A GAMEBOY supercomputer
<p><strong>It is 2016</strong>. Deep learning is everywhere. Image recognition can be considered kind of solved by convolutional neural networks and my research interests gravitate towards neural networks with memories and reinforcement learning.</p>
<p><img alt="" src="https://miro.medium.com/v2/resize:fit:263/1*qmfiLeHUwutY9BW-thYo6Q.png" style="height:254px; width:263px" /></p>
<p>Specifically, in a paper showed by <em>Google Deepmind</em>, it has been shown that it is possible to achieve human or even superhuman-level performance on a variety of Atari 2600 (a home game console released in 1977) games using a simple reinforcement learning algorithm called <em>Deep Q-Neural Network</em>. All that done by just observing the gameplay. That caught my attention.</p>
<p><a href="https://towardsdatascience.com/a-gameboy-supercomputer-33a6955a79a4"><strong>Learn More</strong></a></p>