If you've used Google Maps, you've experienced artificial intelligence ( AI) firsthand. It's a prime example of how AI technology today enables computers to take on tasks formerly reserved solely for humans -- such as reading a map. In this case, Google uses historical and real-time data to visualize current traffic patterns and then applies AI to predict future traffic flow, with the objective to plot the quickest route to a destination. Three important trends have made recent advancements in AI possible: big data collection, reduced computing costs, and improvements in algorithms. Data these days are easy to collect and cheap to store, while the advent of cloud computing has made it much more affordable to crunch all that data.
This is what Latent semantic analysis (LSA) does. It is based on how frequently you see the word on the exact topic. Like, there are more tech terms in tech articles, for sure. The names of politicians are mostly found in political news, etc. Yes, we can just make clusters from all the words at the articles, but we will lose all the important connections (for example the same meaning of battery and accumulator in different documents). LSA will handle it properly, that's why its called "latent semantic".
They diagnose illnesses, help you find photos of your cat, decide whether to give you a loan1. They make up a huge part of what we call "machine learning" or "artificial intelligence," especially the new, exciting, scary parts of it. And, given the magnitude of the problems they can handle, they're simpler than you'd expect.
At DKdL (Die Krieger des Lichts, part of the fischerAppelt group) we have decided to take a novel and holistic approach to developing intelligent data-driven concepts and products. We call this approach "human centered AI", where AI stands for artificial intelligence. Our approach integrates the research & development (R&D) needed to develop AI systems into a human centered design process. In simple words, we understand that the intelligent products (that is, products that use AI at their core) we develop are designed to be used by humans in a way that adds value to their daily experiences. Therefore, we start by understanding the people who are going to use the product and the needs it is intended to meet. We then keep those needs at the focus of our considerations throughout the entire development process and the design iterations.
And it's only going to become more sophisticated. Auto makers are conceiving self-driving vehicles to ferry people to their destinations, then park or carry other passengers until pickup time. Lights and thermostats can connect to your smartphone's location sensors, so your home can go to sleep when you depart and wake up when you return. Factory robots are sorting goods into customer orders that might be carried to your doorstep by autonomous quadcopters. AI isn't the next big thing--it's here now, and it shows no sign of letting up.