Connectionists: Workshop Progress in Brain-Like Computing, February 5-6 2014

Sun Jan 26 13:25:00 EST 2014

Dear John and all,

I was not aware until this morning that my simple announcement of the
workshop on ”Progress in Brain-Like Computing” at KTH Royal Institute of
Technology in Stockholm next week had stirred up such a vivid discussion on
the list. I was on a conference trip to Singapore with only occasional web
access and got back only yesterday. Allow me some comments and reflections.

I agree with some of the original points made by John Weng on that we need
brain-scale theories in order to make real progress in brain-like computing
and what the focus should be. Indeed, I think we see some maybe vague
contours of partial theories that wait to be integrated to a more complete
understanding.

Since the terminology of “brain-like” was criticized from different
perspectives, allow me some motivation why we use this term. We could have
stated “neuromorphic” but in my opinion this term leads the thoughts a bit
too much towards microscopic and microcircuit levels. After all real brains
not only have very many neurons and synapses but also a very complex
structure in terms of specialized neural populations and projections
connecting them. We have today chips and clusters that are able to simulate
with reasonable throughput such multi-neural-network structures (if not too
complex components 
) so we can at least computationally handle this level,
rather than staying with small simple networks. Personally I think that to
understand principles of brain function we need to avoid a lot but not all
of the complexity we see at the single neuron and synapse levels. I also
prefer the term “brain-like” rather than “brain-inspired” since the former
defines the goal of building computational structures that are like brains
and not just to start there and then perhaps quickly, in all our
inspiration, diverge away from mimicking the essential aspects of real
brains.

It is interesting to note that the subject of the discussion quickly
deviated from the main content of our workshop which has to do with
designing and eventually building brain-like computational architectures in
silicon – or some more exotic substrate. Such research has been going on for
long time and is now seeing increasing efforts. It can obviously be argued
whether this is still premature or if it is now finally the right time to
boost such efforts. Despite the fact that our knowledge about the brain is
still not complete 

What also strikes me when I read this discussion is that we are still quite
a divided and diverse community with minor consensus. There are many who
think we are many decades away from doing the above, many who study abstract
computational “deep learning” network models for classification and
prediction without bothering much about the biology, many who study
experimentally or model brain circuits without focusing much on what
functions they perform, and many who design hardware without knowing exactly
what features to include, etc. 

But I am optimistic! Perhaps, in the near future, these efforts will combine
synergistically and the pieces of the puzzle will start falling in place,
triggering a series of real breakthroughs in our understanding of how our
brain works. To identify at what point in time and what stage in brain
science this will happen is indeed critical. Then, those who have the best
understanding of how to design the hardware appropriate for executing in
real time or faster this integrated set of brain-like algorithms in a
low-power way will be in an excellent position for exploiting such progress
in many important applications – hopefully beneficial for mankind!

This is some of the background for organizing the event I announced, which
will hopefully contribute something to the further discussion on these very
important topics.

/Anders La

From: Juyang Weng [mailto:weng at cse.msu.edu] 
Sent: den 23 januari 2014 19:09
To: Anders Lansner
Cc: connectionists at cs.cmu.edu
Subject: Re: Connectionists: Workshop Progress in Brain-Like Computing,
February 5-6 2014

Dear Anders,

Interesting topic about the brain!  But Brain-Like Computing is misleading
because neural networks have been around for at least 70 years.

I quote: "We are now approaching the point when our knowledge will enable
successful demonstrations of some of the underlying principles in software
and hardware, i.e. brain-like computing."

What are the underlying principles?  I am concerned that projects like
"Brain-Like Computing" avoid essential issues: 
the wide gap between neuron-like computing and well-known highly integrated
brain functions.
Continuing this avoidance would again create bad names for "brain-like
computing", just such behaviors did for "neural networks".

Henry Markram criticized IBM's brain project which does miss essential brain
principles, but has he published such principles?
Modeling individual neurons more and more precisely will explain highly
integrated brain functions?   From what I know, definitely not, by far. 

Has any of your 10 speakers published any brain-scale theory that bridges
the wide gap?  Are you aware of any such published theories? 

I am sorry for giving a CC to the list, but many on the list said that they
like to hear discussions instead of just event announcements. 

-John

On 1/13/14 12:14 PM, Anders Lansner wrote:

Workshop on Brain-Like Computing, February 5-6 2014

The exciting prospects of developing brain-like information processing is
one of the Deans Forum focus areas.
As a means to encourage progress in this research area a Workshop is
arranged February 5th-6th 2014 on KTH campus in Stockholm. 

The human brain excels over contemporary computers and robots in processing
real-time unstructured information and uncertain data as well as in
controlling a complex mechanical platform with multiple degrees of freedom
like the human body. Intense experimental research complemented by
computational and informatics efforts are gradually increasing our
understanding of underlying processes and mechanisms in small animal and
mammalian brains and are beginning to shed light on the human brain. We are
now approaching the point when our knowledge will enable successful
demonstrations of some of the underlying principles in software and
hardware, i.e. brain-like computing.

This workshop assembles experts, from the partners and also other leading
names in the field, to provide an overview of the state-of-the-art in
theoretical, software, and hardware aspects of brain-like computing.

List of speakers

Speaker

Affiliation

Giacomo Indiveri

ETH Zürich

Abigail Morrison

Forschungszentrum Jülich

Mark Ritter

IBM Watson Research Center

Guillermo Cecchi

IBM Watson Research Center

Anders Lansner

KTH Royal Institute of Technology

Ahmed Hemani

KTH Royal Institute of Technology

Steve Furber

University of Manchester

Kazuyuki Aihara

University of Tokyo

Karlheinz Meier

Heidelberg University

Andreas Schierwagen

Leipzig University

For signing up to the Workshop please use the registration form found at
<http://bit.ly/1dkuBgR> http://bit.ly/1dkuBgR

You need to sign up before January 28th.

Web page:
http://www.kth.se/en/om/internationellt/university-networks/deans-forum/work
shop-on-brain-like-computing-1.442038 

******************************************

Anders Lansner

Professor in Computer Science, Computational biology

School of Computer Science and Communication

Stockholm University and Royal Institute of Technology (KTH)

ala at kth.se, +46-70-2166122

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--
Juyang (John) Weng, Professor
Department of Computer Science and Engineering
MSU Cognitive Science Program and MSU Neuroscience Program
428 S Shaw Ln Rm 3115
Michigan State University
East Lansing, MI 48824 USA
Tel: 517-353-4388
Fax: 517-432-1061
Email: weng at cse.msu.edu
URL: http://www.cse.msu.edu/~weng/
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