The third age of computing - The Computing Universe: A Journey through a Revolution - page 324

How will we be able to cope with the immense complexity of this new
world? The computer entrepreneur Ray Ozzie has painted a vision of what he
calls “a world of continuous services and connected devices”: 6
To cope with the inherent complexity of a world of devices, a world of
websites, and a world of apps and personal data that is spread across myriad
devices and websites, a simple conceptual model is taking shape that brings it
all together. We're moving toward a world of 1) cloud-based continuous services
that connect us and do our bidding, and 2) appliance-like connected devices
enabling us to interact with those cloud-based services. 7
Cloud computing is a way of sharing computing resources by linking large num-
bers of computers and other devices over the Internet with massive data cen-
ters where huge amounts of information can be stored together with massive,
on-demand, computational capacity. Websites will use these cloud resources
to provide continuous services that are always available and can be scaled to
meet any fluctuation in demand. These services will constantly gather and ana-
lyze data from both the real and online worlds. Users will interact with these
services using “apps” - software applications - on a range of connected devices.
Increasingly, as the Internet of Things grows, these devices will include many
types of embedded systems, from webcams in our homes to sensors on our
highways.
Strong AI and the mind-body problem
WARNING: In the remaining sections of this chapter, we enter into areas
in which there is no clear consensus among researchers, computer scientists,
neuroscientists, and philosophers. There are many different opinions and often
little agreement even about definitions.
In their topic Artificial Intelligence , Stuart Russell and Peter Norvig define the
terms weak AI and strong AI as follows:
The assertion that machines could act as if they were intelligent is called the
weak AI hypothesis by philosophers, and the assertion that machines that do
so are actually thinking (not just simulating thinking) is called the strong AI
hypothesis. 8
The proposal for John McCarthy's 1956 workshop that introduced the term AI
confidently asserted that weak AI was possible, saying, “Every aspect of learn-
ing or any other feature of intelligence can be so precisely described that a
machine can be made to simulate it.” 9
In their topic, Russell and Norvig take the view that “intelligence is con-
cerned mainly with rational action.” 10 They introduce the idea of building
intelligent systems in terms of agents , subsystems that can perceive their envir-
onment through sensors and can act on the environment through actuators. A
rational agent is one that selects an action that maximizes its performance for
every possible sequence of inputs. The agent can also learn from experience to
improve its performance. Russell and Norvig identify different types of agents,
including reflex agents, goal-based agents, and utility-based agents. Reflex agents
respond only to their last input. Goal-based agents act to achieve a well-defined