Impacts of AI in the Present and the Near Future

“Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to learn and improve from experience without being explicitly programmed.”

More and more people are entering the field of Machine Learning every day. Hence, it’s a pretty good idea to note the fields where Machine Learning has shown its dominance and has contributed significantly.

AI in Social Media:

It’s a pretty frequently observed phenomenon that Facebook automatically identifies your friend while tagging them in a post. This is done with the help of Facial Recognition technology. Facial recognition requires multiple layers of neural networks, which use machine learning to identify the various features of a face and thus, they predict the identity. A vast number of facial filters on apps like Snapchat and Instagram make use of this as well.

Recommendation systems use ML to give you the best recommendations in terms of “people you may know” or certain advertisements you see or the various posts you may like. All this data is gathered and monitored closely by the systems to give you better recommendations each time.

AI in Chatbots :

Smart Home gadgets like Amazon Alexa or Amazon Echo and Virtual Assistants like Siri and Cortana automate many tasks that can be performed just by our voice commands. Alexa uses signal processing, Wake Word Detection, and other Natural Language Processing (NLP) techniques to process our orders correctly. Siri registers the frequencies and other features in our tone and converts them into a code. Siri then examines the code to identify patterns, phrases, and keywords. This data gets input into an algorithm that is already trained on thousands of sentences to determine what the feature data or the input command means. Once Siri knows what the request is, it begins to assess what tasks need to be carried out, determining whether the required information can be found within the phone’s data or has to be found online. Siri is then able to answer in her voice or show the results relevant to the type of command requested.

Autonomous Vehicles :

Self Driving cars will be the next big thing to hit the road in the coming decades. Companies like Waymo and Tesla are continuously working in this field and have come up with successful trials of self-driving cars. However, it’s still going to take some time for it to get commercial.

Autonomous vehicles rely on sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software. Hard-coded rules, obstacle avoidance algorithms, predictive modelling, and object recognition help the software follow traffic rules and navigate obstacles.

AI in Finance and Banking:

Application of AI in various fields of finance has brought innovative changes like:

• Risk Assessment: Today, we use a credit score to decide who is eligible for a credit card and who isn’t. Data about each individual’s loan repayment habits, the number of loans currently active, the number of existing credit cards, etc. can be used by AI to predict loan and credit offerings.
• Fraud Detection and Management: AI is proving to be almost crucial when it comes to security and fraud identification. It can use past spending behaviours on different transactions to point out odd behaviour. An example of such an action could be, using a card from another country just a few hours after it has been used somewhere else, or an attempt to withdraw a sum of money that is unusual for the account from which it is being taken.
• Financial Advisory Services: Many chatbots have been developed in banks and financial institutions to advise people one-on-one. HDFC bank’s chatbot ‘Ask EVA’ successfully addressed over 2.7 million customer queries over a period of six months. These chatbots are also essential in detecting frauds.
• Trading: ML algorithms are used to predict stock prices by observing patterns in past and from those drawing predictions on how these patterns might repeat in the future. A market crisis can be expected well in advance, and even those who are beginners in trading may receive pretty good advice on when to sell, buy, or hold the stocks.

AI in Agriculture:

Farmers produce tonnes of data on their land daily. AI helps farmers by optimizing planning to generate more bountiful yields by determining crop choices, the best hybrid seed choices, and resource utilization.

CropIn is a Bengaluru-based startup that helps in remote sensing of crops and advises on areas like weather for scheduling and monitoring farm activities for maximum yield, educating farmers on the adoption of acceptable practices, monitoring crop health and harvest estimation, and alerts on pests and diseases.

Autonomous tractors, detection against pests, soils, and crop health monitoring are being done with AI. A deep learning-based application called Plantix can identify the potential defects and nutrient deficiencies in the ground, including plant pests and diseases. It compares new satellite images against past pictures of the same patches of the farm, and AI algorithms detect whether pests invaded their fields so that the farmers use such information to remove them on time.

Precision Farming with Predictive Analytics: AI applications in agriculture have grown into doing precise, controlled farming by providing proper guidance to farmers about the optimum plantation, water management, crop rotation, timely harvesting, nutrient management, and pest attacks.

AI in Healthcare:

Ever wondered how impaired people get when neurological diseases or trauma take away their ability to speak, move, and interact meaningfully with others and the environment. Brain-computer interfaces (BCIs) backed up by artificial intelligence can restore the actual experiences to some extent. You could think of it as a CPR to the brain (or electrifying Frankenstein 😛). Electronic health record (EHR) data can help identify infection patterns of every patient and identify the ones at risk of such health disorders before they actually show symptoms. Leveraging machine learning and AI tools to drive these analytics can enhance their accuracy and create faster, more accurate alerts for healthcare providers. Researchers in the United Kingdom have developed a tool that identifies developmental diseases by analyzing images of a child’s face through a selfie. Not only this, but many ML models have been trained, which could predict a condition based on the part of the body that it affects the most.

Microsoft Imagine Cup, 2019 winner, made an AI model that could predict a person’s blood sugar levels and many other factors and tell if one is suffering from diabetes or not by just looking at their retina’s image.

IBM Watson and DeepMind are doing significant AI-related innovations in healthcare. IBM Watson’s Imaging Patient Synopsis, a Radiologist (who deals with X-rays and medical imaging)- trained AI tool that efficiently informs clinical care decisions by extracting data from the Electronic Health Record of that particular person.

AI in Marketing:

Have you ever wondered how you got engaged in Youtube for countless hours when you went there for just one video or failing to get your eye off the excellent recommendation system of web series and movies by Netflix or Amazon Prime (if you don’t know of Telegram yet 😉)? When you bought something online from Amazon or Flipkart, you must have seen “customers who bought this, also bought this” or more of the exclusive deals related to the purchase you had just made. Well, these are all done with excellent recommendation systems that are AI-powered. Every time you visit these sites or apps, data is generated based on your interaction with them which helps the systems make more customised future predictions.

Nowadays, in malls, one can see virtual face counters where one can see the results of trying different types of facial products without ever applying them on one’s face in reality. Alibaba’s open AI store is equipped with intelligent garment tags that detect when the item is touched and smart mirrors that display clothing information and suggest coordinating items. Alibaba also has plans to integrate the brick-and-mortar store with a virtual wardrobe app that will allow customers to see the outfits they would have otherwise tried on in-store. AI can give you a highly personalized website experience by analyzing hundreds of data points created by features per user.

AI-powered content creation is on the rise like MuseNet, a deep neural network that can generate musical compositions with ten different instruments and combine different music styles. Wordsmith is an AI platform used for natural language generation. It uses lots of data, computation strategy, and rules for right and wrong grammar to produce sentences related to various topics and is used extensively by Yahoo.

So one can see that AI is impacting our lives in every way. Its impact ranges from a simple game suggestion on Playstore for us to chill out up to life-saving road condition prediction while seated in the autonomous car. It’s time to realise that AI is driving us to a more magical future.