Add sections on LLM ecosystem continuation and Nous Research in index.md and...

Add sections on LLM ecosystem continuation and Nous Research in index.md and index.html, improving content structure and clarity

index.md

@@ -131,10 +131,16 @@ date: December 4th, 2024
 - Mistral is a close second - also no training data
 - Google is catching up FAST on closed models (and leaving open behind)
 - AllenAI is catching up and it's open
+
+---
+
+# The LLM ecosystem (cont)
+
 - Microsoft has tiny, bad ones (but I wouldn't bet against them)
 - Apple is going their own way + using ChatGPT
 - Twitter/X has Grok-2 for paying customers, Grok-1 is enormous and "old" (from march)
 - Anthropic is receiving billions from Amazon but Claude is completely closed
+- Amazon released its "Nova" models yesterday. 100% closed, interesting tiering (similar to blablador)
 
 ---
 
@@ -164,7 +170,7 @@ date: December 4th, 2024
 
 ---
 
-# Open Source?
+## Open Source?
 
 - Very few models are really open source
 - Most are "open source" in the sense that you can download the weights
@@ -172,7 +178,7 @@ date: December 4th, 2024
 
 ---
 
-# Open Source
+## Open Source
 
 - German academia: [OpenGPT-X](https://opengpt-x.de/en/)
     - Trained in Jülich and Dresden
@@ -196,6 +202,16 @@ date: December 4th, 2024
     - They claim overall compute utilization of 83% across continents and 96% when training only in the USA
     - Fully open
 
+---
+
+# Nous Research
+
+- Training live, on the interent
+- Previous models were Llama finetuned on synthetic data
+
+![](images/nous-distro.png){width=500px}
+
+
 --- 
 
 # Non-transformer architectures

public/index.html

@@ -392,6 +392,11 @@ data</li>
 <li class="fragment">Google is catching up FAST on closed models (and
 leaving open behind)</li>
 <li class="fragment">AllenAI is catching up and it’s open</li>
+</ul>
+</section>
+<section id="the-llm-ecosystem-cont" class="slide level1">
+<h1>The LLM ecosystem (cont)</h1>
+<ul>
 <li class="fragment">Microsoft has tiny, bad ones (but I wouldn’t bet
 against them)</li>
 <li class="fragment">Apple is going their own way + using ChatGPT</li>
@@ -399,6 +404,8 @@ against them)</li>
 is enormous and “old” (from march)</li>
 <li class="fragment">Anthropic is receiving billions from Amazon but
 Claude is completely closed</li>
+<li class="fragment">Amazon released its “Nova” models yesterday. 100%
+closed, interesting tiering (similar to blablador)</li>
 </ul>
 </section>
 <section id="the-llm-ecosystem-1" class="slide level1">
@@ -433,8 +440,9 @@ href="https://lmarena.ai">https://lmarena.ai</a></li>
 
 <p><img data-src="images/llm-leaderboard-2024-11.png" /></p>
 </section>
-<section id="open-source" class="slide level1">
-<h1>Open Source?</h1>
+<section class="slide level1">
+
+<h2 id="open-source">Open Source?</h2>
 <ul>
 <li class="fragment">Very few models are really open source</li>
 <li class="fragment">Most are “open source” in the sense that you can
@@ -442,8 +450,9 @@ download the weights</li>
 <li class="fragment">Either the code isn’t available, or the data</li>
 </ul>
 </section>
-<section id="open-source-1" class="slide level1">
-<h1>Open Source</h1>
+<section class="slide level1">
+
+<h2 id="open-source-1">Open Source</h2>
 <ul>
 <li class="fragment">German academia: <a
 href="https://opengpt-x.de/en/">OpenGPT-X</a>
@@ -486,6 +495,15 @@ across continents and 96% when training only in the USA</li>
 </ul></li>
 </ul>
 </section>
+<section id="nous-research" class="slide level1">
+<h1>Nous Research</h1>
+<ul>
+<li class="fragment">Training live, on the interent</li>
+<li class="fragment">Previous models were Llama finetuned on synthetic
+data</li>
+</ul>
+<p><img data-src="images/nous-distro.png" width="500" /></p>
+</section>
 <section id="non-transformer-architectures" class="slide level1">
 <h1>Non-transformer architectures</h1>
 <ul>