What Is Artificial Intelligence AI?

Alan Turing, the mathematician famous for helping the Allied Forces win World War II by breaking the Nazi encryption machine Enigma raised a powerful question that forever changed the course of history; “Can machines really think?” In a way, Turin set the foundation for what we call “Artificial Intelligence”. AI is the simulation of human intelligence processes by computer systems. Artificial intelligence is what enables machines to perform human-like tasks, mimic human cognitive skills, adjust to new inputs, and learn from experiences to solve challenges in unexpected ways.  AI is ubiquitous today, be it to detect credit card fraud, identify people in a photograph, virtual assistants like Apple’s Siri and Amazon’s Alexa, automatic language translation, getting recommendation on what to buy online based on previous purchase history, to chess-playing computers, grocery ordering refrigerators, and self-driving cars!

Why Does AI Matter?

AI improves our daily lives by allowing a computer to make certain processes more efficient and perform fairly complicated tasks automatically. AI takes the human capabilities of knowledge, reasoning, forecasting, communication and perception at scale to create new opportunities in consumer applications. For instance, AI automates repetitive learning and discovery but instead of simply automating manual tasks, artificial intelligence has the capacity to perform high-volume tasks at trailblazing speed and infallible accuracy. Not to mention, AI also incorporates the element of intelligence in your existing products. AI isn’t marketed as some stand-alone application or program; rather, AI capabilities are capitalized on to improve your existing products. For instance, Siri was added to new generation of Apple products to offer a personalized assistant to users. Similarly, many technologies like investment analysis and security intelligence can be improved by combining bots, conversational platforms, and automation to voluminous data. Instead of being programmed what to think, AI adapts through progressive learning algorithms, where machines can observe, analyze and let the data do the programming. AI can find patterns, structures and regularities in data and teach itself to preserve the context in translation, detect which transactions are likely to be fraudulent, play chess, identify facial features, or even to learn the purchasing behavior of consumers and show them products they may like. The more data it acquires, the better the algorithm adapts. This technology has led to major breakthroughs in healthcare, retail, Ecommerce, and even manufacturing and travel. AI relies on deep neural networks to achieve amazing accuracy. For instance, deep learning systems can deliver scalable, automated diagnosis that was hitherto impossible. Similarly, computer vision solutions are changing the face of diagnostic imaging since deep learning systems can be trained to identify abnormalities in magnetic resonance images and ultrasounds in mere seconds, with human-level accuracy. Similarly, do you notice how your interaction with Alexa, Siri, and Google Search keeps getting more personalized and customized the more you use them? You only get the most out of voluminous data when algorithms are self-learning. When presented with such overwhelming amount of data, humans may not be able to fish the answer out that lies buried within, but you just need AI to find the answer for you. Since data has become somewhat of an intellectual property in every process these days, you need the best techniques to make that data relevant and find meaning within.

What are the different types of AI?

Artificial intelligence encompasses two broad categories: Narrow AI Also known as "Weak AI," this kind of AI is what we see today in computer systems all around us; seemingly intelligent systems that have been taught or trained to perform specific tasks to perfection, but operate within a restricted set of rules and limitations as compared to human intelligence. This type of machine intelligence can better be understood by looking at the vision-recognition systems on self-driving cars, Google search, Customer service bots that redirect inquiries on a webpage, Spam filters that keep your inbox clean, or speech and language recognition capabilities of Siri. Artificial General Intelligence (AGI) Thing of ‘Jarvis” in Iron Man to better understand the concept of AGI. Unlike narrow AI, Artificial general intelligence allows a machine to apply knowledge and skills in different contexts, much like a simulation of the human mind. Think of AGI as a machine possessing a general experiential understanding of its environments and cognitive abilities mimicking humans, combined with an exponentially superior knowledge, cognitive ability, and processing speed than humans to cope with any generalized task which is asked of it. Think of smart assistants like Alexa and Siri, social media monitoring tools keeping an eye out for fake news, manufacturing robots, customer service chat bots, COVID mapping and forecasting tools, movie recommendation from Netflix, or even disease diagnosis and treatment recommendation.

How Does AI Work?

You may have often been bombarded with buzzwords such as “predictive analysis”, “deep learning”, “the internet of things”, and so forth. In reality, these are the cutting-edge technologies behind computer systems, helping machines make sense of data and make decisions, learn from experiences and mistakes, understand human concepts, identify patterns and anomalies, and so on. If we are to explore the real-world possibilities of AI, it is important that we must first get to grips with these revolutionary technologies that are revolutionizing the way humans interact with machines. Machine Learning We often describe intelligent systems as machines that can perform certain tasks without being explicitly programmed. This particular application of AI enables computer systems to automatically learn and improve from experience, observe and analyze data, and make forecasts and decisions accordingly. Machine learning is how Spotify predicts which songs you may like or the Uber app finds the fastest route to your destination. ML is also revolutionizing the field of medical image interpretation, improving disease diagnostics, and accelerating drug development. Deep Learning Deep learning leverages artificial neural networks, brain-inspired networks of interconnected layers of algorithms that mimic the biological neural networks in the human brain and learn by processing data. These multi-tiered neural networks work across many layers to determine a single output from a large number of inputs. Since the deep learning algorithm learns from experience, it performs a task repeatedly, each time tweaking it a little to learn through positive and negative reinforcement. Whether it’s Alexa or Siri, the virtual assistants leverage deep learning to help understand your speech and respond accordingly. Deep learning is how chatbots and service bots are able to respond in an intelligent way to all auditory and text questions or how Facebook automatically tags people on their photos. Neural Network A biologically-inspired programming paradigm, neural networks are the drivers behind deep learning. In order to draw parallels with the human brain, think of the perceptron as the artificial equivalent of a human neuron. When combined together, these perceptrons give birth to artificial neural networks in machines.  Neural networks are how a computer learns to perform some task by analyzing training examples, usually in the form of data sets. For instance, an object recognition system is fed literally millions of images of everyday objects before it learns to find associations and visual patterns in the images, and identify the object correctly. Cognitive Computing Cognitive computing aims to improve human-machine interaction by recreating the human thought processes in complex situations where the answers may be ambiguous; for instance, to better understand the context of speech or the meaning of images. Cognitive computing works by synthesizing data from various information sources to suggest the best possible answers, using a blend of technologies such as machine learning, natural language processing, neural networks, AI, and contextual awareness. Cognitive computing serves as an assistant, not only being able to study patterns and behaviors, but also proposing suitable actions.  For instance, a machine can study patient history, journal articles, diagnostic tools, and other data to provide a suitable treatment. Natural Language Processing NLP helps computers understand, interpret and manipulate human speech and language. The role of NLP is to empower machines to understand human language in context so as to offer a seamless interaction with the machines we use. Human language is often ambiguous and the linguistic structure ridden with complex variables, such as social context, regional dialects, and even slang. NLP helps chat bots and customer service bots produce logical responses. Think of Skype Translator, which interprets the speech of multiple languages in real-time or even how when you say something along the lines of “Alexa, I like this song”, Alexa plays it for you. Computer Vision This field of AI deals with how computers can gain high-level understanding from digital images or videos. Leveraging techniques like pattern identification and deep learning, computer vision is able to “see” and understand the content of an image, even text, charts, tables, and graphics within PDF documents and  videos. In addition to the above mentioned technologies, several others support AI. For instance, AI can’t function without Graphical processing units, since they are the source of computing power that is needed for iterative processing by training neural networks. Similarly, training neural networks require vast amount of data, which is generated by the Internet of things using a horde of connected devices. AI allows us to tap into that vast ocean of data and make sense of it. Also, we need advanced and innovative algorithms to analyze data faster and with a higher precision. This intelligent processing allows AI machines to optimize unique scenarios, predict and identify events, and comprehend ambiguous systems. Last but not the least, Application processing interfaces helps us add AI capability to existing products. For instance, we can add mask detection capabilities in building security systems or automated response systems in helplines. In a nutshell, all these technologies result in a software that can provide human-like interactions with software.

Applications of AI

There isn’t a single industry that AI hasn’t touched yet. With companies spending nearly $20 billion collective dollars on AI products and services, expect to see big changes in the way everything is done now. Below are some of the most popular examples of artificial intelligence that's being used today. Personal Assistants AI-powered personal assistants like Apple HomePod, Google Home, and Amazon Echo are capable of performing of basic tasks at the moment, but they continue to learn from daily interactions and will probably get smarter over the years and better able to predict our natural-language questions and requests.  We all know Siri, the pseudo-intelligent, friendly voice-activated computer that helps us add items to our grocery lists, looks up information on the web, reminds us to take our medicine, gives us directions, sends messages and emails on our behalf, and so on. Similarly, Amazon Alexa’s astounding ability to decipher speech from anywhere in the room, has left us in awe. Not only is Alexa an amazing personal assistant like Siri, it can also power our smart homes and help people with limited mobility get things done. Market Research There are tons of AI-based applications like IBM’s Watson, that are capable of performing comprehensive research for businesses, as well as performing competitor comparisons and generating detailed reports. Expect to see more and more companies use these tools to provide surprisingly accurate predictions about the performance of new products or services. Autonomous Vehicles Self-driving cars need AI to make sense of the world around them and the ability to choose specific actions based on information gathered. Gathering data and information using LIDAR  long range radar, and cameras, AI algorithms helps direct autonomous vehicles to nearest gas stations, adjust routes based on traffic conditions, incorporate speech recognition to offer seamless interaction with passengers, and so on. If you are a tech junkie, you must have seen the out-of-the-box predictive capabilities of Tesla’s self-driving cars. Healthcare This is one industry where AI is promising to make great breakthroughs. Robot-assisted surgery will greatly help doctors in operations while virtual nursing assistants will make it easier to garner diagnosis. Not to mention, AI-powered computer vision is already improving X-ray results. For instance, the Chinese startup Infervision is using image recognition technologies and machine learning to diagnose possible signs of lung cancer with X-rays. Similarly, the Redivus Health app offers clinical decision support during critical medical events to prevent medical errors. Customer service Customer service has never been faster and better, thanks to a horde of automated AI-powered chat bots that can quickly and efficiently respond to the customers’ main worries and issues. Look at the AliMe chat bot by Alibaba, which relies upon a wide array of technologies such as semantic understanding, personalized recommendations, and voice recognition. Similarly, Cogito was invented to improve the emotional intelligence of customer support representatives by relying on behavioral science and machine learning. For brands like Sephora and H&M, advanced chat bots serve as sales consultants and, help users find what they are looking for. Sephora customers can virtually try on different cosmetics by sharing a picture of themselves with the AI bot. The bot identifies different facial features and uses augmented reality to apply these makeup tests. Email Marketing A lot of email service providers are incorporating AI capabilities in their products. For instance, AI can help improve the effectiveness of email marketing campaigns by deciphering which headlines generate the most open rates, which keywords yield the highest traffic, or what is considered the ideal length or format of emails for engagements. One such AI tool, Boomerang Respondable, is able to proof your emails and offers suggestions on what can be done to improve them. Finance The financial sector relies on computers and data scientists to determine future patterns in the market and make forecasts accurately. Via their ability to analyze huge amounts of data in a short span, AI machines can observe patterns in past data and predict how these patterns might repeat in the future. Not to mention, since success of activities like trading mainly depend on the ability to make accurate predictions, financial organizations are leveraging advancements in AI to improve their stock trading performance and boost profit. Agriculture Issues such as climate change, an unprecedented population growth, and food security concerns have highlighted the need of advancements in technology improve crop yield. Companies are turning to AI to protect their crops from weeds. For instance, an AI powered precision spraying machine called See & Spray uses object detection to monitor and precisely spray weedicide on cotton plants to prevent herbicide resistance.

What are the Latest uses of artificial intelligence in UAE?

It won’t be an exaggeration to say that UAE is leading the way with artificial intelligence (AI), with advancement and futuristic development. The country's Ministry of Artificial Intelligence aims to position the country as a global artificial intelligence (AI) hub, with an objective to implement advancements in AI in nine sectors including traffic, environment, education, technology, water, renewable energy, space, health, and transport. In its efforts to incorporate AI technologies in both its healthcare and education sectors, UAE collaborated with the local technology company, Alef Education, to integrate its digital education platforms into several schools located in Abu Dhabi and Al Ain. Similarly, if we talk about the future of AI in healthcare industry, AI and robotics are already being used to largely automate surgeries and other procedures. Ministry of Health and Prevention launched the Medopad app that tracks the daily activities of patients, monitor their vital signs remotely, and analyze, document, and review their data and information to help healthcare professionals detect life-threatening medical conditions and offer remote care.  It also offers informative content to patients suffering from multiple diseases, such as Parkinson’s, kidney and heart diseases, cancer, COPD, and multiple sclerosis.