Artificial intelligence

The term “artificial intelligence” is a very broad term that doesn’t cover one specific technology or solution. It’s used whenever a machine mimics “cognitive” functions that humans associate with other human minds. A few examples are “learning” and “problem solving”.

AI techniques have become an essential part of technology industry to create intelligent routing, execute military simulations or interpret complex data, including images and videos. But also to build machines which are capable of thinking like humans, but much faster and using massive amounts of data (big data). AI is already more present in daily applications than you might suspect. For example, if you’re using an Android smartphone, AI is used to optimize your battery usage.

With the massive availability of data – from things we share on social media to machine data generated by connected industrial machinery – computers now have a universe of information available to them, helping them to learn to be more efficient and make better decisions.

Application domains of AI

AI technology is key in the digital transformation taking place today. After all it allows us to build more intelligent and complex solutions to automate manual tasks.

Some applications using AI are:

  • Online assistants: Chatbots, Siri, …
  • Content delivery: Publishers now use this technology to distribute content, to post stories more effectively and generate higher volumes of
    traffic on social media
  • Data mining: search engines, image recognition in photographs and video, spam filtering, prediction of judicial decisions, …
  • Finance: The finance industry applies AI for everything from fraud detection to improving customer service by predicting what services customers will need.
  • Autonomous vehicles (drones, self-driving cars) would not be possible without AI.
  • Medical diagnosis, impact of medication, often in combination with IoT and wearables are some of the examples using AI in healthcare.
  • In manufacturing AI helps to manage workforces and production processes; predicting faults before they occur and enabling predictive maintenance.
  • Creating art (such as poetry), proving mathematical theorems, playing games (such as Chess or Go), …