Photo by Author | IdeogramWe are living in an interesting period, as the Generative AI emerged as a device that significantly enhances our work. Since the launch of products like Chat GPT, the arrival of large language models (LLMS) has changed basically how we live and work.
Google, as a company, certainly cannot have the opportunity to produce its LLM products, as the Gemini model has shown. In addition, Google already has many useful products of business, such as Google Sheets. Google has taken an amazing move by allowing Gemini to integrate directly into Google Sheets.
Since Google Sheets use many businesses, it will be helpful to understand how we can use Gemini AI inside it. In this article, we will go through Google Sheets through the implementation of Gemini.
Careful Let’s dive!
Google Gemini in Google Sheets
According to Google’s official announcement, the current Spreadsheet AI (Google Sheets in Google Sheets) is already available to the public, but only through Google Work Space Subscription. Try it LOO, you can find them Plans to determine the pricing And use the free trial available.
Before we try Google Gemini in Google Sheets, we need to make it available too, as the default, the feature is not automatically continued and we need to have a Google Work space admin account. Go to the Admin Dash Board and enable Gemini for Google Workpress by activating the features of Alpha within the Generative AITabs.
Once the features are enabled, try to create a new Google Sheet using your Google Work space account. After opening a new file, you will see ** Gemini icon **, which is like a picture below.
This is your Gemini assistant, where you can ask Gemini to do anything and directly to do something in Google Sheets. If you are not sure what you can do, you can always ask Gemini “what Gemini can do”.
For example, we can ask Google Gemini to create a new table and enter our sheets, which is like a picture below.
Referring to existing files or tables in Google Sheets, we can ask the Gemini model for more analysis or suggestions. For example, we can ask Gemini with our data for insights and chart suggests advice that we can prepare, as shown in the picture below.
Basically, you can ask Gemini anything, and the model will suggest or provide appropriate operations for your workflow.
In addition, you can work directly to the Google Sheet cell level using Gemini, which helps the Lord =AI Formula. The formula currently allows text generation, summary and classification.
=AI The formula takes two parameters: quick (or instruction) and optional reference cell range. Let’s start by developing a new label using it =AI Formula. For example, we can try to assign the name of the document based on the data available.
=AI("Generate a document name suitable for this row", A2:F2)After that, press the “Prepare and Insert” button to put the formula into practice.
Once =AI The formula is implemented, you can drag it into the first cells to apply it to all available data. For example, we can produce document names in five different cells, as shown below.
Even you can refer to the table overall and use the following formulas to summarize the dataset.
=AI("Summarize the data in one line", Table1)The result is text data that is like the output below.
The table outlines project management approaches, detailing their characteristics, advantages, disadvantages, suitable applications, and risk levels.
This ends the basic introduction of access and implementation of the Gemini model in Google Sheets. You can discover more and see how the model can accelerate your data analysis.
Conclusion
Google Gemini has become a primary product that helps people do its work by developing natural language indicators. Currently, Google has connected the Gemini model into Google Sheets via Google Works Space, which we can access after subscribing the project.
In this article, we learned in Google Sheets, Google Gemini directly via Gemini Sidebar and using and using =AI Formula.
I hope it has helped!
Cornelius Yodha Vijaya Data Science is Assistant Manager and Data Writer. Elijan, working in Indonesia for a full time, likes to share indicators of data and data through social media and written media. CorneLius writes on various types of AI and machine learning titles.