Google Sheets wants to use AI to flag and correct you
Google’s artificial intelligence (AI) research team has released a free machine learning (ML) add-on for Google Sheets which it claims can help anyone use predictions to fill in the gaps in their data without prior ML or coding experience.
notification Simple Machine Learning for Sheets (opens in a new tab) in one parcel (opens in a new tab) on the TensorFlow blog, the team stated that small businesses, students, and even scientists and analysts at large corporations can find uses for spreadsheet softwareits new feature to make valuable predictions or even just save yourself time in error detection.
It also suggests that those familiar with ML can also benefit from productivity boost offers add-ons, with “training, evaluating, interpreting and exporting a model” taking “5 clicks and as little as 10 seconds”.
Machine learning ability
Machine learning algorithms are trained on huge sets of data to be able to make human-readable predictions without explicit programming. When they predict, they become better at making predictions.
This is the latest example of AI-driven machine learning in consumer-level applications. AI implementation company openAI (opens in a new tab)For example, a third-party GPT-3 neural network that powers any number of AI writer and image creation 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 machine learning’s capabilities, limitations, and how it works are fully provided with Google Basic and Advanced Courses (opens in a new tab).
Even so, newbies and enthusiasts alike can benefit from leveraging “modern ML technology” inside the Sheets extension, which Google claims powers it. data classification library TensorFlow Decision Forest (opens in a new tab). It also promises that no predictive data is shared or owned by Google or any other company.
Once the user has installed the extension, the user can take advantage of the technology by opening the Extensions tab in their open Sheets spreadsheet, starting simple ML and using the simple user interface simple to design the most suitable task. From there, the data can be applied just like any manually sourced data in a given use case.
However, even Google wants to emphasize that ML-driven predictions are just that and should not be taken as a guarantee of factual information. Therefore, it is worth double-checking all the predictions made to ensure accuracy.