Hi! I'm Tim Tyler - and this is a video which discusses the issue of
whether the path to superintelligent machines will be "broad" or
The breadth of machine intelligence
Enthusiasts for creating general-purpose machine intelligence have
often described classical application-driven development projects as
having a "narrow" scope. Despite - or perhaps because of - the rather
derogatory overtones, the name seems to have stuck - so these days,
"general" machine intelligence projects are sometimes described as
being "broad" - while ones targetted at particular application domains
are usually described as being "narrow".
"Narrow" projects have some advantages. They are more likely to pay the
bills, and actually do something useful in the short term. However,
some have questioned whether such development will lead to the type of
more general-purpose intelligence found in humans.
Here is Ben
Goertzel on the topic:
[Footage of Ben Goertzel]
Follow the money
My take on this issue is that the first superintelligent machines will
probably arise out of a large organisation with a specific mission.
The most likely candidates are probably search engines, stock market
investment firms and governmental security services - such as the NSA.
These organisations seem to me to be the most likely ones to have the
money, manpower and motivation to create the first superintelligence.
In each case, there is a driving problem - which seems best classified
as a being associated with a narrow problem domain.
However, in order to excel at solving these kinds of problems,
considerable breadth of intelligence will be required.
Don't compete with humans
Apart from sheer financial oomph, there is another reason to expect
these kinds of projects to be promising candidates for the role of the
first superintelligent machine.
So far, computing machines have made their inroads into the biosphere
largely by avoiding competing directly with humans - and
instead specializing in the areas where the human brain is weak.
Consequently we have machines with enormous memories, high reliability
and rapid serial performance, which are appalling at parallel
Such machines complement human intelligence - rather than competing
directly with it. They augment humans, rather than attempt to
substitute for them - because human labour is pretty cheap, and
machines can't yet compete directly with us in the cognitive areas
where we are strong.
The search oracles, stockmarket masters, and surveillance gurus than I
envisage waking up first are utterly inhuman entities - whose roles
could not be played by human beings. The fact that they are not in
competition with existing human brains will help them to get off the
So, to summarise, "narrow" machine intelligence projects will be
better funded, are more likely to get earlier access to better
hardware, and will attract a larger research and development budget.
Also, they avoid competing directly with the human brain in areas
where the existing brains hardware is strong - which is a smart
The tip of a wedge is narrow - as it must be, in order to penetrate
initially. A wedge with a broad tip is not very useful. Breadth comes