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Dear All, <br>
<br>
You are invited to recommend this new magazine to your colleagues
and submit papers to it.<br>
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charset=ISO-8859-1">
<p>The BMM publishes contributions related to brain, mind, life,
intelligence, law, policy, society, politics, and beyond. The
subject scope includes all subjects that a brain can learn to deal
with. Public oriented analysis about the science behind natural
phenomena is especially welcome.</p>
<p>The BMM explores ways to alleviate limitations of a peer review
system. The editors of BMM do not reject a contribution based on
typical criteria in a peer review system, such as whether the
position expressed is supported by sufficient evidence, whether
the direction of the article is acceptable by the majority of a
community, or whether the view is what public is comfortable to
hear. New knowledge always starts from a single person.<br>
</p>
<p>Your suggestions for improving this new kind of magazine are also
welcome. <br>
</p>
<p>-Juyang Weng<br>
</p>
<br>
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<br>
<h3 class="color-in-selected-button" align="center">Brain-Mind
Magazine<br>
Vol. 1, No. 1, June 2012<br>
<a href="http://www.brain-mind-magazine.org/">http://www.brain-mind-magazine.org/</a><br>
</h3>
<h3 class="color-in-selected-button" align="center">Table of
Contents</h3>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-BMMsubm.pdf">Start
a Different Kind of Magazine</a> 1 <br>
by <em>Juyang Weng </em><br>
<br>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-BMI-Flyer-3-A4Size.pdf">Brain-Mind
Institute: For Future Leaders of Brain-Mind Research</a>
2 <br>
<br>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-Obama.pdf">Open
Letter to the US President Obama: Is the US Foreign Policy
Scientifically Shortsighted?</a><img
src="cid:part5.00030808.03040002@cse.msu.edu" alt="banner"
style="float:left;margin:0 5px 0 0;" height="100" width="100"> 3
- 4<br>
by <em>Juyang Weng </em><br>
<strong>Abstract: </strong>All minds are groupish and shortsighted
in nature. The aftermath of Richard Nixon’s China visit demonstrated
that a scientifically correct foreign policy is to make friends with
foes, counter intuitive to many souls. Our brains blinded us.
Scientific principles, e.g., checks-and-balances of government
power, seem more convincing and effective in converting foes than
shallow and ideological slogans like “human rights”. <br>
<strong>Index terms: </strong>brain, science of mind, foreign policy
<br>
<br>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-BrainStories1.pdf">Brain
Stories 1: Naivety in Everybody</a><img
src="cid:part7.04040603.05090204@cse.msu.edu" alt="banner"
style="float:left;margin:0 5px 0 0;" height="100" width="100"> 5
- 6<br>
by <em>Brian N. Huang </em><br>
<strong>Abstract: </strong>Meant for layman readers, this series
uses real world stories to explain how a single brain works
computationally inside its skull and how multiple brains work
together to give rise to group intelligence. Hopefully, this series
is useful for us humans to see the weakness of our current governing
systems, in developed countries and developing countries alike, and
how a country can develop earlier and better. It also explains some
key mechanisms to make a robot learn skills that its human
programmer does not have. This installment is about naivety, in
childhood and adulthood; in you and in your officials. Brains are
naive for various tasks, making strategic errors with high costs.
This installment raises a few nation-scale naiveties to be discussed
in future installments of this series. <br>
<strong>Index terms: </strong>brain, mind, law, group intelligence <br>
<br>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-ProblemPosing.pdf">Problem
Solving to Problem Posing</a><img
src="cid:part9.07060602.04070209@cse.msu.edu" alt="banner"
style="float:left;margin:0 5px 0 0;" height="100" width="100"> 7
- 8<br>
by <em>Yoonsuck Choe </em>and<em> Timothy A. Mann </em><br>
<strong>Abstract: </strong>Artificial intelligence and machine
learning approaches are both very good at problem solving. However,
the various methods accumulated in these fields have not been able
to give us truly autonomous agents. The main shortcoming is that the
problems themselves are formulated by human designers and
subsequently fed to the problem solving or learning algorithms. The
algorithms do not question the validity of the problems nor do they
formulate new problems. This latter task is called “problem posing”,
and is in fact an active area in education research. In this
article, we will discuss the importance and relevance of problem
posing to autonomous intelligence and speculate on key ingredients
for effective problem posing in an AI and machine learning context.
<br>
<strong>Index terms: </strong>problem posing, education, artificial
intelligence <br>
<br>
<a moz-do-not-send="true"
href="http://www.brain-mind-magazine.org/download-article.php?file=V1-N1-VisionSee.pdf">Why
Should the CVPR Community See that Output Is Not Only Output?</a><img
src="cid:part11.04040003.08040305@cse.msu.edu" alt="banner"
style="float:left;margin:0 5px 0 0;" height="100" width="100"> 9
- 10<br>
by <em>Christopher S. Masfis </em><br>
<strong>Abstract: </strong>The currently prevailing methods in the
computer vision and pattern recognition (CVPR) community require
images for system training. Many of such methods require manually
drawn object contours to segment the pixels from each object of
interest from those pixels in other parts of the image. Does a human
child require such object-contour annotation to learn how to detect,
recognize, and segment objects from cluttered natural scenes? Weng
argued for a negative answer. He explained that a brain autonomously
learns directly from its physical environment using not only
non-annotated continuous video of dynamic and cluttered scenes, but
also its video-synchronized actions — output is also input.
Body-environment interactions give rise to brain representations. In
particular, contour annotation is not necessary for a brain, neither
for a machine. <br>
<strong>Index terms: </strong>pattern recognition, computer vision,
brain <br>
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