The Helen Keller example is probably not appropriate since her
intelligence was the result of an evolutionary process that expected
inputs typical of an embodiment, and in the absence of a number of those
developed itself with what input was available. I would say this only
indicates how similar humans really are, not how an intelligence can
develop from any old basis. Trying to create an intelligence that is not
embodied the way John suggests might work in some fashion, but don't
expect it to be able to understand or relate much to humanity.
On 6/30/2015 3:40 PM, Julian Samaroo wrote:
The body is really just the input and output systems that the neural
structures attach to, as well as providing the ever-important task of
supplying nutrients, fighting disease, etc. But in AI, it is simply
abstracted away, and you are left with a set of sensory inputs and
motor outputs, which can be anything you'd like. As David said, sight
and audition aren't vital to intelligence in its most simplistic form,
and you can thus attach something like HTM to any input-output pair
that you can think up (although this doesn't necessarily imply
anything useful will come of it).
Julian Samaroo
Manager of Information Technology
BluePrint Pathways, LLC
(516) 993-1150
On Tue, Jun 30, 2015 at 2:36 PM, cogmission (David Ray)
<[email protected] <mailto:[email protected]>> wrote:
John,
I just thought of this. I wonder how relevant the experiences of
sensory deprived individuals are to a comparison of the
capabilities of "dis-embodied" intelligences? Someone like Helen
Keller who maybe only had kinesthetic and taste senses, could
maybe be analogous in some way to a developing dis-embodied
intelligence? Maybe not, just a thought...
On Tue, Jun 30, 2015 at 2:21 PM, Matthew Taylor <[email protected]
<mailto:[email protected]>> wrote:
John,
Just to make sure that all your questions have been addressed
directly:
On Tue, Jun 30, 2015 at 2:55 AM, John Blackburn
<[email protected]
<mailto:[email protected]>> wrote:
> "performs with true intelligence" is a pretty bold claim. If
this is
> the case, how come there are no very convincing examples of HTM
> working with human like intelligence? The Hotgym example is
nice but
> it is really no better than what could be achieved with many
existing
> neural networks. Echo state networks have been around for
years and
> can make temporal predictions quite well.
People define "intelligence" in different ways. If you take for
granted that the neocortex has "true intelligence", then HTM
might be
called an implementation of "true intelligence" algorithms
based upon
the fact that it acts upon incoming data with the same basic
principles as the neocortex. We are trying to lift the
intelligence
out of the brain and into software, one step at a time.
So, while NuPIC's performance might not seem all that
impressive when
other technologies can do similar things, we have lots of room
to grow
[1] and a lot more work to do. All of this upcoming work should
increase the capabilities of the HTM system we are
implementing. The
fact that we are somewhat on-par with some other ML techniques
at this
point is encouraging to me.
> I recently presented some
> time sequence data relating to a bridge to this forum but
HTM did not
> succeed in modelling this (ESNs worked much better).
I had a little time to work on your bridge tilt data [2], but not
enough to make it useful. I still think this problem presents a
relevant challenge for HTM, and I think with more time and effort,
someone might be able to create a real solution. I, unfortunately,
have other projects I have to work on. :(
> So outside of
> Hotgym, what really compelling demos do you have? I've been
away for a
> while so maybe I missed something...
My current favorites are location-based anomaly demos like these:
- https://github.com/nupic-community/mine-hack
- https://github.com/numenta/nupic.geospatial
I am also working on a new tutorial, coming within a couple
weeks (hopefully).
> I am also rather concerned HTM needs swarming before it can
model
> anything. Isn't that "cheating" in a way? It seems the HTM
is rather
> fragile and needs a lot of help. The human brain does not
have this
> luxury it just has to cope with whatever data it gets.
Swarming is hard to explain. In the brain, input data to the
neocortex
comes from sensory organs, which have been tuned by millions
of years
of evolution to have very specific characteristics that process
incoming light, sound, movement, etc. into certain patterns of
nerve
excitations. These patterns get generated outside the cortex,
but they
are still important to attempt to replicate in some ways. All
data in
"reality" must be represented to the cortex somehow outside of
that
reality. In NuPIC, this is what encoders so. They translate data
coming into them into a representation similar to a vector of
nerve
excitations.
Anyway, swarming is a very rough way to simulate evolution in the
sensory organs. It randomly sets up encoders with different
parameters
(also spatial pooling and temporal memory parameters) and tries to
find the best possible set of configurations for the specific data
that is being processed. Your cochlea have had millions of
years to
come to that perfect set of configuration parameters ;).
Swarming is a
brute-force attempt to resolve some set of parameters for a
specific
input data set. It is not always right, it takes a long time,
and it
sometimes requires manual intervention, but it definitely very
useful
for finding groups of configurations that work well for
certain types
of data.
> I'm also not convinced the neocortex is everything as Jeff
Hawkins
> thinks. I seriously doubt the bulk of the brain is just
scaffolding.
> I've been told birds have no neocortex but are capable of very
> intelligent behaviour including constructing tools.
Meanwhile I don't
> see any AI robot capable of even ant-like intelligence.
(ants are
> amazing!) Has anyone even constructed a robot based on HTM?
While I know nothing about bird brains, except that they have a
cerebral cortex that has some similarities to the mammalian
cortex, I
do know that hierarchy in the neocortex is a generally
accepted theory
in neuroscience.
We could still learn a helluva lot from the lower levels of
the brain
(imagine a flight vehicle that could control itself as
efficiently as
a fly), that just isn't what we're trying to do at Numenta.
> Personally I don't think a a disembodied computer can ever be
> intelligent (not even ant-like intelligence). IMO a robot
(and it must
> BE a robot) needs to be embodied with sensory-motor loop at
the core
> of its functionality to start behaving like an animal.
You don't need to have physical interaction with the world to have
behavior. There are millions of actions that can be taken on the
internet that all have consequences, change the landscape for the
actor, and present different possible actions in return. The most
obvious example is video games, but the internet in general is
a very
large universe with no physical structure, but endless virtual
structures to interact with.
[1]
https://github.com/numenta/nupic.research/wiki/Current-Research-Tasks
[2] https://github.com/nupic-community/bridge-tilt
Regards,
--
/With kind regards,/
David Ray
Java Solutions Architect
*Cortical.io <http://cortical.io/>*
Sponsor of: HTM.java <https://github.com/numenta/htm.java>
[email protected] <mailto:[email protected]>
http://cortical.io <http://cortical.io/>
