Learn how Copilot can help you improve your workflow by assisting you with your documents and tasks
In today’s world, we often need to create and improve various types of documents. We also need to perform tasks for different purposes and audiences. Whether it is drafting a report, coding a web page, analyzing data, or preparing a presentation, we face many challenges and difficulties. These could stem from a lack of time, skills, or inspiration. The need to deal with errors, issues, or feedback; or even simply feeling “stuck” and not knowing how to get something we can work with onto the screen. How can we overcome these challenges and difficulties and produce high-quality, relevant, and accurate work faster and easier? Microsoft Copilot offers solutions!
Microsoft Copilot offers compelling answers to these questions. Copilot is a new service from Microsoft that uses artificial intelligence (AI) to assist us in creating and improving documents and performing tasks. Copilot is powered by large language models (LLMs). LLMs are computer programs that can generate natural language responses based on a given prompt. The service is not limited to one LLM, but rather coordinates multiple LLMs. This produces high-quality, relevant, and accurate suggestions for various kinds of work, such as writing, coding, data analysis, or presentation.
In this blog post, we will introduce Copilot and explain how it works, how to use it, and what it can do for us. We will also discuss Copilot’s benefits, challenges, and best practices. We will give you some examples and tips to start with Copilot.
Copilot: Much More than a Large Language Model
As mentioned in the introduction, Copilot coordinates multiple LLMs to produce both accurate and relevant output. But what is an LLM? Various sources such as books, articles, websites, or code repositories provide vast amounts of text data for training LLMs. Large Language Models learn the patterns, rules, and structures of natural language. LLMs then can use them to generate new texts based on a given prompt. LLMs can also learn the content, meaning, and context of natural language, and can use them to generate relevant and accurate texts based on a given prompt.
Copilot uses multiple LLMs, each specialized in a different type of work, such as writing, coding, data analysis, or presentation. Copilot coordinates these LLMs to provide us with the best suggestions for our specific use cases and preferences. Also, Copilot uses other AI techniques, (such as grounding, post-processing, and output). These techniques enhance the quality, relevance, and accuracy of the suggestions.
Grounding is the process of understanding the context of our specific use case, using information that is not available as part of the LLM’s trained knowledge. This information can include online resources, previous work, or our own input. Grounding ensures that the generated output matches our needs and preferences. However, ir does not contradict or conflict with the existing information. For example, if we want to write a report about a specific topic, grounding can help the LLM to use relevant sources, facts, or arguments, and avoid using irrelevant or incorrect information.
Post-processing is the process of checking the output for potential issues. These include errors, plagiarism, bias, or ethical concerns, and flagging them for our review. Post-processing ensures that the generated output is safe, secure, and compliant with responsible AI principles. It does not cause any harm or damage to us or others. For example, if we want to code a web page, post-processing can help the LLM to find and fix any errors, bugs, or vulnerabilities in the code, and alert us to any potential security, compliance, or privacy issues.
Output is the process of presenting the output in a suitable format, style, and level of detail, according to our prompt and preferences. Output ensures that the generated output is clear, concise, and specific, and meets our expectations and requirements. For example, if we want to prepare a presentation, output can help the LLM to generate the appropriate slides, charts, graphs, or tables, and use the suitable language, tone, and voice for our audience and purpose.
How do you construct a Copilot prompt?
To use Copilot, we need to construct a prompt that tells the service what kind of work we want to create or improve. A prompt can be a natural language description. A document snippet, a task name, a question, or a combination of these elements. The prompt should be clear, concise, and specific. It should include any relevant information or constraints that we want the service to consider. For example, we can specify the type of work, the format, the style, the audience, the purpose, or the deadline that we want the service to follow.
The prompt can also include keywords or phrases that indicate the level of detail, complexity, or creativity that we want the service to use. For example, we can use words like “simple”, “advanced”, “optimized”, “elegant”, “novel”, or “creative” to guide the service in creating or improving the work. We can also use words like “explain”, “show”, “demonstrate”, or “illustrate” to ask the service to provide additional information or examples for the work.
For example, if we want to write a blog post about Copilot and how it works, we can construct a prompt like this:
Write a blog post about Microsoft Copilot and how it works. The blog post should be about 2000 words long and should have a title, a subtitle, an introduction, a main body, and a conclusion. The blog post should explain what Copilot is, how it works, how to use it, and what it can do for us. It should also discuss some of the benefits and challenges. Include best practices of using Copilot, and provide some examples and tips to help us get started with Copilot. The blog post should be written in a clear, concise, and engaging style, and should use simple and accessible language. The blog post should be suitable for a general audience interested in technology and innovation.
If we want to code a web page that displays a table of data, we can construct a prompt like this:
If we want to prepare a presentation that summarizes the results of a data analysis, we can construct a prompt like this:
Prepare a presentation that summarizes the results of a data analysis. The presentation should use PowerPoint and should have 10 slides. The presentation should have a title slide, an introduction slide, a data slide, a method slide, a result slide, a discussion slide, a conclusion slide, a recommendation slide, and a reference slide. It should show the data, the method, the results, the discussion, the conclusion, and the recommendations of the data analysis clearly and concisely. The presentation should also use charts, graphs, or tables to illustrate the data and the results. The presentation should be professional, persuasive, and informative, and should use suitable language, tone, and voice for the target audience and purpose.
What can Copilot do for you?
Provide suggestions tailored to our specific use cases and preferences. Copilot can help us perform our work faster and easier. Microsoft Copilot also helps us with various tasks, such as:
- Writing documents, such as reports, proposals, emails, or blogs, by generating complete or partial texts based on our prompt. Copilot can help us write documents from scratch, or improve existing documents, by adding, deleting, or modifying texts. Copilot can also help us write documents for different purposes and audiences. Some examples include informative, persuasive, or entertaining, and use the appropriate language, tone, and voice.
- Editing documents, by improving the grammar, spelling, or punctuation. Style of our texts, or by suggesting alternative words, phrases, or sentences. Copilot can help us edit documents for clarity, correctness, or consistency. It finds and fixes any errors, mistakes, or inconsistencies in our texts. Microsoft Copilot can also help us edit documents for variety, coherence, or elegance. It suggests alternative ways of expressing our ideas, connecting our sentences, or enhancing our style.
- Enhancing documents, by adding features, such as images, charts, graphs, or tables, based on our prompt. Copilot can help us enhance documents by generating or inserting features that complement or illustrate our texts or codes. Copilot can also help us enhance documents by adjusting or modifying features that improve or optimize our texts or codes. Copilot can also help us enhance documents by using features that are suitable for our format, style, or purpose.
- Reviewing documents, by finding and fixing issues, such as errors, inconsistencies, or redundancies, in our texts or codes, or by providing feedback or comments that explain the work. Copilot can help us review documents by checking or testing our texts or codes for any issues. These include errors, bugs, or vulnerabilities, and suggesting or applying solutions or fixes. Copilot can also help us review documents by providing feedback or comments. This feedback evaluates or explains our texts or codes, such as strengths, weaknesses, or suggestions.
- Learning documents, by providing examples, explanations, or tutorials for various topics, formats, or skills that we want to learn or improve. Copilot can help us learn documents by generating or showing examples. These examples demonstrate or illustrate these topics, formats, or skills, such as concepts, methods, or techniques. Copilot can also help us learn documents. It provides explanations or tutorials that describe or teach different topics, formats, or skills, such as definitions, steps, or tips.
Copilot can also help us with other tasks, such as generating data, queries, summaries, reviews, or feedback, based on our prompt; generating data, such as numbers, texts, or images, that are relevant or useful for our work, such as statistics, facts, or quotes; generate queries, such as questions, requests, or commands, that are appropriate or helpful for our work; or help us get “unstuck” by suggesting queries, searches, or actions. Because it leverages LLMs, Copilot is especially useful for analyzing, summarizing, and extracting the information contained in natural language documents, especially when there are many such documents stored in different locations. Copilot can help us discover and organize these documents. Then it generates abstracts, overviews, or highlights, that are concise and informative for our work.
How to get started with Copilot?
To get started with Copilot, we need to sign up for the service and install the Copilot extension for our preferred document editor. We can sign up for Copilot at https://copilot.microsoft.com/. There are Copilot extensions for various document editors, such as Word, Excel, PowerPoint, Visual Studio Code, or Google Docs. We can also use Copilot on the web. Access the Copilot website or the built-in Copilot button (if browsing in Microsoft Edge).
Once installed, we can start using Copilot by constructing a prompt and pressing the Copilot button on our document editor. Copilot will then generate one or more suggestions for our prompt, and show them on our document editor. We can then review the suggestions, and choose to accept, reject, or modify them. We can also provide feedback to Copilot, by rating or commenting on the suggestions. Also, report any issues or problems. If Copilot’s initial output doesn’t quite meet our needs, we can instruct Copilot to modify its output to have a specific tone (such as informal or professional) or target a specific audience (such as general business users, IT professionals, or the C-Suite). We can also further customize our Copilot experience by adjusting Copilot’s settings and preferences. These settings allow us to adjust the language, format, style, level of detail, complexity, and creativity of Copilot’s suggestions.