A few months ago, Google added access to reasoning modes to its Gemini AI chatbot. Now, it’s expanded the reach of Gemini 2.0 Flash Thinking Experimental to other features of the chat experience as it doubles down on context-filled responses. 

The company announced it’s making Gemini more personal, connected and helpful. It’s also making its version of Deep Research, which searches the Internet for information, more widely available to Gemini users. 

Deep Research will now be backed by Gemini 2.0 Flash Thinking Experimental. Google said in a blog post that, by adding the power of Flash Thinking, Deep Research can now give users “a real-time look into how it’s going about solving your research tasks.” The company said this combination will improve the quality of reports done through Deep Research by providing more details and insights. 

Before this update, Gemini 1.5 Pro powered Deep Research and was only available on the $20-a-month Google One AI Premium plan. However, VentureBeat’s Carl Franzen found even this now less-powerful version to be a helpful research assistant. 

A more personal Gemini

Gemini 2.0 Flash Thinking Experimental will also power a new capability called personalization. 

Personalization is precisely that: Responses will be more tailored to the user by referencing previous conversations or searches. To enable this level of personalization, Gemini connects to users’ Google apps and services, including Search and Photos. Google emphasized that it will use information from your Google apps only with permission. 

“In the coming months, Gemini will expand its ability to understand you by connecting with other Google apps and services, including Photos and YouTube,” Dave Citron, senior director, product management, Gemini app, said in a blog post. “This will enable Gemini to provide more personalized insights, drawing from a broader understanding of your activities and preferences to deliver responses that truly resonate with you.”

Since Gemini 2.0 Flash Thinking Experimental is built into the personalization feature, users can see an outline of which data sources the model is tapping to answer queries or to complete requests. 

Gemini Advanced users can toggle other preferences they want the chatbot to remember, such as instructing it to refer to past conversations or reminding it of dietary restrictions. This allows Gemini to offer more natural and relevant responses.

Of course, Google is not the only company that recognizes the importance of personalized and relevant responses. In November, Anthropic launched its Styles feature, which allows people to customize how Claude speaks to them. 

More connected apps

As personalization requires access to more data about the user, think of it as RAG, but for a Gemini user rather than an entire organization, with Google connecting more of its services to Gemini 2.0 Flash Thinking Experimental. 

The model can tap apps like Calendar, Notes, Tasks and Photos. 

“With this thinking model, Gemini can better tackle complex requests like prompts that involve multiple apps, because the new model can better reason over the overall request, break it down into distinct steps, and assess its own progress as it goes,” Citron said. 

Google said that in a couple of weeks, Gemini will be able to look at photos in Google Photos and answer questions based on users’ images. It can create travel itineraries based on pictures from recent trips, and recall information like the expiration date for a driver’s license, or whether you happen to have taken a photo of milk in the store. 

Integrating applications to provide more context to chatbot responses has been a big trend for AI companies. This has translated to giving chatbots access to developer environments or emails in the enterprise space. ChatGPT can open most IDEs so developers can bring their code from VSCode and query ChatGPT about it. Google’s coding helper, Code Assist, also connects to IDEs. 

Google’s increasing app and service integration and personalizing Gemini underscore the importance of context and data in making these chatbots more useful, even if the query is just asking for a restaurant recommendation.