In 2014, young Nabuuma Shamim Kaliisa from Uganda, was diagnosed with breast cancer. Prior to her diagnosis, she had watched her mother battle with cervical cancer, which eventually claimed her life. Following her struggle with cancer and the loss of her mother to cancer, Nabuuma was driven to create a company that could help people survive their battle with cancer. The company would turn out to become Chil AI Lab, in Uganda. According to Nabuuma, her vision is to create a world where “nobody dies of any reproductive health related cancer caused by late detection and treatment.”
Her company, Chil AI Lab, is an Artificial Intelligence company that facilitates access to affordable and easy-to-use E-oncology services for women across the globe. The company’s flagship product is an AI-powered mobile application named Keti, which utilizes artificial intelligence to diagnose cervical and breast cancer. Through the mobile app, women can access consultation services, follow-up and other add-on reproductive health services. The company has also created self-testing kits that are powered by machine learning, which make it easier for their services to reach the underserved. Through Chil AI Lab, Nabuuma has helped over 100,000 women diagnose cancer at an early phase and, via partnerships, helped them access quality treatment.
Like Nabuuma, a lot of young innovative Africans are also leveraging artificial intelligence to solve global and local healthcare challenges. With Ubenwa, Charles Onu, like Nabuuma, is using AI to transform the healthcare system in Africa and the world at large.
Ubenwa is one amid many other disruptive AI-powered startups in Africa. Through their machine-learning-powered mobile app, the Nigerian-based startup is on the path to saving the lives of as many newborns as possible from losing their lives to perinatal asphyxia, which annually claims the lives of millions of newborns. According to the UN, if newborns who have asphyxia can be detected early enough, we may be able to save their lives.
The mobile app is a screening tool that takes the sound of infant cry as input, analyzes the acoustic parameters of the sound, and then, using machine learning, compares it against a database of infant cries that have been clinically labelled. The output is then used to predict the risk of perinatal asphyxia within a short time frame. Just like magic, with just the cry of a baby, Ubenwa’s mobile app is capable of detecting birth asphyxia, thereby, helping in the prevention of the death of these babies. The company is also working on an automated cry analysis tool that can help parents understand their babies. Through the automated cry analysis, basic needs, like hunger, sleep and pain, can be extracted from infant cry and translated to parents so that appropriate care can be given.
Situated in Southern Africa, fast-rising AI-powered startup, Envisionit Deep AI, is also making giant strides in the integration of artificial intelligence in healthcare services. The South African startup is leveraging the use of machine learning, in conjunction with the expertise of radiologists, to improve and enhance easy access to radiology services in Africa.
The company has developed a flagship product known as RADIFY. RADIFY is an AI-powered tool that can detect up to 20 different pathologies on x-rays, at a rate of up to 2000 x-rays within a minute. The tool is capable of taking up radiology tasks, to fill in the gap of the deficit of radiology experts in Africa, with the capability of analyzing and interpreting radiology scans just like a human expert. This tool supplements the efforts of doctors within the region, and does not eliminate the need for doctors.
The tool is very easy to use. Once a doctor uploads a batch of images from scans, the images get analyzed by an AI algorithm which then identifies possible issues and pathologies, and prioritizes the images and cases that are most relevant. All the identified features are clearly highlighted and labelled on the images. This makes the process of diagnosis, via radiology, much efficient.
In response to the COVID-19 pandemic, the company offered RADIFY to the public at no cost, to be used in the diagnosis and treatment of the COVID-19 pneumonia.
The fascinating ways in which Africans are using artificial intelligence to build solutions to challenges within a critical sector, like the healthcare sector, is indeed profound. With the cultivation of a mindset that is shifted from a consumption-based orientation to a creation-based one, the world is beginning to witness more and more Africans leveraging the use of artificial intelligence to create global healthcare solutions that are saving the lives of millions of people around the world.
How AI Is Helping Fintechs Provide Intelligent And Better Financial Services
We live in an era of data. In today’s world, data is the new gold. The quality of services now significantly depends on how much insight can be extracted from data to help in the creation of the services. For fintech organizations, building services that harness the power of data and artificial intelligence has now become necessary to ensure that the services are tailored to meet the needs of customers. Artificial intelligence is now being used in various ways to help fintech companies provide intelligent and improved services. Some of the major areas of AI application in fintech are discussed in this article.
From insurance companies to banks and other fintech institutions, assessing credit worthiness and estimating the level of risk associated with every transaction has become very crucial. Now, many fintech companies employ the use of AI in determining the credit profiles of clients which helps to minimize financial losses when customers fail to repay loans or meet other financial commitments.
Predicting and preventing fraudulent transactions is another challenge that fintechs are using AI to solve. Using machine learning algorithms, fintech organizations are able to build more accurate fraud detection mechanisms to curb the activities of scammers. The advantage of using machine learning for fraud detection in financial systems is that the machine learning model can learn from the financial data by itself. Thus, it is able to uncover hidden patterns and make a more robust prediction compared to traditional fraud detection algorithms. AI-based fraud detection algorithms can also be used to verify insurance claims and flag fraudulent ones.
Customer churn is an important Key Performance Index (KPI) for any organisation. Preventing customer churn is aimpoaaaustomers and improve customer engagement. Many fintechs across the world now use AI to increase customer retention by understanding customer behaviour and making data-driven decisions to retain the audience of customers.
Intelligent Customer Service
Customer service is an aspect of fintech that has been significantly transformed by AI. The use of AI in this area has drastically reduced the need for human customer care representatives and the cost associated with employing these representatives. With AI, more customers can be attended to more efficiently via chatbots, virtual assistants etc.
Chatbots are, particularly, one of the most common uses of AI in fintech customer service. Chatbots are sophisticated conversational AI applications that can engage with customers, address complaints and basically fill in the gap of a human employee. Chatbots have now become faster and easier means for customers to fix issues they have while using fintech services.
The Future of Fintech With AI
The use of AI in financial technology extends beyond risk assessment, churn prediction and intelligent customer service. Areas like payment processing and sentiment analysis are also being transformed by AI. Organizations like MasterCard and Visa have been able to improve the quality of their services by leveraging AI to achieve this. Personalized banking and financial services will define the future of financial technology. Better experiences will be developed for each customer in a unique and personalized manner. This may be impossible without AI. The future of fintech is geared towards smarter and more intelligent services, with AI steering the wheel to this future.
This New AI Can Tell The Kind Of Faces You Find Attractive
AI researchers are constantly coming up with ways to make the technology serve us better. However, while these services are impressive they can be a tad creepy. A time when social media will be able to like pictures on our behalf, based on how our brain reacts to the picture sounds quite uncomfortable.
Although Instagram isn’t working on an algorithm that tracks brain waves, researchers from the University of Helsinki and Copenhagen University are. This AI matchmaker can tell when you find someone attractive. It creates a database of this information and knows the kind of faces you find attractive or in more lucid terms, “your type”
Here’s how it works
According to Digital Trends, the researchers used a generative adversarial neural network. This network has over 200,000 pictures of celebrities. The AI then recreates original faces based on that database. A group of participants kitted with electroencephalography (EEG) caps were shown these images. Concentrating on which picture they found attractive, the cap read their brain waves to know how they felt about the picture.
Michiel Spapé, one of the researchers, said, “By capturing the brain waves that occurred just after seeing a face, we estimated whether a face was seen as attractive or not. This information was then used to drive a search within the neural network model — a 512-dimensional ‘face-space’ — and triangulate a point that would match an individual participant’s point of attractivity.”
The AI uses machine learning to connect the dots as per what we are attracted to. Whatever pictures cause a spike in brain waves is stored, the machine analyzes them and looks for the faintest detail they have in common. Afterwards, it comes up with facial features we might not know we are attracted to.
So, how do you measure attraction?
The researchers have found out that roughly 300 milliseconds after a participant sees an attractive image, the brain lights up. Well, a living brain lights up every time but this particular “lighting up” gives off a specific signal identified as a P300 wave. A P300 wave in itself, does not mean you’re attracted to something. It simply means you have spotted what you have been asked to look out for. The participants have been asked to look out for images they find attractive, as such, any discovery of a P300 wave at that time, means that they find the picture attractive.
Great algorithm for dating apps?
An algorithm that can tell which facial features you find attractive will be great for dating apps. It will recommend to users, the kind of faces they will probably find attractive.
However, one can argue that the laws of attraction aren’t that simple. Facial features are just a facet of what people find attractive. Nevertheless, there could be an integration of the detection of all the possible attraction facets. This would go a long way in cementing AI’s position as a major partaker in human lives- or love lives, as the case may be.
Using AI To Grow Avocados And Improve Agricultural Productivity In South Africa
Globally, South Africa maintains a spot as one of the major producers of avocado. In 2019, the nation secured approximately 1.1% international market share in the multi-billion dollar avocado export market. However, its annual production volume of between 80,000 and 120,000 tonnes is still many miles behind the annual production volume of 1.5 million tonnes by top avocado producer, Mexico. However, this figure could be significantly increased with precision agriculture, thereby, providing ample opportunity to boost the nation’s overall revenue from avocado export.
The right amount of irrigation is extremely critical for South African avocados to attain maximum growth. For a long time now, South African farmers have relied on traditional irrigation strategies that are largely hinged on their intuition and experience, which has hindered the attainment of the maximum productivity that could be reached in avocado production. Cracking the issue of irrigation could unlock an astonishing increase in South Africa’s annual avocado production volume.
Now, Israeli company, SupPlant, is using technology, particularly AI, to provide farmers with smarter and more efficient ways to improve agricultural productivity. They have been able to achieve this by developing an AI model that employs predictive algorithms to provide customized irrigation recommendations based on analyzing about 100 million data points. Their solution is now being used by South African farmers to grow avocados as the solution is particularly useful for South Africa’s avocado irrigation challenge.
To gather data, SupPlant’s solution involves the use of sensors. These sensors are located in 5 different parts of the plant (avocado, deep soil, shallow soil, leaf, stem/trunk). The sensors monitor plant stress, the exact water content in the soil, health data of the plant, the growth patterns of the plant and the fruit. Climatic data and data on the growth patterns of the plant are also monitored by the sensors. The combination of the data is uploaded to a cloud-based algorithm, at 30-minute intervals, which then makes predictions based on the input data from the sensors to provide farmers with irrigation recommendations.
However, the solution above does not solve all of the challenges that South African farmers face in avocado production. Another critical challenge for the farmers is associated with the weather. To overcome this hurdle for South African farmers, SupPlant integrates the use of top weather intelligence platform, ClimaCell, to monitor the weather in a particular plot of land. Today, with the use of SupPlant’s mobile app, South African farmers can monitor their farm plots and control irrigation on any plot from anywhere. The mobile app provides graphical information on historical and future irrigation plans, present and forecasted climatic data customized for each farm plot, growth patterns of the avocado plant, agronomic insights and recommendations for irrigation.
If, for instance, plant stress begins to increase, farmers will immediately get altered via the mobile app and receive data-driven amplified irrigation recommendations to prevent severe damages to the plant. With SupPlant’s solution in the hands of farmers, farmers will no longer need to engage intuitive and traditional irrigation and farming approaches.
In such a time as now, when the demand to produce more in smarter and more efficient ways is seemingly high, SupPlant’s solution evidently lies beyond South Africa’s avocado industry, as it also extends to other areas where precision agriculture could be harnessed to unlock massive agricultural productivity. With a technology like AI, the journey to smarter and more intelligent farming is just evolving.
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