We are aware of our dependency on AI in complicated processes on which our private data’s security may hinge today. When asked, we all know that such prosaic actions as shopping, booking a holiday, and paying bills online are exceptionally time-saving, but unfortunately, AI is being applied in even more worthless ways. “Technology is everywhere, but only if we want to use it.” – we say. But what if we tell you that AI is controlling your life unnoticeably? Let’s make you aware of THIS fact as well.
It all starts with dialogue. AI can facilitate various interactions between machines and the physical environment, people or other machines. It enables robotic systems to navigate and manipulate the world around them by analyzing amounts of real-time data taken from cameras, sensors, GPS systems, and maps. Computer systems can now respond to our gestures, speech, and facial expressions. Moreover, they can monitor environmental conditions, internal temperature and adjust systems to optimize performance while minimizing energy costs continuously. Sounds like that “Black Mirror” plot we’ve all heard about. But what if we tell you that…
…the service automatically highlights your friends’ faces and suggests who you should tag? It also uses AI facial recognition – strictly Artificial Neural Networks. Facebook personalizes your newsfeed with posts that would interest you by using AI too. This relates to ads as well, because the better targeted they are, the greater the chance that you will click them and buy something. In the first quarter of 2016, Facebook and Google secured a total of 85% of the online ad market.
AI technology is largely powering one of its most important features, which is, of course, the spam filter. It must learn from a variety of signals (message metadata or the words in the message). Simple filters cannot solve this problem as spammers quickly update their spam to work around the short rules. Even the daily emails you consider spam are a welcome sight in our inboxes. Thanks to AI, the Gmail filter successfully blocks even 99.9% of spam.
There is much more than you imagined.
One Llama Labs has developed a smartphone app – Audio Aware – which uses ML for identifying sounds associated with dangerous situations, like squealing tires, via a microphone and warns the user about it. What’s more, users can record and share their own sounds when they detect one.
TensorFlow, Google’s open-source ML software built by a Japanese farmer, can sort cucumbers based on visual differences, as he trained the system to recognize nine different categories. Having a 70% accuracy, it works substantially faster than manual sorting.
Everlaw is a lawyer’s right hand when preparing for trials. The AI reads documents that could be helpful in the case and those which need to be sent to the opposition to avoid a mistrial.
One Concern has developed a system that uses AI to model buildings in a town in order to plug in seismic data in case of an earthquake. Information is based on buildings’ age, materials used in construction and density. Predictions of the most damaged areas can be made in this way.
BioAge Labs helps us to live longer. It uses ML by looking for small molecules in our bloodstream that can predict mortality and be focusing on drug discovery, which might help in extending our lives.
Self-Learning Weather Model and Renewable Energy Forecasting Technology is an ML system by IBM. As the name suggests, it analyzes data from 1600 weather stations, satellites, wind farms and solar stations to predict the availability of renewable energy up to weeks in advance.
The Nest Learning Thermostat can save up to $145 in energy costs per year. It uses AI to learn our schedules and preferences to optimize our home heating and cooling. Nobody’s home? No need to worry, it can automatically reduce the temperature to avoid wasting energy.
Firebird is an ML model formulated by data scientists and the Atlanta Fire Rescue Department for recommending inspection of buildings posing the highest fire risks. It also analyses past data, buildings’ materials and size. Firebird was able to predict fires with up to 71% accuracy.
STAR – Smart Tissue Autonomous Robot is able to administer stitches with a precision surpassing that of human surgeons. It analyzes data from infrared and 3D cameras in real time and generates a plan for optimal stitch arrangement. Moreover, STAR administers them with a robotic arm.
Now you can easily say that AI is totally everywhere. It will be “more” than everywhere over time. Which examples delight you and which are a matter of a concern?