Google’s Artificial Intelligence (AI) research team has released a free machine learning (ML) add-on. Google Sheets claims it can help anyone use predictions to fill data gaps with no prior experience with machine learning or code.
Announcement Simple ML for Sheets (opens in a new tab) in Post (opens in a new tab) On the TensorFlow blog, the team found that small businesses, students, and even researchers and analysts at large corporations could use the new spreadsheet feature to make valuable predictions, or even just save time on bug-finding.
It also suggests that those familiar with ML can also benefit performance improvements provided that the “train, evaluate, interpret and export model” add-on takes “5 clicks and only 10 seconds”.
Machine learning capabilities
Machine learning algorithms are trained on huge datasets to be able to make human-readable predictions without the need for programming. When they predict, they become better at predicting.
This is the latest example of using AI-based machine learning for consumer applications. A company that implements artificial intelligence OpenAI (opens in a new tab)The company’s GPT-3 neural network, for example, powers any number of third parties AI writers and image generation services, including those provided by OpenAI itself such as Playground (opens in a new tab) and DALL E (opens in a new tab).
Those who want to learn more about the possibilities, limitations and how machine learning works are well prepared Basic and Advanced Google Courses (opens in a new tab).
Still, both novices and enthusiasts alike can benefit from the use of “state-of-the-art ML technology” in the Sheets extension, which Google says already feeds into the data classification library TensorFlow decision forests (opens in a new tab). It also promises that no forecast data is shared with or owned by Google or any other company.
Once the extension is installed, users can take advantage of the technology by opening the Extensions tab in an open Sheets spreadsheet, launching Simple ML, and using the simple UI to design the most appropriate task. From there, the data can be applied in the same way as any manually ingested data in a given use case.
However, even Google is keen to point out that ML based predictions are just that and should not be taken as a guarantee of factual information. Therefore, it is worth checking all forecasts carefully for accuracy.