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A few months ago, Google Addition of access to reasoning methods to your Gemini AI chatbot. Now he has widened the scope of Gemini 2.0 Flash Thinking Experimental to the other features of the cat experience because it doubles on the responses filled with context.
The company has announced that it makes Gemini more personal, connected and useful. It also makes its version of Deep Research, which is looking for information on the Internet, more widely available for users of Gemini.
In -depth research will now be supported by Gemini 2.0 Flash Thinking Experimental. Google has declared in a blog article by adding the power of flash thought, in -depth research can now give users a “real -time overview on the way it happens to resolve your research tasks”. The company said that this combination would improve the quality of the reports carried out thanks to in -depth research by providing more details and information.
Before this update, Gemini 1.5 PRO propelled deep research and was only available on the premium Google One AI level of $ 20 per month. However, Carl Franzen de Venturebeat even found this less powerful version Be a useful research assistant.
A more personal Gemini
Gemini 2.0 Flash Thinking Experimental will also feed a new capacity called personalization.
Personalization is precisely this: the answers will be more suitable for the user by referring to previous conversations or research. To activate this level of customization, GEMINI connects to Google user apps and services, including search and photos. Google stressed that it would only use your Google applications with permission.
“In the coming months, Gemini will broaden its ability to understand yourself by connecting to other Google applications and services, including photos and YouTube,” said Dave Lemon, Product Management Director, Gemini App, in a blog article. “This will allow Gemini to provide more personalized information, by drawing a broader understanding of your activities and preferences to provide answers that really resonate with you.”
Since Gemini 2.0 Flash Thinking Experimental is integrated into the personalization function, users can see an overview of data sources that the Tape model to respond to requests or to complete requests.
Gemini’s advanced users can switch to other preferences they want the chatbot to remember, as asking it to refer to past conversations or to remind him of food restrictions. This allows Gemini to offer more natural and relevant responses.
Of course, Google is not the only company to recognize the importance of personalized and relevant responses. In November, Anthropic Launched his styles Functionality, which allows people to personalize how Claude speaks to them.
More connected applications
As personalization requires access to more data on the user, consider it a cloth, but for a user of Gemini rather than a whole organization, Google connecting more of its services to Gemini 2.0 Flash Thinking Experimental.
The model can press applications such as calendar, notes, tasks and photos.
“With this model of reflection, Gemini can better tackle complex requests such as prompts that imply several applications, because the new model can reason better on global demand, decompose it in distinct steps and assess its own progress as and when,” said Lemon.
Google said that in a few weeks, Gemini will be able to look at photos on Google Photos and answer questions based on user images. It can create travel routes based on recent travel photos, and recall information such as the expiration date of a driving license, or if you have taken a photo of milk in the store.
The integration of applications to provide more context to Chatbot responses was a great trend for AI companies. This resulted in access to chatbots to developers in the business space. Chatgpt can open most of the ideas Thus, developers can bring their VSCODE code and question Chatgpt on this subject. Google coding assistance, code assistance, also connects to ideas.
The growing integration of Google’s applications and services and the personalization of Gemini highlight the importance of the context and data to make these chatbots more useful, even if the request simply requires a restaurant recommendation.
