Add grammarly to microsoft edge -
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Add grammarly to microsoft edge - |
Add grammarly to microsoft edge. Microsoft is adding a Grammarly-like feature to the Edge browser
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Below is the detailed steps for how to install Chrome extensions in Edge. Step 1. Open the new Microsoft Edge browser, and click the three-dot icon at the upper-right corner in browser. Click Extensions option. Step 2. Premium users tend to write more text than other users and also frequently copy and paste longer texts to get writing feedback. When they had a high volume of suggestions, they could only accept them one by one—and were spending too much time accepting each spelling or grammar mistake.
This could be tedious and time-consuming. Shape the way millions of people communicate! Open Roles. It was an interesting road to get here. We went through several iterations of the design, and had to carefully consider trade-offs to arrive at a feature that balances convenience and control in the right ways.
From the natural language processing NLP model to the front-end and backend, this feature was essentially bootstrapped from various side projects that ultimately fit together in a cohesive way. The problem was clear: Grammarly Premium users were spending too much time making clicks to accept high numbers of suggestions one by one.
Would this solution solve the problem our Premium users were facing? Helpfully, there is a pattern that we can see when we look at the data.
When the suggestions are about grammar, spelling, and punctuation—those rules of language concerning writing mechanics—they are accepted at a high rate. From a user perspective, accepting fewer suggestions for clarity, structure, and tone is quite understandable.
One just has to look at the world of professional editing for an analogy. When a proofreader catches a typo, the writer almost always breathes a sigh of gratitude and never gives it another thought. This finding had implications for the feature we were developing. For accepting multiple suggestions at once, we selected metrics that could show engagement, repeat engagement, and quality:. When testing any new model for a feature, we always analyze precision and recall.
Precision is the trickier of the two. And we then chose to look at how often users reverted suggestions to get a measure of how valuable they were finding this new functionality.
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