Push dev branch build

docs/contents/contributors.html

@@ -744,10 +744,10 @@ <h1 class="title">Contributors &amp; Thanks</h1>
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-<a href="https://github.com/shanzehbatool"><img src="https://avatars.githubusercontent.com/shanzehbatool?s=100" width="100px;" alt="shanzehbatool"><br><sub><b>shanzehbatool</b></sub></a><br>
+<a href="https://github.com/Mjrovai"><img src="https://avatars.githubusercontent.com/Mjrovai?s=100" width="100px;" alt="Marcelo Rovai"><br><sub><b>Marcelo Rovai</b></sub></a><br>
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-<a href="https://github.com/Mjrovai"><img src="https://avatars.githubusercontent.com/Mjrovai?s=100" width="100px;" alt="Marcelo Rovai"><br><sub><b>Marcelo Rovai</b></sub></a><br>
+<a href="https://github.com/shanzehbatool"><img src="https://avatars.githubusercontent.com/shanzehbatool?s=100" width="100px;" alt="shanzehbatool"><br><sub><b>shanzehbatool</b></sub></a><br>
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 <a href="https://github.com/mpstewart1"><img src="https://avatars.githubusercontent.com/mpstewart1?s=100" width="100px;" alt="Matthew Stewart"><br><sub><b>Matthew Stewart</b></sub></a><br>
@@ -832,30 +832,30 @@ <h1 class="title">Contributors &amp; Thanks</h1>
 <a href="https://github.com/jared-ni"><img src="https://avatars.githubusercontent.com/jared-ni?s=100" width="100px;" alt="Jared Ni"><br><sub><b>Jared Ni</b></sub></a><br>
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-<a href="https://github.com/Ekhao"><img src="https://avatars.githubusercontent.com/Ekhao?s=100" width="100px;" alt="Emil Njor"><br><sub><b>Emil Njor</b></sub></a><br>
+<a href="https://github.com/oishib"><img src="https://avatars.githubusercontent.com/oishib?s=100" width="100px;" alt="oishib"><br><sub><b>oishib</b></sub></a><br>
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-<a href="https://github.com/oishib"><img src="https://avatars.githubusercontent.com/oishib?s=100" width="100px;" alt="oishib"><br><sub><b>oishib</b></sub></a><br>
+<a href="https://github.com/harvard-edge/cs249r_book/graphs/contributors"><img src="https://www.gravatar.com/avatar/71b1bd9ab89c2648e3a1c9641d5e0c54?d=identicon&amp;s=100?s=100" width="100px;" alt="Haoran Qiu"><br><sub><b>Haoran Qiu</b></sub></a><br>
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 <a href="https://github.com/MichaelSchnebly"><img src="https://avatars.githubusercontent.com/MichaelSchnebly?s=100" width="100px;" alt="Michael Schnebly"><br><sub><b>Michael Schnebly</b></sub></a><br>
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-<a href="https://github.com/leo47007"><img src="https://avatars.githubusercontent.com/leo47007?s=100" width="100px;" alt="Yu-Shun Hsiao"><br><sub><b>Yu-Shun Hsiao</b></sub></a><br>
+<a href="https://github.com/Ekhao"><img src="https://avatars.githubusercontent.com/Ekhao?s=100" width="100px;" alt="Emil Njor"><br><sub><b>Emil Njor</b></sub></a><br>
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 <a href="https://github.com/BaeHenryS"><img src="https://avatars.githubusercontent.com/BaeHenryS?s=100" width="100px;" alt="Henry Bae"><br><sub><b>Henry Bae</b></sub></a><br>
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-<a href="https://github.com/harvard-edge/cs249r_book/graphs/contributors"><img src="https://www.gravatar.com/avatar/71b1bd9ab89c2648e3a1c9641d5e0c54?d=identicon&amp;s=100?s=100" width="100px;" alt="Haoran Qiu"><br><sub><b>Haoran Qiu</b></sub></a><br>
+<a href="https://github.com/mmaz"><img src="https://avatars.githubusercontent.com/mmaz?s=100" width="100px;" alt="Mark Mazumder"><br><sub><b>Mark Mazumder</b></sub></a><br>
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 <a href="https://github.com/jaywonchung"><img src="https://avatars.githubusercontent.com/jaywonchung?s=100" width="100px;" alt="Jae-Won Chung"><br><sub><b>Jae-Won Chung</b></sub></a><br>
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-<a href="https://github.com/mmaz"><img src="https://avatars.githubusercontent.com/mmaz?s=100" width="100px;" alt="Mark Mazumder"><br><sub><b>Mark Mazumder</b></sub></a><br>
+<a href="https://github.com/leo47007"><img src="https://avatars.githubusercontent.com/leo47007?s=100" width="100px;" alt="Yu-Shun Hsiao"><br><sub><b>Yu-Shun Hsiao</b></sub></a><br>
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 <a href="https://github.com/marcozennaro"><img src="https://avatars.githubusercontent.com/marcozennaro?s=100" width="100px;" alt="Marco Zennaro"><br><sub><b>Marco Zennaro</b></sub></a><br>

docs/contents/ml_systems/ml_systems.html

@@ -881,13 +881,13 @@ <h3 data-number="2.3.3" class="anchored" data-anchor-id="challenges-1"><span cla
 </section>
 <section id="example-use-cases-1" class="level3" data-number="2.3.4">
 <h3 data-number="2.3.4" class="anchored" data-anchor-id="example-use-cases-1"><span class="header-section-number">2.3.4</span> Example Use Cases</h3>
-<p>Edge ML has many applications, from autonomous vehicles and smart homes to industrial IoT. These examples were chosen to highlight scenarios where real-time data processing, reduced latency, and enhanced privacy are not just beneficial but often critical to the operation and success of these technologies. They demonstrate the role that Edge ML can play in driving advancements in various sectors, fostering innovation, and paving the way for more intelligent, responsive, and adaptive systems.</p>
+<p>Edge ML has many applications, from autonomous vehicles and smart homes to industrial Internet of Things (IoT). These examples were chosen to highlight scenarios where real-time data processing, reduced latency, and enhanced privacy are not just beneficial but often critical to the operation and success of these technologies. They demonstrate the role that Edge ML can play in driving advancements in various sectors, fostering innovation, and paving the way for more intelligent, responsive, and adaptive systems.</p>
 <p><strong>Autonomous Vehicles</strong></p>
 <p>Autonomous vehicles stand as a prime example of Edge ML’s potential. These vehicles rely heavily on real-time data processing to navigate and make decisions. Localized machine learning models assist in quickly analyzing data from various sensors to make immediate driving decisions, ensuring safety and smooth operation.</p>
 <p><strong>Smart Homes and Buildings</strong></p>
 <p>Edge ML plays a crucial role in efficiently managing various systems in smart homes and buildings, from lighting and heating to security. By processing data locally, these systems can operate more responsively and harmoniously with the occupants’ habits and preferences, creating a more comfortable living environment.</p>
 <p><strong>Industrial IoT</strong></p>
-<p>The Industrial Internet of Things (IoT) leverages Edge ML to monitor and control complex industrial processes. Here, machine learning models can analyze data from numerous sensors in real-time, enabling predictive maintenance, optimizing operations, and enhancing safety measures. This revolution in industrial automation and efficiency.</p>
+<p>The Industrial IoT leverages Edge ML to monitor and control complex industrial processes. Here, machine learning models can analyze data from numerous sensors in real-time, enabling predictive maintenance, optimizing operations, and enhancing safety measures. This revolution in industrial automation and efficiency is transforming manufacturing and production across various sectors.</p>
 <p>The applicability of Edge ML is vast and not limited to these examples. Various other sectors, including healthcare, agriculture, and urban planning, are exploring and integrating Edge ML to develop innovative solutions responsive to real-world needs and challenges, heralding a new era of smart, interconnected systems.</p>
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docs/index.html

@@ -7,7 +7,7 @@
 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
 <meta name="author" content="Vijay Janapa Reddi">
-<meta name="dcterms.date" content="2024-09-01">
+<meta name="dcterms.date" content="2024-09-02">
 
 <title>Machine Learning Systems</title>
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@@ -683,7 +683,7 @@ <h1 class="title">Machine Learning Systems</h1>
     <div>
     <div class="quarto-title-meta-heading">Last Updated</div>
     <div class="quarto-title-meta-contents">
-      <p class="date">September 1, 2024</p>
+      <p class="date">September 2, 2024</p>
     </div>
   </div>