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<!DOCTYPE html><html lang="en-us" >
<head>
<meta charset="utf-8">
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<title>MSAIL</title>
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<h1>Search</h1>
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<a class="js-search" href="#"><i class="fas fa-times-circle text-muted" aria-hidden="true"></i></a>
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.maize-btn{background-color:#ffcb05; border-color: #ffcb05; color:#00274c}
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<h1 class="hero-title maize-text">
Michigan Student Artificial Intelligence Lab
</h1>
<div class="hero-lead"><p>A student organization focused on exploring cutting-edge artificial intelligence education, application and research.</p>
</div>
<p class="cta-btns">
<a href="/join" class="btn maize-btn btn-light btn-lg">Sign up!</a>
<a href="https://msail-team.slack.com/ssb/redirect " target="_blank" rel="noopener" class="hero-cta-alt pl-4">Join our Slack <i class="fas fa-angle-right"></i></a>
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<h1>What is MSAIL?</h1>
<p>MSAIL is a student organization devoted to artificial intelligence research. We strive to spread our passion for artificial intelligence throughout the University of Michigan student body, regardless of demographic or academic standing. As of Winter 2024, our main operations are
<a href="education/">education</a>,
<a href="projects/">projects</a>, and
<a href="talk/">reading groups</a>.</p>
</div>
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<h1>Upcoming Talks</h1>
<div style="
display: flex;
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align-items: center;
gap: 50px;
flex-wrap: wrap;
padding: 20px;
">
<img src="Google.jpeg" alt="Upcoming Talk" style="width:300px; height:auto; border-radius:8px;">
<p> MSAIL x Google
We are excited to announce that MSAIL will be hosting an event in collaboration with Google and the UM Artificial Intelligence Laboratory! Join us on <b>Thursday, November 20, from 6:30pm - 7:30pm EST</b> for a discussion on AI-Assisted Development and Coding, featuring <b>Google representatives</b> who will share insights into how AI is transforming the software development process and what the future of AI-powered tools looks like.
<br><br>There are limited spots available, so make sure to RSVP as soon as possible!</p>
<br>
<br>
<br>
<img src="IMG_4080.jpeg" alt="Upcoming Talk" style="width:300px; height:auto; border-radius:8px;">
<p> Molly Welch is a Partner at Radical Ventures, based in San Francisco. Molly invests in AI-native startups at the early-stage, including infrastructure and application AI startups. She has worked with Radical portfolio companies Datology, Muon Space, P-1, Solver, Spara, World Labs, and others not yet public.
Prior to Radical, Molly worked on the Google Brain team, collaborating with research leadership on commercial initiatives and special projects. During graduate school, she also worked on AI policy at Lyft and as a venture investor at frontier tech VC Playground Global.
Molly holds a B.A. with distinction from Stanford University, a Masters in Public Policy from the Harvard Kennedy School, and an MBA with distinction from Harvard Business School.
<br>
<br>
<b>Who:</b> Molly Welch <br>
<b>When:</b> Tuesday September 23, 6:30pm EST
<br>
<br>
RSVP for this event!</p>
</div>
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<a href="/talk/">
See all talks <i class="fas fa-angle-right"></i>
</a>
</div>
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src="https://calendar.google.com/calendar/embed?src=c_1acd07e8dd75073266870b85a133f3b84bc52f7707701bfa0db69495bcca78cb%40group.calendar.google.com&ctz=America%2FDetroit"
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<!-- <section id="posts" class="home-section wg-pages " >
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<h1>Recent Posts</h1>
</div>
<div class="col-12 col-lg-8">
<div class="media stream-item">
<div class="media-body">
<h3 class="article-title mb-0 mt-0">
<a href="/post/molecular_iclr_2022/" >Generating Molecular Conformations via Normalizing Flows and Neural ODEs</a>
</h3>
<a href="/post/molecular_iclr_2022/" class="summary-link">
<div class="article-style">
Post accepted to the ICLR 2022 Blog Track. In this post, we provide an in-depth overview of methods outlined in the paper “Learning Neural Generative Dynamics for Molecular Conformation Generation,” discuss the impact of the work in the context of other conformation generation approaches, and additionally discuss future potential applications to improve the diversity and stability of generated conformations.
</div>
</a>
<div class="stream-meta article-metadata">
<div class="article-metadata">
<div>
<span >Mukundh Murthy</span>, <span >Nikhil Devraj</span>
</div>
<span class="article-date">
Mar 25, 2022
</span>
<span class="middot-divider"></span>
<span class="article-reading-time">
13 min read
</span>
</div>
</div>
</div>
<div class="ml-3">
<a href="/post/molecular_iclr_2022/" >
<img src="/post/molecular_iclr_2022/featured_huc8db73f9d3ef0436f0e58a09de43767e_125311_150x0_resize_q90_lanczos.jpg" alt="Generating Molecular Conformations via Normalizing Flows and Neural ODEs">
</a>
</div>
</div>
<div class="media stream-item">
<div class="media-body">
<h3 class="article-title mb-0 mt-0">
<a href="/post/federated_learning/" >Data privacy and AI</a>
</h3>
<a href="/post/federated_learning/" class="summary-link">
<div class="article-style">
We interact with machine learning algorithms every day–from scrolling through social media, to navigating around town, to selecting word recommendations when we text. But what do we know about these machine learning methods?
</div>
</a>
<div class="stream-meta article-metadata">
<div class="article-metadata">
<div>
<span >Yash Gambhir</span>
</div>
<span class="article-date">
May 19, 2021
</span>
<span class="middot-divider"></span>
<span class="article-reading-time">
9 min read
</span>
</div>
</div>
</div>
<div class="ml-3">
<a href="/post/federated_learning/" >
<img src="/post/federated_learning/featured_hu76831665ed9ecdf2d57e0bc61585f68c_464482_150x0_resize_lanczos_3.png" alt="Data privacy and AI">
</a>
</div>
</div>
<div class="media stream-item">
<div class="media-body">
<h3 class="article-title mb-0 mt-0">
<a href="/post/cnn_human_visual/" >Do convolutional neural networks mimic the human visual system?</a>
</h3>
<a href="/post/cnn_human_visual/" class="summary-link">
<div class="article-style">
Richard Feynman once said “What I cannot create I do not understand.” Therefore, to truly understand the human visual system, we must learn to create it. One of the most effective forms of such creation is the Convolutional Neural Network (CNN) system to mimic the human visual system.
</div>
</a>
<div class="stream-meta article-metadata">
<div class="article-metadata">
<div>
<span >Robert Aung</span>
</div>
<span class="article-date">
Apr 11, 2021
</span>
<span class="middot-divider"></span>
<span class="article-reading-time">
7 min read
</span>
</div>
</div>
</div>
<div class="ml-3">
<a href="/post/cnn_human_visual/" >
<img src="/post/cnn_human_visual/featured_hu7c49d17fc1bb88178f08c352e28faf25_4313839_150x0_resize_lanczos_3.png" alt="Do convolutional neural networks mimic the human visual system?">
</a>
</div>
</div>
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See all posts
<i class="fas fa-angle-right"></i>
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<div class="col-lg-12">
<h1>Education Sessions</h1>
<p style="text-align: center;">
Check out our <a href="education">education tracks</a> and join our slack for session updates. <br>
</p>
</div>
</div>
</div>
</section>