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Email&Tasks: Jira Cloud for Gmail is a suite of three add-ons (Atlassian Marketplace, Google Workspace Marketplace connector for Gmail, and Chrome browser extension). The add-on is designed to optimize task management processes, such as quick access to tasks and any operations with them, as well as detecting tasks in emails in an inbox, etc. We described its work in more detail in the articles - Jira & Gmail – the perfect tandem for your team's productivity, Convert emails into Jira issues and not only.
The main function around which the app is built is the conversion of emails into tasks in Jira. It is possible in manual mode and with the revolutionary 1-CLICK TASK option. This feature is made possible by an AI solution.
The team worked hard to improve the automatic task detection in emails and implemented GPT-3 technology in the app. So, let's talk about why it was done, what preceded it, and what we got as a result.
GPT-3 (Generative Pre-trained Transformer 3) is a natural language processing model developed by OpenAI. It is the latest and most powerful version of the GPT series of models based on a deep-learning architecture called a transformer. GPT-3 contains 175 billion parameters.
GPT-3 has many capabilities, including translation, question answering, completion, and generation. It can understand natural language and generate human-like responses, making it useful for tasks such as chatbots, virtual assistants, and speech applications. GPT-3 can also be customized to perform specific tasks such as sentiment analysis, generalization, and language modeling.
One of the unique features of the GPT-3 is its ability to perform multi-shot and zero-shot learning. Multiple-shot learning involves training the model on only a few task examples. In contrast, zero-shot learning allows the model to perform tasks for which it has not been specifically trained using existing knowledge and context.
Previously, our developers used the Codeq API to recognize tasks in the email content. Codeq's proprietary NLP technology offers advanced deep-learning models and linguistic analysis tools to extract rich representations from your textual data. Codeq API is optimized for accuracy and precision in understanding and responding to task classification. Despite all its capabilities, this solution did not fully satisfy us, so we decided to implement GPT-3.
What is the difference? Let's try to compare these two technologies.
Natural language is recognized, but the result is often negative in terms of quality
Wide range of natural language processing tasks
Very high accuracy in natural language recognition. Much better than Codeq API
Highly specialized in task classification
Broad-based but may require fine-tuning for specific tasks
Supports a wide range of natural languages
Available for commercial use
Available for commercial use
Large-scale general-purpose text corpora
Since the application works with natural language, switching to this technology was logical. Let's look at an example of email detection with GPT-3 already implemented.
This technology allows you to recognize the text of emails and transform them into Jira tasks.
How does it work?
Now you just need to click the Create issue button.
So, a few seconds and you're done. Note that if the email contains attachments, checking the Include email Attachments box will automatically attach them to the issue.
Implementing GPT-3 in Email&Tasks: Jira Cloud for Gmail app is not the only thing we are preparing to improve its performance. Everything is for the user's convenience; everything is for optimizing workflows. Try to test this AI-powered app, and be sure to write to us about your impressions. We've got a 30-day trial for you to see its benefits. Also, note that the add-on is free for teams of up to 10 users. Enjoy!
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