Who could have imagined an Englishman finding his way through South Africa just by speaking English into his Android phone, which translated it to spoken Swahili for the taxi driver?
Who could have predicted machines with abilities to manage and add events to our calendars, help us find information, give directions, suggest our friends, and even quite interestingly, protect children from sex trafficking, and help us buy shoes that fit our feet perfectly!
Bots now trade our stocks. Our cars can drive and park themselves, and we now have autopilot drones. We now live in automated homes and use smart appliances. We don’t overly worry that our mobile phone’s calculator outstrips our arithmetic skills, nor that it can automatically connect to the best network base tower, or autocorrect the spelling in our text messages. Nor are we bothered that our television can automatically tune itself to channels.
These are ways our world is being run by Artificial Intelligence (AI). It has seeped into our lives in all sorts of expected and unexpected ways, thereby, revolutionizing every aspect of our daily life: work, mobility, medicine, economy, and communication, amongst other things.
What is Artificial Intelligence?
Call it Machine Intelligence, you will not be wrong. Artificial Intelligence (AI) centers on creating systems that can function intelligently and independently.
AI is a broad branch of computer science that aims to use software that can analyze its environment using either predetermined rules and search algorithms, or patterns recognizing machine learning models while helping decision making based on the analyses.
These software mimics the way that human natural intelligence (cognition) functions, such as learning and problem solving. AI revolves around the use of algorithms – a set of instructions that computers can execute, and which makes AI capable of learning from data. Computers are learning to think, read, and write. They are also picking up human sensory function, with the capability to see, hear, touch, taste and smell.
How Artificial Intelligence Works
To understand what Artificial Intelligence is and how it works, it would be a great help to do that in respect to humans, the most intelligent creatures on Earth:
Statistical learning is a subfield of AI that deals with speech recognition. Just as humans can speak and listen to communicate languages, machines can read, process, and understand human language from texts through Natural Language Processing (NLP). These statistical tools which are used to explore and analyze data, fall into an even broader subset of AI called Machine Learning.
Humans have the ability to see patterns, such as the grouping of like objects. Machines are even better at it, as they can use more data in more dimensions than humans can, thereby, giving them the ability to make predictions and classifications not even wisest humans can come close to. Deep Learning is the part of Artificial Intelligence that has made the most progress in recognizing patterns and advancing learning. It makes use of Neural Networks. No doubt, AI is adding to human capabilities. So, next time you use Google services to search the web, or use its applications to translate from one language to another or turn speech into text, you have to come to terms with the fact that AI has made you smarter, or perhaps, more effective.
Artificial Intelligence can be symbolic-based (Symbolic Learning). The subfields of computer vision and robotics are found here. Just as humans can see with their eyes, process what they see, and equally understand their environment, AI has developed the ability to use input from sensors, microphones, wireless signals, sonar, radar and so on, to deduce aspects of their environment.
There are many more ways of learning algorithms used for AI. If you train an algorithm with data that also contains the answer, for example, identifying your friends to a computer to make it recognize your friends by name, this is called Supervised learning. Unsupervised learning is when you train an algorithm with data and expect it to come up and figure out the patterns by itself. A machine can learn to achieve a goal in an uncertain, potentially complex environment. This is called Reinforcement learning.
In these ways, AI attempts to mimic biological Intelligence to allow software applications or systems to act with varying extents of autonomy, thereby, minimizing manual human intervention for a huge range of functions.
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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