Artificial intelligence (IA) is a relatively new branch of computer science that focuses on the creation of artificially intelligent machines, humans like in the case of computer software, expert systems and human speech recognition. The field is growing and currently includes many areas of research such as self-driving cars, self-piloted planes, and interactive online games. Recently, artificial intelligence has been used to develop artificial intelligence computers; these are called deep neural networks (DNNs), which are designed to work alongside humans in tasks such as diagnosing disease or making decisions on security.
Artificial intelligence has had a long history; however recent advances have enabled machines to achieve nearly perfect forms of AI. In its most simple form, AI is used to program and control computers, much like how humans trained bees to collect honey rather than kill it themselves. Today, computers can think, reason and adapt to changing situations, much like people do. There are three main areas of artificial intelligence research; computer science, computer engineering and computer science/engineering. Researchers have been working on AIs since the 1970’s. While research continues, AIs are being programmed and developed in many different fields to serve specific purposes.
Computers are increasingly able to handle and process information better than humans, this allows computers and AI systems to perform more complex tasks. As machines are able to deal with more data, the programming language of artificial intelligence is being expanded. Data science refers to the application of scientific knowledge to solve problems; an example is research in databases, statistical methodologies and machine learning. Humans may be involved in some cases; however machine learning requires a great deal more thought and human input than what it does with AIs.
Humans and AIs share a number of similarities; for instance both can use memory, plan ahead and make decisions based on results. However, while AIs may communicate, humans cannot. Humans are visual beings and so can machines. Humans also can provide motivation, which is key to the success of any artificial intelligence. Machine learning uses large amounts of data and if humans are involved it will allow the system to remember things humans have said earlier and possibly learn from those previous conversations. In turn this would allow artificial intelligence to adapt to changing environments like the stock market or political climates.
Task Completion Through AI
While artificial intelligence include AIs that can perform simple tasks such as recognizing images or speech, more advanced versions of these types of robots are able to handle more complicated tasks. This may include things like picking stocks or weather stations in different locations around the world. Robotic systems may also be programmed to make decisions on their own based on patterns seen in data or past events. For instance, a robot could be programmed to recognize a person wearing a particular type of clothing and act accordingly, should that person to show up at another location carrying the same type of clothing. This type of decision making is currently being used by machines to make weather forecasts and even to spot people carrying fake guns. Of course most of these types of decisions are made by humans and the robots are merely acting according to pre-programmed rules and circumstances.
One of the key differences between AI and general intelligence is that while general intelligence is considered to be our capacity for reason and creativity, artificial intelligence is measured by the success or failure of an experiment. Although the results of the experiments are not humanly understandable, the computers behind the scenes have learned from the successes and failures of each experiment. Artificial intelligence is continually improving with every passing day and is rapidly becoming one of the most important developments of our time.
