We live in an exhilarating era, because generative artificial intelligence appeared as a tool that significantly improves our work. Since the premiere of products such as chatgpt, the arrival of huge language models (LLM) has fundamentally changed the way of life and work.
Google, as a company, would certainly not skip the chance to develop its own LLM products, as the Gemini model showed. In addition, Google already has many useful business products, such as Google Arkus. Google made a fantastic movement, allowing Gemini to integrate directly with Google sheets.
Since many companies are used by Google Sheets, it will be helpful to understand how we can operate AI Gemini in it. In this article we will go to the implementation of Gemini from Google Arreets.
Inquisitive? Let’s immerse ourselves!
Google Gemini in Google sheets
According to the official announcement of Google, present AI spreadsheet AI (Twins in Google Arreets) is already available to the audience, but only through the subscription to Google’s working space. To try it out, you can examine them Price plans And operate the available free test.
Before we try Google Gemini in Google sheets, we also need to make them available, because by default the function is not automatically enabled and requires us to be an administrator account in Google. Go to the administrator’s dashboard and turn on Gemini for Google Workspace, including alpha functions as part of AI generative.
After turning on the function, try to create a recent Google sheet with a Google Workspace account. After opening the recent file, you will see the ** Gemini icon **, just like the image below.
This is your twin assistant in which you can ask for everything and direct Gemini to perform specific actions in Google sheets. If you are not sure what you can do, you can always ask Gemini “What can Gemini” in Monita.
For example, we can ask Google Gemini to create a recent table and put it in our sheets, just like the picture below.
Referring to existing files or tables in Google sheets, we may ask the Gemini model about further analysis or suggestions. For example, we could ask Gemini to observe our data and suggestions regarding charts that we could develop, as shown in the picture below.
Basically, you can ask Gemini about everything, and the model will suggest or provide actions suitable for your workflow.
Additionally, you can work directly at Google’s cell levels using Gemini, which is facilitated by =AI formula. Currently, the formula allows you to generate text, summary and classification.
. =AI The formula adopts two parameters: prompt (or instructions) and the optional range of reference cells. Let’s start by generating a recent label with =AI formula. For example, we can try to assign the name of the document on the basis of your data.
=AI("Generate a document name suitable for this row", A2:F2)Then press the “Generate and insert” button to make a formula.
Once =AI The formula is performed, you can drag it to the cells below the first to apply them to all available data. For example, we can generate document names in five different cells, as shown below.
You can even call the table as a whole and operate the following formula to summarize the data set.
=AI("Summarize the data in one line", Table1)The result is text data similar to the results below.
The table outlines project management approaches, detailing their characteristics, advantages, disadvantages, suitable applications, and risk levels.
This ends the basic introduction to access and implementation of the Gemini model in Google sheets. You can continue to examine and see how the model can speed up data analysis.
Application
Google Gemini has become a basic product that helps people in their work, generating a text based on a natural language error. Currently, Google has integrated the Gemini model with Google sheets via Google Workspace, to which we can access after subscription to the plan.
In this article, we have learned to operate Google Gemini directly in Google sheets, both via the Gemini side belt and with the support =AI formula.
I hope it helped!
Cornellius Yudha Wijaya He is a data assistant and data writer. Working full -time at Allianz Indonesia, he loves to share Python and data tips through social media and media writing. Cornellius writes on various AI topics and machine learning.