Category Archives: Week-14

OPEN SOURCE VS. COMMERCIAL LICENSING

A few weeks ago, I learned about the necessity of publishing code under a license and now that I have had the chance to implement proper licensing into assignments that I have been tasked with, I wanted to take a second and closer look at the positives and negatives associated with publishing software as “Open Source” as opposed to under commercial licensing. Before writing this blog post, I did some research and came across a blog titled, “Open Source vs. Commercial Software License: What Do You Need?” by Frank Amissah, which does a good job comparing and differentiating open-source licensing from commercial licensing.

OPEN SOURCE:

Open source code is source code that has been made available to the public for free, allowing for anyone to read, share, or modify it. Open software licensing is divided into two categories, these being “Permissive” and “Copyleft”. Permissive licensing is less restrictive, allowing people to do as they please with the code, often only requiring the original author to be credited. Copyleft licensing is more restrictive, requiring future redistribution of code under a copyleft license to also abide by the terms of the originally implemented copyleft license. Open source code is easily accessible and adaptable by a community. The ease of acquiring the code also allows for a large scale of quality improvements and innovation provided by the community to be officially implemented. This, however, comes as a downside being that there is very limited funding for the future development of the code and if its users lose interest, it will ultimately be abandoned entirely.

COMMERCIAL LICENSING:

Commercial licensed software is usually proprietary and is distributed with the intent of its developer making a profit. The terms of use of the software is identified directly by the developer, but in general, licenses for their use will exist in the forms of subscription services or one-time payments, either for one user or an entire team of users. Benefits of using a commercial license include establishing direct ownership of the software for its users, as well as constant funding for improvements through the purchasing of copies of the software. On the other hand, commercial licenses often cost a lot of money to their customers, have longer development cycles for implementing changes, and suffer highly from piracy of the software.

This blog post effectively compared the similarities and differences of both open source and commercial licensed software, even going so far as to teach me that the choice for which license to implement will come down to the goals of the project, as well as its intended audience and cost of operation. It was also formatted in a very user-friendly way, using well-organized diagrams to prove its point. Going forward, I feel that I will be more inclined to take my time weighing my choices when it comes to choosing the right license for my projects, especially now that I have been made aware of the difference one can make.

Blog Referenced: Open Source vs. Commercial Software License: What Do You Need? | Turing

From the blog CS@Worcester – CS Blogs with Aidan by anoone234 and used with permission of the author. All other rights reserved by the author.

Microsoft’s Solution to Offensive Generated Text

Recently, I have been made aware of a “Alex” linter, which is capable of analyzing the words used in a program and identifying ones that may be offensive or used in a harmful context. This got me interested in looking further into what other forms of software are being used to perform similar actions and where.

In order to learn more on the topic, I have read a blog titled, “Microsoft claims its new tools make language models safer to use” by Kyle Wiggers. This article goes in depth about how Microsoft has been developing open-source tools to audit AI generated content and automatically test them for potential bugs, especially in a content moderation context, where “toxic speech” may be used. Microsoft has focused their efforts on two projects for this cause.

ToxiGen is a dataset that contains 274,000 examples of statements that may be considered “toxic” or “neutral”, acting as a massive hate speech dataset and functioning in a similar but much greater scale of what the “Alex” linter does. ToxiGen is being used by researchers on LLMs similar to ChatGPT to generate statements that are likely to be misidentified and aid in finding potential weaknesses in these generative tools.

AdaTest is the second program Microsoft is focusing on developing and should help address larger issues with AI language modules. It functionally generates a large number of tests, steered by human guidance, and organizes them into similar groupings. It is run with the goal of adding diversity to test cases and enhancing the reliability of LLMs.

From my perspective, generative AI does not possess cognitive function in a comparable manner to that of a human and until it does, AI will forever struggle at identifying speech that may be acceptable in one context or culture but viewed as very offensive in a separate culture or environment. I also believe that because these newly developed programs are being made in the same way that the “Alex” linter is (that being through someone providing a list of key words or phrases to be cross referenced) and is not able to generate its own list of potentially harmful or “toxic” terms without human oversight, the most these programs will likely be able to do is provide quality standards for LLMs through testing.

Through my research, I became aware of programs being developed by Microsoft to help detect harmful speech in a similar way that the “Alex” linter does (that being through cross referencing with a dataset). I also became aware of the many forms of biases that exist even in generative AI as a result of information provided by biased human input. Moving forward, I plan on being more careful with the phrasings I give or artificially generated when working on projects. Given that AdaTest is an open-source software as well, I am interested in using it in the future to test for bias and offensive speech wherever I use generative AI.

Blog Referenced: Microsoft claims its new tools make language models safer to use | TechCrunch

From the blog CS@Worcester – CS Blogs with Aidan by anoone234 and used with permission of the author. All other rights reserved by the author.

A List of Open Source Software

Open-Source software has become a vital source of tools for the development community, as well as innovative software. Recently I have become interested in finding out just how many of the applications I use are open-source, while at the same time finding new open-source software. I want to expand the software I have at my selection. First, let us reestablish what open-source software means: software that can be modified, enhanced, or inspected by developers who are not the original creators. This is done by packaging the source code along with the software so that it can be edited by anyone who knows how to.

To start off this extensive list, Mozilla Firefox is open source to my surprise. Firefox has its source code internally available within the browser itself and can be found by using the URL https://searchfox.org/mozilla-central/source and has guidelines for contributors up on a separate website. Mozilla also has the source code for countless other projects up on GitHub, such as Gecko, the rendering engine for Firefox. Continuing down the list we got GIMP and Blender, two powerful tools for any aspiring artist out there. In recent days I actually downloaded Blender onto some of the computers at the school I work at. While I am not going introduce 3D modeling to my middle schoolers, there have been students who have shown an interest in the subject. I thought having Blender available to these students would foster interest and motivate these students to pursue more. It is for situations like these that I believe in the importance of open-source software and the need to have these tools available to all. GIMP has helped me out here and there in the past, and since it is the only image manipulation software that is free, I am also planning to implement it in my classroom.

One of the most important pieces of open-source software is none other than the operating system Linux. So many pieces of technology are running on Linux, or some variation thereof. Android OS is based on Linux and is also open source, Chromebook OS is based off Linux, several routers are using Linux. From cars, TVs, to even super computers, Linux has been a reliable operating system for a massive amount of hardware. Even NASA has completely switched over to Linux as of 2013. I am partially convinced to convert to Linux after all the compelling evidence I found.

Finally, I have already mentioned LibreOffice in a previous blogpost as well, but it bears mentioning here. Microsoft Office is such a ubiquitous piece of software it is almost impossible to work in any sector of society that does not make use of it. The downside is that it is expensive for many. This is where LibreOffice comes in and offers a free alternative that does not require making an account of some kind like Google’s services. It perfectly embodies the spirit of open-source software.

https://opensource.com/resources/what-open-source