Sat. Mar 25th, 2023

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Victor Tuson Palau, Chief Technology Officer at Ebury, explores how one of the most transformational new trends could affect the tech world.

Will AI coding like ChatGPT revolutionise software development?

Image source: Pexls/Tara Winstead

Today, it’s hard to go on any social media platform, and not come across an AI generated work of art or student assignment. But beyond these novelty uses of technology, there are real practical applications in the tech and software program development industry.  

GitHub, for example , is the particular lead source management solution in the industry, plus it was acquired by Microsoft in 2018. In late October 2021, GitHub launched Copilot, advertising it as your “Pair Programming” companion.

Pair programming is a software development technique in which two programmers work together at one workstation to produce higher quality software. The function of Copilot is that it replaces one of the two developers, therefore halving software production costs.  

Essentially, GitHub Copilot is able to write simple code upon request, simply by turning natural language prompts into code suggestions throughout dozens associated with languages.  

OpenAI’s ChatGPT can also be used in order to generate easy code structures, to review code and tell you what its function is.

This almost sounds too good to be true – coding software that has the potential be the next revolution in lowering the cost of software development plus outstrip alternatives like no-code solutions.

That said, maybe it is too idealistic. The code undoubtedly works but whose code will be it? Both OpenAI and ChatGPT admit that their algorithms are trained on publicly available code that they don’t own. Even ChatGPT has concerns about it:


Open resource projects have made collaboration possible at a scale not seen before in any industry, however, open supply can be Free as in Beer (you don’t have to pay for it) but not necessarily Totally free as within Speech (you can do whatever you want with it).  

Most open source code is usually licensed, and different licences allow you to use the particular code under different conditions, but crucially, they do not transfer ownership or allow unrestricted use of its Intellectual Property to the user.

The key question is how much these types of algorithms are usually inspired by others’ program code or are they just copying it? Of course , OpenAI plus Microsoft claim that this is definitely “Fair Use” – a doctrine in United States law that permits limited utilization of copyrighted material without having to first acquire permission from the copyright holder.  

The problem arises, nevertheless, when not everyone agrees with this reasoning, and a Class-Action lawsuit has already been filed against them.

Sounds familiar? If this does it might be because this is the same argument that will Google used against Oracle’s Lawsuit over the usage of Java APIs in Google’s Android Mobile operating system.  

Google ended up winning the argument in 2021 but you do not would like to be at the wrong end associated with this lawsuit when this particular new court case can be settled.

So does that mean that a person should not really use AI to improve your software program practices? No, there is a lot to gain through artificial software developers!

First of all, it is a great educational tool. If you are looking for examples of implementation of algorithms, comparing technologies or even getting started with a language, talking to an AI can save a lot of research time. The main thing to avoid is copying plus pasting code into your product.  

It can also be very useful to explain code that you don’t understand, or even to write comments and high-level documentation. However, before you feed the code towards the AI, make sure you have the particular copyright owner’s permission, since it can be considered a form of distribution.  

A final word of advice, if you do decide in order to use AI generated program code in your product, make sure you fully understand the code. As I mentioned before, the models are trained using actual code generated by human developers. Code that contains bugs may lead to some nasty surprises with regard to developers that will deploy it when they avoid completely understand this in their manufacturing systems.


The particular views plus opinions expressed are not necessarily those of AltFi.

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