From Netflix To Healthcare: AI In Our Daily Lives
AI is the use of computer science and programming that trains machines to imitate human tasks and thought processes. It works by analyzing data and surroundings to solve problems, incrementally learning for itself to continuously improve. AI functions are initially based or trained using the instructions given to it by humans. We call this “Narrow AI” whereby technology is able to handle just one particular task unlike the creative fantasies movies would have us believe.
Right now, all AI uses some form of human intervention to load the training data, to analyze the results and then, perfect them. AI is not at a point where it has its own conscious decision-making process. It can’t see the world as or better than a human would. However, there are still some amazing applications of narrow AI that influence our daily lives.
AI has become so common in our lives that sometimes we might not even recognize it as AI. Here are a few AI solutions that are already part of today’s AI dominating world.
Alexa and Google Homes have made their customers’ lives easier. Using Natural language processing (NLP), an AI application, generates appropriate responses for users. Vast amounts of data and computing power are used to accomplish this, allowing giants like Amazon and Google to be well ahead of the curve for voice activated devices. Once you ask a question, they track your words based on previous requests from you and other uses, search histories, and, data classification. This means they become more intelligent, learning from interactions on an unsupervised or semi-supervised basis.
Also known as emotional AI, affective computing refers to machines that can recognize, interpret, process and simulate human behavior. Call centers use AI applications that can ascertain the emotional state of the caller through the speed of their speech, intonations and pauses. A combination of this data feeds into an algorithm that presents alternative scripts to staff regarding the best approach for each individual customer. Similar technology is used to interpret body language.
Industry of Internet of Things (IoT)
The key to manufacturing is fast and efficient production of goods. AI in factories use sensors to collect data on the environment and equipment including attributes like temperature and pressure to make this happen. Factories can also record staff productivity and machine status. Concluding in algorithms recommendation of optimal conditions for developing products i.e. X members of staff using Y machine at Z temperature will produce the best yield.
In the healthcare industry, AI has led to one of the most ground-breaking trials: Cancer diagnosis. It does this through analyzing images against a vast amount of past data. This means Image recognition technology has been able to outcompete the human eye in finding early onset of some cancers. This allows clinicians to focus more on patient care and spend less time doing the laborious tasks. Even though ethical issues are holding AI back in this field, it is thought to be a major area of investment in the next decade or so.
Knowing Us Better Than We Know Ourselves
For many of us, a day probably doesn’t go by where we don’t stream something on Netflix, listen to music on Spotify or browse products through Amazon. All these platforms use AI to power their services. In fact, up to 80% of the shows people watch on Netflix are those that the streaming service has recommended to them as opposed to shows they proactively searched for. This form of hyper-personalization has become an expectation. Netflix even goes as far as to display different images to each user based on their likely preferences. This is possible because AI is even able to tell how much a film scares you or how much it makes you laugh. Your recommendations are no accident.
If you have seen the movie Moneyball, you know that data means big business in sports nowadays. Whilst there are arguments that team success is down to how they are coached, motivation and sometimes pure luck, data does have a role to play. Teams can analyze data in real-time during matches and predict what is most likely to happen next. This has even been successfully used in the NBA as a method to counteract certain plays.
Believe it or not, AI is able to play a melody and even write lyrics. Google has an interactive experiment that virtually plays the piano with you as a duet. As you play, it picks up the melody and responds alongside you. Maybe even more impressively, DopeLearning suggests and creates its own rap lyrics based on a set of rules you provide. Super fun, even for a Metal-head like me!
As well as music, deep learning algorithms have started to help design new pieces of art through analyzing the work of the most renowned artists. IBM’s Watson platform can deliver suggestions and inspiration to humans as they work and even to avoid writers/artists block. Similar technology is used in the culinary world where AI can recommend which ingredients might complement each other and can come up with new recipes for chefs. This may even lead to Michelin star restaurants with fully AI generated menus in the future.
This article could go on and on with great examples of AI in the world as it stands today. However, the takeaway here is that as everything becomes more digital and collaborative, the scope for machines to learn increases exponentially. AI thrives on data and with so much of it being generated in the last few years, we are seeing the start of the technological revolution. We are some way off a machine/human singularity and there are questions around whether we would even want that. The fact is AI is changing the world and has endless scope for future creations which will see us adapt and amend how we do things today.
The future of AI is bright and I am proud and extremely excited to be a part of one of the strongest AI teams globally, at Crayon.