
- Unlike OpenAI’s o1 model, which keeps things hidden, Gemini spells out its reasoning, making it easier to follow and avoid AI mistakes.
- This approach helps Gemini 2.0 Flash Thinking handle tougher challenges better than the standard version.
- The model is free to try on Google’s AI Studio, though it has a 32,767-token limit.
Google has introduced Gemini 2.0 Flash Thinking, an experimental AI model that lays out how it tackles tough problems in order to let you peek into its thought process and make it easier to see how it works.
Gemini 2.0 Flash Thinking blends Flash tech’s speed with the reasoning chops of OpenAI’s o1 model. The difference is that Gemini spells out its thought process, while o1 keeps things behind the curtain. That clear breakdown makes it a win for anyone needing to follow complex reasoning and dodge surprise AI slip-ups.
This unique approach helps it outshine the standard Gemini 2.0 Flash on tougher challenges.
Logan Kilpatrick, head of product for AI Studio, calls this model a big first step in Google’s push for smarter AI reasoning (via TechCrunch). Unlike most AI systems, these reasoning models can self-check their work, reducing common errors. The trade-off is that it takes a bit longer to get answers—sometimes seconds or even minutes.
Just when you thought it was over… we’re introducing Gemini 2.0 Flash Thinking, a new experimental model that unlocks stronger reasoning capabilities and shows its thoughts.The model plans (with thoughts visible), can solve complex problems with Flash speeds, and more 🧵December 19, 2024
Google DeepMind’s chief scientist, Jeff Dean, showed off on X some capabilities of Gemini 2.0 Flash Thinking.
Want to see Gemini 2.0 Flash Thinking in action? Check out this demo where the model solves a physics problem and explains its reasoning. pic.twitter.com/Nl0hYj7ZFSDecember 19, 2024
The demo featured the AI solving tough physics problems by breaking them into smaller steps, showcasing its knack for methodical problem-solving and delivering solid, reliable results.
In another demo from Kilpatrick, the model shows off its impressive reasoning skills by combining visual and text data to solve a problem. It highlights how well the model can process and blend info from different sources.
While early demos have shown some missteps or missed details, it’s important to remember that this model is still in its early stages. Even so, these first impressions highlight the impressive potential of the DeepMind AI architecture.
The new model is free for everyone to try on Google’s AI Studio platform. That said, it has a 32,767-token limit, so it’s a bit capped compared to other versions. Still, it’s impressive how quickly it handles tricky problems that usually leave regular AI models scratching their heads.
