CoPilot vs. GitHub Copilot

I used it recently to go over a syllabus. It caught errors in grading where there were overlaps in the grading scale. It also caught a section that was deemed to be problematic as it could have created a conflict in grading based on the subjectiveness of the score and how it was determined

Incentivized

Copilit is fantastic at the following: 1. Solving simple, well-defined problems, such as implementing an algorithm, manipulating a data structure, or string manipulation and regex. 2. Implementing simple APIs that are mainly CRUD in nature, with moderate business logic inside them, which may involve some processing or passing the data through an algorithm. 3. Implementation of well-defined activities, such as implementing a connection to an Oracle DB using Hibernate or JDBC, or implementing boilerplate code for a backend service to listen to Kafka events. It is not that great when it comes to understanding and implementing code in a proprietary DSL. It struggles when implementing a major feature across a complex codebase. I believe developers should also adopt the trust-but-verify paradigm when expecting highly secure or regulated code from GitHub Copilot.

Incentivized

• Examines a syllabus for errors or contradictions in grading
• It works as a great starting point for doing research
• We use it to aid in developing classroom instruction

Incentivized

• Make code development faster and quicker.
• Helps write better code standards for projects.
• Provide the latest functions from the technology.
• Notifies about the deprecated functions.

Incentivized

• I would like to see better image creation tools
• More tools in creating custom GPTs
• Easier tools to limit and create the data used for the LLM

Incentivized

• The only issue I faced is the context token size, it can be increase.
• Sometime with agent mode it takes too much time, which can be reduced but I understand it also depends on the complexity of the given task.

Incentivized

I feel that GitHub Copilot's overall usability is good due to its tight integration with Visual Studio and the workspace. However, developers expect greater ease of use, as there is a learning curve to realize productivity gains with the tool fully. I think there is room for improvement in GitHub Copilot's UI integration within Visual Studio.

Incentivized

The primary reason is the integration into Office 360. Having the AI tool built into all of the office apps was a game changer in my opinion. Being able to use it in Word to help rewrite a sentence or look up a reference. In Excel, I have used to to build formulas or write simple code.

Incentivized

It is useful that copilot integrates so well with vscode, which is a very common IDE. I used Tabnine for a little while but it was not that intuitive, and did not seem as helpful as GitHub copilot was. I have enjoyed GitHub copilot a lot, especially the ease of hitting the tab key and seeing quick progress in my tasks.

Incentivized

• It is too early to tell at the moment but I can see it as a positive moving forward
• The amount of time saved in creating content will be a huge asset for faculty
• The same holds true for students as they to will be able to safe a lot of time

Incentivized

• Our ROI of the purchase of Copilot was met in less than a day. The timesave cannot be overstated
• Programmer boredom/dissatisfaction is down because of less repetetive crud work.

Incentivized