AI is different things to people and invokes different pictures. A human killing terminator style robot for some, and a helpful assistant for others. The present picture is significantly more positive. We like to fall on the second side and through this blog highlight some of the not-so-dangerous things that AI has been able to do, or can do, which is making the world a better place.
We will be discussing how developing AI has impacted various fields like marketing, finance, banking and others in a positive way, with some anecdotes from industry leaders backing our claim.
Artificial Intelligence Applications: Marketing
Marketing is a way to sugar coat your products to attract more customers. Humans are pretty good at this job. Our minds are conditioned to do this. Now machines can be taught to do the same. But what if an algorithm or a bot is created for the purpose of marketing a brand or a company?
The early 2000s was not so great in terms of finding things online. Yes, e-commerce was there, but the search wasn’t that great. It was hard to find anything on a store if you didn’t know the exact name. But now when we search for an item on an e-commerce store, we get all possible results related to the item. What you thought of a minute ago is now being recommended to you by the website. How? Predictions. And AI is good at this. And it is a great way of marketing as well. In a matter of seconds, we get a list of all relevant items. An example of this is finding the right movies on Netflix.
Netflix provides highly accurate predictive technology based on customer’s reactions to films. It analyzes billions of records to suggest films that you might like based on your previous reactions and choices of films. This tech is getting smarter and smarter by the year as the dataset grows. However, the tech’s only drawback is that most small-labelled movies go unnoticed while big-named movies grow and balloon on the platform.
One reason why we’re all obsessed with Netflix, apart from the fun, is that Netflix provides highly accurate predictive technology based on customer’s reactions to films. It examines millions of records to suggest shows and films that you might like based on your previous actions and choices of films. As the data set grows, this technology is getting smarter and smarter every day. What better way to marketing your service by showing us exactly what we love!
With the growing advancement in AI, in the near future, it may be possible for consumers on the web to buy products by snapping a photo of it. Companies like CamFind and their competitors are experimenting this already. Google also has worked on similar ideas in the past and started integrated them into their android os with limited success.
Artificial Intelligence Applications: Banking
Banking is one of the fastest adopters of AI technology in areas like security and customer experience. A lot of banks have already adopted AI-based systems to provide customer support, detect anomalies and credit card frauds. An example of this is the HDFC Bank, which used a chatbot and has some great results. HDFC Bank has developed an AI-based chatbot called EVA (Electronic Virtual Assistant).
We are using machine learning and AI to build intelligent conversational chatbots and voice skills. These AI-driven conversational interfaces are answering questions from frequently asked questions and answers, helping users with concierge services in hotels, and to provide information about products for shopping. Advancements in deep neural network or deep learning are making many of these AI and ML applications possible. – Mitul Tiwari, Passage AI
Eva has addressed over 3 million customer queries, interacted with over half a million unique users, and held over a million conversations. Eva can collect knowledge from thousands of sources and provide simple answers in less than 0.4 seconds.
Our organization has added machine learning-powered billing rules to maximize our credit card processing success rates for recurring billing. By identifying trends in declined credit cards (for example, cards being declined more often on a Sunday evening compared to a Wednesday morning), and fraud patterns that lead to chargebacks, we’ve been able to raise revenue with little human interaction. – Jason Gill, The HOTH
Another use of AI for banking, which is of far higher value for banks, is in fraud detection. It can be hard for humans to understand patterns, but machines are good at it. This is where fraud prevention AI comes into play.
By tracing card usage and endpoint access, security specialists are more effectively preventing fraud. Organizations rely on AI to trace those steps by analyzing the behaviors of transactions.
Companies such as MasterCard and RBS WorldPay have relied on AI and Deep Learning to detect fraudulent transaction patterns and prevent card fraud for years now. This has saved millions of dollars.
Artificial Intelligence Applications: Finance
Finance Companies rely on computers and data scientists to determine future patterns in the market. Trading mainly depends on the ability to predict the future accurately and there is no one better at the job than machines which can crunch a huge amount of data in a short span. Machines can also learn to observe patterns in past data and predict how these patterns might repeat in the future.
In the age of ultra-high-frequency trading, financial organizations are developing AI solutions to improve their stock trading performance and boost profit.
AI is affecting many industries. Accounting and Fin-Tech are no exceptions. After years of working closely with professional accountants, I’m noticing a growing trend — they’re utilizing AI to streamline their professional routines through practices like automated data entry and reporting. And it’s not just accountants, the entire financial services industry is embracing automation. – Nick Chandi, PayPie
Japan’s leading brokerage house, Nomura Securities, is just one such organization. The company has been reluctantly pursuing one goal, i.e. to analyze the insights of experienced stock traders with the help of computers. After years of research, Nomura is set to introduce a new stock trading system.
The new system stores a vast amount of price and trading data in its computer. By tapping into this reservoir of information, it will make assessments, for example, it may determine that current market conditions are similar to the conditions two weeks ago and predict how share prices will be changing a few minutes down the line. This will help to take better trading decisions based on the predicted market prices.
Artificial Intelligence Applications: Agriculture
Did you know that the world will need to produce 50 per cent more food by 2050 because we’re literally eating up everything? We need to use our resources carefully. But how do we decide what to use and how to use it? AI can help farmers get more from the land while using resources more sustainably. Issues such as climate change, population growth and food security concerns have pushed the industry into seeking more innovative approaches to improve crop yield.
The agriculture industry has been using automation and robotics to help farmers find more efficient ways to protect their crops from weeds.
Blue River Technology has developed a robot called See & Spray which uses computer vision technologies like object detection to monitor and precisely spray weedicide on cotton plants. Precision spraying can help prevent herbicide resistance.
Apart from this, Berlin-based agricultural tech start-up called PEAT, has developed an AI application called Plantix that identifies potential defects and nutrient deficiencies in soil through images.
The image recognition app identifies possible defects through images captured by the user’s smartphone camera. Users are then provided with soil restoration techniques, tips and other possible solutions. The company claims that its software can achieve pattern detection with an estimated accuracy of up to 95%! We definitely need to develop AI which can do such wondrous things for our nature and sustainability.
Artificial Intelligence Applications: Health Care
Healthcare sector has been amongst the top adopters of AI technology. It boils down to the power of AI to crunch numbers fast and learn from historical data, which is critical in the industry.
An organization called Cambio Health Care developed a clinical decision support system for stroke prevention that can give the physician a warning when there’s a patient at risk of having a heart stroke.
We are exploring AI/ML technology for health care. It can help doctors with diagnoses and tell when patients are deteriorating so medical intervention can occur sooner before the patient needs hospitalization. It’s a win-win for the healthcare industry, saving costs for both the hospitals and patients. The precision of machine learning can also detect diseases such as cancer sooner, thus saving lives. – Adam Bayaa, Heal
Another such example is Coala life which is a company that has developed an AI-powered digitalized device that can find cardiac diseases.
Similarly, Aifloo is developing a system for keeping track of how people are doing in nursing homes, home care, etc. The best thing about AI in healthcare is that you don’t even need to develop a new medication. Just by using an existing medication in the right way, you can also save lives.