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This week in Artificial Intelligence & Security - #28 of 2016
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<abbr class="published" title="2016-07-16T00:00:00">
Sat 16 July 2016 </abbr>
<span class="label"> Category</span>
<a href="./category/ai-ml-security.html"><i class="icon-folder-open"></i>AI & ML, Security</a>
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<p><img alt="cyberpunk" height="300px" src="./cyberpunk/3.gif" width="400px" /></p>
<h2>Papers</h2>
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<li>
<p><a href="https://gogameguru.com/i/2016/03/deepmind-mastering-go.pdf">Mastering the Game of Go with Deep Neural Networks and Tree Search</a>. <em>"All games of perfect information have an optimal
value function which determines the outcome of the game".</em> , Basically:</p>
<ul>
<li>Values networks to evaluate board positions and policy networks to select moves.</li>
<li>Trained with supervised learning from human expert games and reinforcement learning from games of self-play.</li>
<li>NN playS Go at the level of state-of-art Monte-Carlo tree search that simulate thousands of random games of self-play.</li>
<li>New search algorithm that combines Monte-Carlo simulation with value and policy network.</li>
</ul>
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<li>
<p><a href="http://arxiv.org/pdf/1607.02533v1.pdf">Adversarial Examples in the Physical World (Kurakin, <em>et al.</em>, 2016)</a>.</p>
</li>
</ul>
<h2>News</h2>
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<li><a href="http://www.benjamintd.com/blog/spynet/?utm_campaign=Artificial%2BIntelligence%2BWeekly&utm_medium=web&utm_source=Artificial_Intelligence_Weekly_42">Teaching an AI to write Python code with Python code</a></li>
<li><a href="http://colah.github.io/posts/2015-08-Understanding-LSTMs/">Understanding LSTM Networks</a></li>
<li><a href="http://efavdb.com/deep-learning-with-jupyter-on-aws/">Starting DL with Jupyter</a></li>
<li><a href="https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.gc2fcdcce7_216_515">DIY Deep Learning for Vision: a Hands-On Tutorial with Caffe</a></li>
<li><a href="https://research.googleblog.com/2016/06/wide-deep-learning-better-together-with.html">Wide & Deep Learning: Better Together with TensorFlow</a>. <em>Can we teach computers to learn like humans do, by combining the power of memorization and generalization?</em></li>
</ul>
<h2>Videos</h2>
<ul>
<li><a href="http://icml.cc/2016/tutorials/icml2016_tutorial_deep_residual_networks_kaiminghe.pdf">Deep Residual Networks, Kaiming He, Facebook AI Research</a>.</li>
<li><a href="http://www0.cs.ucl.ac.uk/staff/d.silver/web/Resources_files/AlphaGo_IJCAI.pdf">AlphaGo Presentation</a>.</li>
<li><a href="https://www.youtube.com/watch?v=XkltShNd6XE">Prof. Jürgen Schmidhuber - True Artificial Intelligence Will Change Everything</a>.</li>
</ul>
<h2>Learning</h2>
<ul>
<li>
<p><a href="https://www.quora.com/What-are-your-recommendations-for-self-studying-machine-learning/answer/Yann-LeCun">Yann LeCun on What are your recommendations for self-studying machine learning?</a>.</p>
</li>
<li>
<p><a href="http://www.deeplearningbook.org/">Deep Learning Book</a>.</p>
</li>
</ul>
<h2>Fun</h2>
<ul>
<li><a href="https://diogenes.greedbag.com/buy/ghost-lanes-0/">Post-Rock as it best: Ghost Lanes</a></li>
</ul>
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<img alt="cyberpunk" height="600px" src="./draws/6.png" width="900px" />
<img alt="cyberpunk" height="600px" src="./draws/7.png" width="900px" /></p>
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