Who could have imagined an Englishman finding his way through South Africa just by speaking English into his Android phone, which translated it to spoken Swahili for the taxi driver?
Who could have predicted machines with abilities to manage and add events to our calendars, help us find information, give directions, suggest our friends, and even quite interestingly, protect children from sex trafficking, and help us buy shoes that fit our feet perfectly!
Bots now trade our stocks. Our cars can drive and park themselves, and we now have autopilot drones. We now live in automated homes and use smart appliances. We don’t overly worry that our mobile phone’s calculator outstrips our arithmetic skills, nor that it can automatically connect to the best network base tower, or autocorrect the spelling in our text messages. Nor are we bothered that our television can automatically tune itself to channels.
These are ways our world is being run by Artificial Intelligence (AI). It has seeped into our lives in all sorts of expected and unexpected ways, thereby, revolutionizing every aspect of our daily life: work, mobility, medicine, economy, and communication, amongst other things.
What is Artificial Intelligence?
Call it Machine Intelligence, you will not be wrong. Artificial Intelligence (AI) centers on creating systems that can function intelligently and independently.
AI is a broad branch of computer science that aims to use software that can analyze its environment using either predetermined rules and search algorithms, or patterns recognizing machine learning models while helping decision making based on the analyses.
These software mimics the way that human natural intelligence (cognition) functions, such as learning and problem solving. AI revolves around the use of algorithms – a set of instructions that computers can execute, and which makes AI capable of learning from data. Computers are learning to think, read, and write. They are also picking up human sensory function, with the capability to see, hear, touch, taste and smell.
How Artificial Intelligence Works
To understand what Artificial Intelligence is and how it works, it would be a great help to do that in respect to humans, the most intelligent creatures on Earth:
Statistical learning is a subfield of AI that deals with speech recognition. Just as humans can speak and listen to communicate languages, machines can read, process, and understand human language from texts through Natural Language Processing (NLP). These statistical tools which are used to explore and analyze data, fall into an even broader subset of AI called Machine Learning.
Humans have the ability to see patterns, such as the grouping of like objects. Machines are even better at it, as they can use more data in more dimensions than humans can, thereby, giving them the ability to make predictions and classifications not even wisest humans can come close to. Deep Learning is the part of Artificial Intelligence that has made the most progress in recognizing patterns and advancing learning. It makes use of Neural Networks. No doubt, AI is adding to human capabilities. So, next time you use Google services to search the web, or use its applications to translate from one language to another or turn speech into text, you have to come to terms with the fact that AI has made you smarter, or perhaps, more effective.
Artificial Intelligence can be symbolic-based (Symbolic Learning). The subfields of computer vision and robotics are found here. Just as humans can see with their eyes, process what they see, and equally understand their environment, AI has developed the ability to use input from sensors, microphones, wireless signals, sonar, radar and so on, to deduce aspects of their environment.
There are many more ways of learning algorithms used for AI. If you train an algorithm with data that also contains the answer, for example, identifying your friends to a computer to make it recognize your friends by name, this is called Supervised learning. Unsupervised learning is when you train an algorithm with data and expect it to come up and figure out the patterns by itself. A machine can learn to achieve a goal in an uncertain, potentially complex environment. This is called Reinforcement learning.
In these ways, AI attempts to mimic biological Intelligence to allow software applications or systems to act with varying extents of autonomy, thereby, minimizing manual human intervention for a huge range of functions.