<div dir="ltr"><p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif">To whom it may concern,</span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif"> </span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif"> This is
Shuling Chen. I am a research assistant in Dare Institute, Cambridge, MA. My
supervisor Michael Lamport Commons, who is a professor from department of
Psychiatry at Harvard Medical School, published a paper called "Stacked
Neural Networks Must Emulate Evolution's Hierarchical Complexity"
(Commons, 2008). The paper mainly discussed current issues in neural
networks based on the Model of Hierarchical Complexity (Commons, Trudeau,
Stein, Richards, and Krause, 1998) and provided possible solutions that
can help resolve related problems. Feel free to contact me if you are
interested in the paper or related topics and I will email back to you as soon
as possible.</span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif"> </span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif"> </span></p>
<p style="margin-left:0.5in;text-indent:0.5in"><span style="font-size:10pt;font-family:Arial,sans-serif">Stacked
Neural Networks Must Emulate Evolution's Hierarchical Complexity</span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif">Abstract</span></p>
<p style="text-indent:0.5in"><span style="font-size:10pt;font-family:Arial,sans-serif">The
missing ingredients in efforts to develop neural networks and artificial
intelligence (AI) that can emulate human intelligence have been the
evolutionary processes of performing tasks at increased orders of hierarchical
complexity. Stacked neural networks based on the Model of Hierarchical
Complexity could emulate evolution’s actual learning processes and behavioral
reinforcement. Theoretically, this should result in stability and reduce
certain programming demands. The eventual success of such methods begs
questions of humans’ survival in the face of androids of superior intelligence
and physical composition. These raise future moral questions worthy of
speculation.</span></p>
<p style="text-indent:0.5in"><span style="font-size:10pt;font-family:Arial,sans-serif"> </span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif">Reference:</span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif">Commons, M. L. (2008). Stacked
Neural Networks Must Emulate Evolution's Hierarchical Complexity. <i>World Futures</i>, <i>64</i>(5-7),
444-451.</span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif"> </span></p>
<p style="background-repeat:initial initial"><span style="font-size:10pt;font-family:Arial,sans-serif">Commons, M. L., Trudeau, E. J.,
Stein, S. A., Richards, F. A., & Krause, S. R. (1998). Hierarchical
complexity of tasks shows the existence of developmental stages. <i>Developmental
Review</i>, <i>18</i>(3), 237-278.</span></p><div><br></div>-- <br><div dir="ltr"><p style="font-family:arial;font-size:small"><font color="#000000">Regards, </font></p><div><font color="#000000"><br></font></div><div><font color="#000000"><br>
</font></div><div><font color="#000000"><br></font></div><div><font color="#000000"><br></font></div><div><font color="#000000"><br></font></div><div><span style="color:rgb(0,0,0)">Shuling Chen</span><br></div><div><div style="font-family:arial;font-size:small">
<div dir="ltr"><div><font face="arial, helvetica, sans-serif">Research Assistant</font></div><div><font face="arial, helvetica, sans-serif">Dare Institute</font></div><div><font face="arial, helvetica, sans-serif">234 Huron Avenue</font></div>
<div><font face="arial, helvetica, sans-serif">Cambridge, MA 02138</font></div><div><font face="arial, helvetica, sans-serif"><br></font></div><div><pre cols="72" style="white-space:pre-wrap"><font face="arial, helvetica, sans-serif"><font color="#330033">Phone: </font><font color="#1155cc">631-406-3488</font><font color="#330033">
</font><font color="#330033">Email Address: <a href="mailto:shuling.chen.dareinstitute@gmail.com" target="_blank">shuling.chen.dareinstitute@gmail.com</a></font><font color="#330033">
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