Rebuilt site

images/index.xml

@@ -7,33 +7,28 @@
     <generator>Hugo -- gohugo.io</generator>
     <language>en-us</language>
     <managingEditor>[email protected] (David Evans)</managingEditor>
-    <webMaster>[email protected] (David Evans)</webMaster><atom:link href="https://llmrisks.github.io/images/index.xml" rel="self" type="application/rss+xml" />
+    <webMaster>[email protected] (David Evans)</webMaster>
+    <atom:link href="https://llmrisks.github.io/images/index.xml" rel="self" type="application/rss+xml" />
     <item>
       <title></title>
       <link>https://llmrisks.github.io/images/week14/day1/test/</link>
-      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
-      <author>[email protected] (David Evans)</author>
+      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><author>[email protected] (David Evans)</author>
       <guid>https://llmrisks.github.io/images/week14/day1/test/</guid>
       <description></description>
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-
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       <title></title>
       <link>https://llmrisks.github.io/images/week14/day2/test/</link>
-      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
-      <author>[email protected] (David Evans)</author>
+      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><author>[email protected] (David Evans)</author>
       <guid>https://llmrisks.github.io/images/week14/day2/test/</guid>
       <description></description>
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     <item>
       <title></title>
       <link>https://llmrisks.github.io/images/week14/test/</link>
-      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
-      <author>[email protected] (David Evans)</author>
+      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><author>[email protected] (David Evans)</author>
       <guid>https://llmrisks.github.io/images/week14/test/</guid>
       <description></description>
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 </rss>

post/index.html

@@ -83,6 +83,27 @@
 <div class="row">
 
 
+    <h2><a href="/summary/">Summary of Semester</a></h2>
+<div class="post-metadata">
+  <span class="post-date">
+    <time datetime="2023-12-12 00:00:00 &#43;0000 UTC" itemprop="datePublished">12 December 2023</time>
+  </span>
+
+</div>
+
+
+Here&rsquo;s a summary of the topics for the semester:
+Week 1: Introduction
+Attention, Transformers, and BERT Training LLMs, Risks and Rewards Week 2: Alignment
+Introduction to AI Alignment and Failure Cases Redteaming Jail-breaking LLMs Week 3: Prompting and Bias
+Prompt Engineering Marked Personas Week 4: Capabilities of LLMs
+LLM Capabilities Medical Applications of LLMs Week 5: Hallucination
+Hallucination Risks Potential Solutions Week 6: Visit from Anton Korinek
+Week 7: Generative Adversarial Networks and DeepFakes
+<p class="text-right"><a href="/summary/">Read More…</a></p>
+
+
+
     <h2><a href="/week14b/">Week 14b: Ethical AI</a></h2>
 <div class="post-metadata">
   <span class="post-date">
@@ -231,23 +252,6 @@ <h2><a href="/week7/">Week 7: GANs and DeepFakes</a></h2>
 
 
 
-    <h2><a href="/week5/">Week 5: Hallucination</a></h2>
-<div class="post-metadata">
-  <span class="post-date">
-    <time datetime="2023-10-04 00:00:00 &#43;0000 UTC" itemprop="datePublished">4 October 2023</time>
-  </span>
-
-</div>
-
-
-(see bottom for assigned readings and questions)
-Hallucination (Week 5) Presenting Team: Liu Zhe, Peng Wang, Sikun Guo, Yinhan He, Zhepei Wei
-Blogging Team: Anshuman Suri, Jacob Christopher, Kasra Lekan, Kaylee Liu, My Dinh
-Wednesday, September 27th: Intro to Hallucination People Hallucinate Too Hallucination Definition There are three types of hallucinations according to the “Siren's Song in the AI Ocean” paper: Input-conflict: This subcategory of hallucinations deviates from user input. Context-conflict: Context-conflict hallucinations occur when a model generates contradicting information within a response.
-<p class="text-right"><a href="/week5/">Read More…</a></p>
-
-
-
     <div class="row">
   <div class="column small-12">
     <ul class="pagination" role="navigation" aria-label="Pagination">

post/page/2/index.html

@@ -83,6 +83,23 @@
 <div class="row">
 
 
+    <h2><a href="/week5/">Week 5: Hallucination</a></h2>
+<div class="post-metadata">
+  <span class="post-date">
+    <time datetime="2023-10-04 00:00:00 &#43;0000 UTC" itemprop="datePublished">4 October 2023</time>
+  </span>
+
+</div>
+
+
+(see bottom for assigned readings and questions)
+Hallucination (Week 5) Presenting Team: Liu Zhe, Peng Wang, Sikun Guo, Yinhan He, Zhepei Wei
+Blogging Team: Anshuman Suri, Jacob Christopher, Kasra Lekan, Kaylee Liu, My Dinh
+Wednesday, September 27th: Intro to Hallucination People Hallucinate Too Hallucination Definition There are three types of hallucinations according to the “Siren's Song in the AI Ocean” paper: Input-conflict: This subcategory of hallucinations deviates from user input. Context-conflict: Context-conflict hallucinations occur when a model generates contradicting information within a response.
+<p class="text-right"><a href="/week5/">Read More…</a></p>
+
+
+
     <h2><a href="/week4/">Week 4: Capabilities of LLMs</a></h2>
 <div class="post-metadata">
   <span class="post-date">

sitemap.xml

@@ -3,10 +3,13 @@
   xmlns:xhtml="http://www.w3.org/1999/xhtml">
   <url>
     <loc>https://llmrisks.github.io/post/</loc>
-    <lastmod>2023-12-04T00:00:00+00:00</lastmod>
+    <lastmod>2023-12-12T00:00:00+00:00</lastmod>
   </url><url>
     <loc>https://llmrisks.github.io/</loc>
-    <lastmod>2023-12-04T00:00:00+00:00</lastmod>
+    <lastmod>2023-12-12T00:00:00+00:00</lastmod>
+  </url><url>
+    <loc>https://llmrisks.github.io/summary/</loc>
+    <lastmod>2023-12-12T00:00:00+00:00</lastmod>
   </url><url>
     <loc>https://llmrisks.github.io/week14b/</loc>
     <lastmod>2023-12-04T00:00:00+00:00</lastmod>

src/content/post/summary.md

@@ -0,0 +1,66 @@
++++
+date = "12 Dec 2023"
+draft = false
+title = "Summary of Semester"
+slug = "summary"
++++
+
+Here's a summary of the topics for the semester:
+
+[Week 1: Introduction](/week1)
+- Attention, Transformers, and BERT
+- Training LLMs, Risks and Rewards
+
+[Week 2: Alignment](/week2)
+- Introduction to AI Alignment and Failure Cases
+- Redteaming
+- Jail-breaking LLMs
+
+[Week 3: Prompting and Bias](/week3)
+- Prompt Engineering
+- Marked Personas
+
+[Week 4: Capabilities of LLMs](/week4)
+- LLM Capabilities
+- Medical Applications of LLMs
+
+[Week 5: Hallucination](/week5)
+- Hallucination Risks
+- Potential Solutions
+
+Week 6: Visit from [Anton Korinek](https://www.korinek.com/)
+
+[Week 7: Generative Adversarial Networks and DeepFakes](/week7)
+- GANs and DeepFakes
+- Creation and Detection of DeepFake Videos
+
+[Week 8: Machine Translation](/week8)
+- History of Machine Translation
+- Neural Machine Translation
+
+[Week 9: Interpretability](/week9)
+- Introduction to Interpretability
+- Mechanistic Interpretability
+
+[Week 10: Data for Training](/week10)
+- Data Selection for Fine-tuning LLMs
+- Detecting Pretraining Data from Large Language Models
+- Impact of Data on Large Language Models
+- The Curse of Recursion: Training on Generated Data Makes Models Forget
+
+[Week 11: Watermarking](/week11)
+- Watermarking LLM Outputs
+- Watermarking Diffusion Models
+
+[Week 12: LLM Agents](/week12)
+- LLM Agents
+- Tools and Planning
+
+[Week 13: Regulating Dangerous Technologies](/week13)
+- Analogies from other technologies for regulating AI
+
+[Week 14a: Multimodal Models](/week14a)  
+[Week 14b: Ethical AI](/week14b)
+
+
+