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@@ -41,6 +41,8 @@ <h2 class="date">2020/04/09</h2>
     <p><em>Update 2020-06-27</em>: this paper was presented as a `poster&rsquo;(video) at the <a href="https://sites.google.com/view/RL4RealLife">RL for Real Life virtual
 Conference</a>. Read more
 <a href="/posts/rl-at-workshop/">here</a>.</p>
+<iframe src="https://archive.org/embed/rlfor-real-life-2020" width="640" height="480"
+frameborder="0" webkitallowfullscreen="true" mozallowfullscreen="true" allowfullscreen></iframe>
 <p>Reinforcement learning (RL) is becoming an increasingly popular tool to tackle hairy problems
 using data. A nice example of such a hairy problem is <em>personalization</em>. Personalization
 refers to a task central to many applications of data science and machine learning: to change a