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Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
Interesting, I would love to hear how well those worked.

Grammit uses the Prompt API for the local LLM, which currently uses a version of the Gemma 3n model on Chrome.

Grammit uses prompting instead of fine-tuning or custom training. Simplified, it has a system prompt along the lines of: "Rewrite this text, correcting any grammar or spelling mistakes," combined with a prefilled conversation containing a number of examples showing an input sentence and the corrected output.

Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
Yes, Chrome uses the Gemini Nano model for the Prompt API while Edge uses the Phi-4-mini model.
Comment · 1 year ago
We're building a Chrome extension grammar checker that runs locally using Chrome's built-in LLM.

You can try it out here:

https://chromewebstore.google.com/detail/grammit-the-ai-gram...

LLMs can also correct other sorts of mistakes, such as correcting "The first US President was _Ben Franklin_" to "George Washington".

Comment · 2 years ago
Epic is not a customer of Apple.

Many of Apple's customers are also customers of Epic.

Apple is trying to prevent those shared customers from accessing Epic.

Comment · 3 years ago
I've created a few DSL's and I've regretted not closely emulating an existing language that users already know.

When creating a new DSL you should find the language that is most familiar to your users. That could be Python, Javascript, or SQL. There is a good chance though that it is spreadsheet formulas.

Whatever that language, align capabilities you add to your DSL with the syntax and function naming of that language only diverging where needed to add the custom capabilities which motivated the DSL.

The closer you align with what your users already know, the more easily they will be able to adopt it. An added benefit of this that emerged in the past year is GPT's will be able to write your DSL with less prompting.

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