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Ways AI is transforming the Aerospace and Defense system

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The aerospace and defense industry requires supporting software that can initiate quick decisions in high-risk scenarios. These sectors are under constant pressure to maximize profitability and improve operational efficiency. There is every need to continuously adapt to business disruptions. It is necessary that aerospace and defense sectors optimize revenue gains and increase efficiencies by building intelligent processes. AI has an increasingly central role to play in achieving these processes. In this article, we will take a look at ways AI is currently transforming the aerospace and defense system.

Aircraft smart maintenance

Aircraft maintenance is one of the most important tasks in aerospace and defense systems, but this process can be slow and time consuming, as it is done on a scheduled basis. Lack of maintenance can lead to failures or unexpected errors which can result to dowtime and inefficiency. AI powered predictive maintenance can drive efficiency in aerospace and defense systems in terms of maintenance of aircraft and other devices. AI can easily extract information from sensors and reports through maintenance data gathering and interpretations. AI enables early detection and report of failures which helps to predict accurate timelines for appropriate repairs.

Improved Training and Optimizing of Flight Path

AI can be used to give pilots more realistic training experience through AI simulators integrated with virtual reality systems. AI powered simulators can be used to create personalized training patterns based on each trainee’s results by collecting and analyzing training data which include biometric data. AI powered systems within the cockpit can also assist pilots by optimizing real time flight path through assessing and notification of fuel level, system status, weather conditions and other parameters. Pilot’s efficiency can be improved by extending virtual fields when an aircraft is equipped with smart cameras operated by AI algorithms.

Increased Fuel Efficiency

A considerable impact on emissions can be experienced from any little improvement in an aircraft’s fuel consumption. Increased fuel efficiency is one of the main targets of aerospace industries and AI powered systems can make this possible. There is a machine learning tool from AI providers that is capable of optimizing climbing profiles prior to each flight. Aircrafts consume more fuel during the climbing phase, so, optimizing this phase can lead to considerable fuel saving.

Intelligence, Surveillance, and Reconnaissance

Because of the large data sets available for analysis, AI can essentially be useful in intelligence. For example, Project Maven plans to incorporate computer vision and machine learning algorithms into intelligence collection cells that would comb through footage from uninhabited aerial vehicles and automatically identify hostile activity for targeting. Here, the job of  human analysts that spend hours 

Perusing drone footage for actionable information, will be automated by AI, thereby giving analysts more space to make more efficient and timely decisions based on the data.

Cyberspace Operations

AI has the potential of serving as a  key technology in advancing military cyber operations. According to Cyber Command Admiral, Michael Rogers, in his 2016 testimony before the Senate Armed Services Committee, “relying on human intelligence alone in cyberspace is “a losing strategy”. 

“If you can’t get some level of AI or machine learning with the volume of activity you’re trying to understand when you’re defending networks… you are always behind the power curve.”

Common cybersecurity tools look for historical matches to ascertain malicious code. This is not an effective security measure because hackers only have to modify small portions of that code to circumvent the defense. On the other hand, AI-enabled tools, can be trained to detect anomalies in broader patterns of network activity, thus, presenting a more comprehensive and dynamic barrier to attack.

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Artificial Intelligence

How AI Is Helping Fintechs Provide Intelligent And Better Financial Services

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AI fintech 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.

Risk Assessment

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. 

Churn Prediction

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.

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Artificial Intelligence

This New AI Can Tell The Kind Of Faces You Find Attractive

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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.

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Artificial Intelligence

Using AI To Grow Avocados And Improve Agricultural Productivity In South Africa

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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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