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Shooting for the stars, on Linux

Once a year, Boxfusion hosts the annual Graduate Competition, where we invite coders from around the country to submit a homemade solution to a social problem within South Africa. Very often, these yo…
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May 14, 2021

The role of AI in future projects

Artificial Intelligence (AI) and Machine Learning (ML) are two extremely powerful technologies. Interest in the tech has soared in the last two decades decade as computer hardware became more and more powerful, finally able to accurately perform the intricate calculations needed to develop AI and Machine Learning beyond a very basic level.

The cloud played a large part in this as well. As the cloud became a viable commercial technology, huge amounts of processing power was made available to anyone willing and able to pay for it. With this relatively cheap capability readily available, research into AI and ML accelerated dramatically.

Today, the cloud not only powers AI research, but it also provides professional AI services that developers can incorporate into their code. With AI and ML capabilities neatly packaged into easily-used APIs that can be deployed into new solutions quickly and easily, developers can create applications and solutions with truly astonishing capabilities. These leverage AI and ML subroutines to automate complicated tasks and analyse data accurately.

And while you’re not going to see realistic synthetic human androids in the near future, AI and Machine Learning have come far enough that they’re doing some real good in the world.

For example, in the medical field AI and Machine Learning are being used to diagnose illnesses more accurately than human doctors can. As such, AI/ML’s ability to analyse data to determine causal relationships between treatments and outcomes is proving invaluable to the diagnosis and treatment of diseases, as well as in many other aspects of modern medicine.

By feeding Machine Learning algorithms a steady diet of medical data, and those algorithms learning more and more from each byte, it has become possible for machines to pick up the presence of potentially fatal diseases well before symptoms present themselves, allowing for early treatments that save lives. And with such detailed knowledge of those diseases, AI can be used by drug companies to develop more effective treatments.

For example, a company in the US called PathAI is building technology that not only increases the accuracy of breast cancer diagnoses, but can assist doctors in developing highly individualised treatments. This is fantastic because a treatment that works for one patient won’t necessarily work for all, but tailoring treatments to each patient’s individual circumstances has been a challenge up to now. With AI in the mix, it’s no longer impossible.

While medical applications of AI can be seen as some of the more “sexy” solutions, AI is being put to more mundane – but no less useful – uses inside businesses.

Boxfusion recently completed a project with the Gauteng Department of Education that automated the process of registering their children for the 2021 school year.

The solution, called eAdmissions, made use of Azure Cognitive Services – a branch of Azure that lets developers build solutions with AI functions – to automate some functions of the Department’s eAdmissions portal. The portal itself is just a website where parents could upload their documents, but on the back-end, Azure Cognitive Services was verifying the authenticity of all of the documentation submitted.

Once scanned in and uploaded, the eAdmissions solution could detect any fraudulent ID documents, and verify whether forms had been properly filled out or not. This in turn made the registration process an exceptionally smooth one, and dramatically cut down on the number of fraudulent applications. By the Monday after the Friday that the eAdmissions portal opened, over 250,000 applications had been processed.

Another Boxfusion solution, eLeave, also uses AI to automate much of the South African government’s leave application and approval process. The end result is that leave submissions are attended to quickly as opposed to taking weeks, and all of the leave owning and taken is accurately tracked and recorded – all without needing much human intervention at all.

That’s the beauty of AI and Machine Learning, really – it’s a helpful technology that can use its own intelligence and the data it’s fed to make decisions that then help to automate processes.

And that’s really what Boxfusion is all about – automating government processes to make the lives of our officials that much easier, which in turn results in them providing better services to South African citizens. By using AI and ML to do these things, we hope to make the lives of all South Africans better.