add thesis thesis

talks/2017_Seminar.html

@@ -68,20 +68,27 @@ <h1>Motivation</h1>
             <h2>[Supervised] learning in a nutshell</h2>
             <img src='img/ml-900.png' alt='machine learning'/>
           </section>
-          <section>
           <section>
             <h2>Random forests</h2>
             <img src='img/random_forests.png' alt='machine learning'/>
           </section>
           <section>
             <img src='img/biorxiv-scientifictheories.png' alt='biorxiv'/>
           </section>
-    <section>
+          <section>
             <h2>The thesis' thesis</h2>
-      <p></p>
-      <br/>
-      <p></p>
-    </section>
+
+            <p>Biodiversity is shaped by too many factors (speciation,
+            stochastic drift, selection from abiotic and biotic factors) to be
+            understood with a single unifying theory.</p>
+
+            <br/>
+
+            <p>Thus, we must combine traditional theories with techniques
+            capable of learning from data, but we must be able to keep the
+            structure and clarity of these traditional theories.</p>
+
+          </section>
           <section>
             <img src='img/reasoning_systems.png' alt='reasoning systems'/>
           </section>