What is artificial intelligence (AI)?

Back in the 1950s, the fathers of the field Minsky and McCarthy, described artificial intelligence as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.

That obviously is a fairly broad definition, which is why you will sometimes see arguments over whether something is truly AI or not.

AI systems will typically demonstrate at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity.

What are the uses for AI?

AI is ubiquitous today, used to recommend what you should buy next online, to understand what you say to virtual assistants such as Amazon’s Alexa and Apple’s Siri, to recognise who and what is in a photo, to spot spam, or detect credit card fraud.

Applications of artificial neural systems

  • Learning to read postcodes
  • Stock market prediction
  • Debt risk assessment

Vision systems

The need to interpret, fully understand and make sense of visual input on the computer, i.e. Artificial Intelligence is used to try and interpret and understand an image – industrial, military use, satellite photo interpretation.
Spy plane takes a photograph and experts would then analyse it to try and figure it out – see if it was an enemy area.

Police using the computer to come up with a photo fit drawing of a criminal.

Doctors using the system to make the diagnosis of the patient.

Speech recognition

The ability of the computer to understand a human talking to it. There are many problems associated with this – humans have different accents, slang words, noise in the background, feeling poorly (flu, cold etc). This means that the computer has to be trained to recognize the voice of the human. This means that the human has to ensure that by talking to the computer system before, i.e. train it, the system will be able to recognise their words, sentences, etc.
Honda CRV has the following range of voice commands that the driver can use whilst driving. Using the mobile phone, turning the temperature up or down, turning the air con on or off, asking the car to navigate using the satellite navigation system, turning the radio on or off or up or down. Disabled people can use them to write a memo or use the internet on their computer. The latest phones have a built in program that allows the human to make calls or find out the weather conditions.

Intelligent Robots

A robot can carry out many tasks such as the production of cars in a factory. Robots can weld, insert windscreens, paint, etc. The robot follows a control program to carry out the task given to it by a human. All these robots have sensors. These robots are NOT intelligent, they do the same thing over and over again as instructed by the control program. A sensor is a device which can detect physical data from its surroundings and then this data is input into a computer system. Examples of sensors: light, heat, movement, bump, pressure, temperature, sound.

An intelligent robot has many different sensors, large processors and a large memory in order to show that they have intelligence. The robots will learn from their mistakes and be able to adapt to any new situation that may arise.

An intelligent robot can be programmed with its own expert system, e.g. a factory floor is blocked with fallen boxes. An intelligent robot will remember this and take a different route.

These intelligent robots carry out many different tasks such as automated delivery in a factory, pipe inspection, bomb disposal, exploration of dangerous/unknown environments.

10 Examples of Artificial Intelligence You’re Using in Daily Life

Artificial intelligence (AI) might seem like the realm of science fiction, but you might be surprised to find out that you’re already using it. AI has a huge effect on your life, whether you’re aware of it or not, and its influence is likely to grow in the coming years. Here are 10 examples of artificial intelligence that you’re already using every day.

Virtual Personal Assistants

Siri, Google Now, and Cortana are all intelligent digital personal assistants on various platforms (iOS, Android, and Windows Mobile). In short, they help find useful information when you ask for it using your voice; you can say “Where’s the nearest Chinese restaurant?”, “What’s on my schedule today?”, “Remind me to call Jerry at eight o’clock,” and the assistant will respond by finding information, relaying information from your phone, or sending commands to other apps.

AI is important in these apps, as they collect information on your requests and use that information to better recognize your speech and serve you results that are tailored to your preferences. Microsoft says that Cortana “continually learns about its user” and that it will eventually develop the ability to anticipate users’ needs. Virtual personal assistants process a huge amount of data from a variety of sources to learn about users and be more effective in helping them organize and track their information.

Video Games

One of the instances of AI that most people are probably familiar with, video game AI has been used for a very long time—since the very first video games, in fact. But the complexity and effectiveness of that AI have increased exponentially over the past several decades, resulting in video game characters that learn your behaviours, respond to stimuli, and react in unpredictable ways. 2014’s Middle Earth: Shadow of Mordor is especially notable for the individual personalities given to each non-player character, their memories of past interaction, and their variable objectives.

First-person shooters like Far Cry and Call of Duty also make significant use of AI, with enemies that can analyze their environments to find objects or actions that might be beneficial to their survival; they’ll take cover, investigate sounds, use flanking manoeuvres, and communicate with other AIs to increase their chances of victory. As far as AI goes, video games are somewhat simplistic, but because of the industry’s huge market, a great deal of effort and money are invested every year in perfecting this type of AI.

Smart Cars

You probably haven’t seen someone reading the newspaper while driving to work yet, but self-driving cars are moving closer and closer to reality; Google’s self-driving car project and Tesla’s “autopilot” feature are two examples that have been in the news lately. Earlier this year, the Washington Post reported on an algorithm developed by Google that could potentially let self-driving cars learn to drive in the same way that humans do: through experience.

The AI detailed in this article learned to play simple video games, and Google will be testing that same intelligence in driving games before moving onto the road. The idea is that, eventually, the car will be able to “look” at the road ahead of it and make decisions based on what it sees, helping it learn in the process. While Tesla’s autopilot feature isn’t quite this advanced, it’s already being used on the road, indicating that these technologies are certainly on their way in.

Purchase Prediction

Large retailers like Target and Amazon stand to make a lot of money if they can anticipate your needs. Amazon’s anticipatory shipping project hopes to send you items before you need them, completely obviating the need for a last-minute trip to the online store. While that technology isn’t yet in place, brick-and-mortar retailers are using the same ideas with coupons; when you go to the store, you’re often given a number of coupons that have been selected by a predictive analytics algorithm.

This can be used in a wide variety of ways, whether it’s sending you coupons, offering you discounts, targeting advertisements, or stocking warehouses that are close to your home with products that you’re likely to buy. As you can imagine, this is a rather controversial use of AI, and it makes many people nervous about potential privacy violations from the use of predictive analytics.

Fraud Detection

Have you ever gotten an email or a letter asking you if you made a specific purchase on your credit card? Many banks send these types of communications if they think there’s a chance that fraud may have been committed on your account, and want to make sure that you approve the purchase before sending money over to another company. Artificial intelligence is often the technology deployed to monitor for this type of fraud.In many cases, computers are given a very large sample of fraudulent and non-fraudulent purchases and asked to learn to look for signs that a transaction falls into one category or another. After enough training, the system will be able to spot a fraudulent transaction based on the signs and indications that it learned through the training exercise.

Online Customer Support

Many websites now offer customers the opportunity to chat with a customer support representative while they’re browsing—but not every site actually has a live person on the other end of the line. In many cases, you’re talking to a rudimentary AI. Many of these chat support bots amount to little more than automated responders, but some of them are actually able to extract knowledge from the website and present it to customers when they ask for it.

Perhaps most interestingly, these chat bots need to be adept at understanding natural language, which is a rather difficult proposition; the way in which customers talk and the way in which computers talk is very different, and teaching a machine to translate between the two isn’t easy. But with rapid advances in natural language processing (NLP), these bots are getting better all the time.

News Generation

Did you know that artificial intelligence programs can write news stories? According to Wired, the AP, Fox, and Yahoo! all use AI to write simple stories like financial summaries, sports recaps, and fantasy sports reports. AI isn’t writing in-depth investigative articles, but it has no problem with very simple articles that don’t require a lot of synthesis. Automated Insights, the company behind the Wordsmith software, says that e-commerce, financial services, real estate, and other “data-driven” industries are already benefitting from the app.


Of course, Wordsmith still needs quite a bit of help from an actual author to get set up and give it the matrix article that data is placed into. However, the concept has been proven, and it’s likely that we’ll see more and more reports generated by these means. Moving beyond data-driven fields will require major leaps in technology, but the groundwork has been laid, and it seems like it’s only a matter of time until fully automated reporters become a reality.

Security Surveillance

A single person monitoring a number of video cameras isn’t a very secure system; people get bored easily, and keeping track of multiple monitors can be difficult even in the best of circumstances. Which is why training computers to monitor those cameras makes a great deal of sense. With supervised training exercises, security algorithms can take input from security cameras and determine whether there may be a threat—if it “sees” a warning sign, it will alert human security officers.

Of course, the number of things that these computers can catch is currently pretty limited—Wired talks about seeing flashes of colour that may indicate an intruder or someone loitering around a schoolyard. Identifying actions that might imply a thief in a store are likely beyond the current technological limitations but don’t be surprised if this sort of technology debuts in the near future.

Music and Movie Recommendation Services

While they’re rather simple when compared to other AI systems, apps like Spotify, Pandora, and Netflix accomplish a useful task: recommending music and movies based on the interests you’ve expressed and judgments you’ve made in the past. By monitoring the choices you make and inserting them into a learning algorithm, these apps make recommendations that you’re likely to be interested in.

Much of this functionality is dependent on human-assigned factors. For example, a song might have “driving bass,” “dynamic vocals,” and “guitar riffs” listed as characteristics; if you like that song, you’ll probably like other songs that include the same characteristics. This is the basis of many recommendation services; and while it’s not futuristically advanced, it does do a pretty good job of helping you discover new music and movies.

Smart Home Devices

Many smart home devices now include the ability to learn your behaviour patterns and help you save money by adjusting the settings on your thermostat or other appliances in an effort to increase convenience and save energy. For example, turning your oven on when you leave work instead of waiting to get home is a very convenient ability. A thermostat that knows when you’re home and adjusts the temperature accordingly can help you save money by not heating the house when you’re out.

Lighting is another place where you might see basic artificial intelligence; by setting defaults and preferences, the lights around your house (both inside and outside) might adjust based on where you are and what you’re doing; dimmer for watching TV, brighter for cooking, and somewhere in the middle for eating, for example. The uses of AI in smart homes are limited only by our imagination.