artificial intelligence as any task performed by a machine that would have previously been considered to require human intelligence. That's obviously a fairly broad definition, which is why you will sometimes see arguments over whether something is truly AI or not

1. What is artificial intelligence (AI)?
It depends who you ask.
Back in the 1950s, the fathers of the field, Minsky and McCarthy,
described artificial intelligence as any task performed by a machine
that would have previously been considered to require human
intelligence.
That's obviously a fairly broad definition, which is why you will
sometimes see arguments over whether something is truly AI or
not.
Modern definitions of what it means to create intelligence are more
specific. Francois Chollet, an AI researcher at Google and creator of
the machine-learning software library Keras, has said intelligence is
tied to a system's ability to adapt and improvise in a new
environment, to generalise its knowledge and apply it to unfamiliar
scenarios.
"Intelligence is the efficiency with which you acquire new skills at
tasks you didn't previously prepare for," he said.
"Intelligence is not skill itself; it's not what you can do; it's how well
and how efficiently you can learn new things."
It's a definition under which modern AI-powered systems, such as
virtual assistants, would be characterised as having demonstrated
'narrow AI', the ability to generalise their training when carrying
out a limited set of tasks, such as speech recognition or computer
vision.

2. What are the different types of AI?
At a very high level, artificial intelligence can be split into two
broad types:
Narrow AI
Narrow AI is what we see all around us in computers today --
intelligent systems that have been taught or have learned how to
carry out specific tasks without being explicitly programmed how
to do so.
This type of machine intelligence is evident in the speech and
language recognition of the Siri virtual assistant on the Apple
iPhone, in the vision-recognition systems on self-driving cars, or in
the recommendation engines that suggest products you might like
based on what you bought in the past. Unlike humans, these
systems can only learn or be taught how to do defined tasks, which
is why they are called narrow AI.
General AI
General AI is very different and is the type of adaptable intellect
found in humans, a flexible form of intelligence capable of learning
how to carry out vastly different tasks, anything from haircutting
to building spreadsheets or reasoning about a wide variety of topics
based on its accumulated experience.
This is the sort of AI more commonly seen in movies, the likes of
HAL in 2001 or Skynet in The Terminator, but which doesn't exist

3. today – and AI experts are fiercely divided over how soon it will
become a reality.
What can Narrow AI do?
There are a vast number of emerging applications for narrow AI:
 Interpreting video feeds from drones carrying out visual
inspections of infrastructure such as oil pipelines.
 Organizing personal and business calendars.
 Responding to simple customer-service queries.
 Coordinating with other intelligent systems to carry out tasks
like booking a hotel at a suitable time and location.
 Helping radiologists to spot potential tumors in X-rays.
 Flagging inappropriate content online, detecting wear and
tear in elevators from data gathered by IoT devices.
 Generating a 3D model of the world from satellite imagery...
the list goes on and on.
New applications of these learning systems are emerging all the
time. Graphics card designer Nvidia recently revealed an AI-based
system Maxine, which allows people to make good quality video
calls, almost regardless of the speed of their internet connection.
The system reduces the bandwidth needed for such calls by a factor
of 10 by not transmitting the full video stream over the internet
and instead of animating a small number of static images of the
caller in a manner designed to reproduce the callers facial
expressions and movements in real-time and to be indistinguishable

4. from the video.
However, as much untapped potential as these systems have,
sometimes ambitions for the technology outstrips reality. A case in
point is self-driving cars, which themselves are underpinned by AI-
powered systems such as computer vision. Electric car company
Tesla is lagging some way behind CEO Elon Musk's original timeline
for the car's Autopilot system being upgraded to "full self-driving"
from the system's more limited assisted-driving capabilities,
withthe Full Self-Driving option only recently rolled out to a select
group of expert drivers as part of a beta testing program.
What can General AI do?
A survey conducted among four groups of experts in 2012/13 by
AI researchers Vincent C Müller and philosopher Nick Bostrom
reported a 50% chance that Artificial General Intelligence (AGI)
would be developed between 2040 and 2050, rising to 90% by
2075. The group went even further, predicting that so-called
'superintelligence' – which Bostrom defines as "any intellect that
greatly exceeds the cognitive performance of humans in virtually all
domains of interest" -- was expected some 30 years after the
achievement of AGI.