improve desc of data

Author: MarkBruns

book/Manifesto.html

@@ -160,15 +160,15 @@ <h1 id="soil-quality-foundation-models-transforming-earths-living-skin"><a class
 <h2 id="specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models"><a class="header" href="#specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models">Specialized Foundation Models, The Case of Soil Quality Laboratory Foundation Models</a></h2>
 <p>Specialized foundation models for soil quality are artificial intelligence systems trained on vast [yet specific to soil quality] diverse geospatial and environmental datasets to analyze, predict, and monitor soil health with high accuracy. Unlike <a href="https://en.wikipedia.org/wiki/Foundation_model">general-purpose foundation models</a>, these <strong>specialized</strong> versions are based on higher quality training data and also more highly fine-tuned for the unique complexities of agricultural and environmental science, allowing for more precise and actionable insights.</p>
 <h3 id="how-specialized-foundation-models-work-for-soil-quality"><a class="header" href="#how-specialized-foundation-models-work-for-soil-quality">How specialized foundation models work for soil quality</a></h3>
-<p>These models leverage large-scale data and transfer learning to understand complex soil dynamics.</p>
+<p>These models leverage vastly-large-scale training data by providing rapid access to query or assess patterns found by intelligent system to assist in better understand complex soil dynamics than was ever possible before.</p>
 <ol>
 <li><strong>Data integration</strong>: They combine information from multiple sources, including:</li>
 </ol>
 <ul>
 <li>Satellite imagery (e.g., spectral data from MODIS and other NASA sources).</li>
-<li>Ground-based sensors.</li>
-<li>Drone data.</li>
-<li>Geological, hydrological, and climate datasets.</li>
+<li>Ground-based sensors, including human-gathered or human-adjusted survey observations.</li>
+<li>Data from field and/or fertigation equipment supplemented with targeted data from robots.</li>
+<li>Existing geological, hydrological, and climate datasets, both present and past.</li>
 </ul>
 <ol start="2">
 <li>

book/index.html

@@ -160,15 +160,15 @@ <h1 id="soil-quality-foundation-models-transforming-earths-living-skin"><a class
 <h2 id="specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models"><a class="header" href="#specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models">Specialized Foundation Models, The Case of Soil Quality Laboratory Foundation Models</a></h2>
 <p>Specialized foundation models for soil quality are artificial intelligence systems trained on vast [yet specific to soil quality] diverse geospatial and environmental datasets to analyze, predict, and monitor soil health with high accuracy. Unlike <a href="https://en.wikipedia.org/wiki/Foundation_model">general-purpose foundation models</a>, these <strong>specialized</strong> versions are based on higher quality training data and also more highly fine-tuned for the unique complexities of agricultural and environmental science, allowing for more precise and actionable insights.</p>
 <h3 id="how-specialized-foundation-models-work-for-soil-quality"><a class="header" href="#how-specialized-foundation-models-work-for-soil-quality">How specialized foundation models work for soil quality</a></h3>
-<p>These models leverage large-scale data and transfer learning to understand complex soil dynamics.</p>
+<p>These models leverage vastly-large-scale training data by providing rapid access to query or assess patterns found by intelligent system to assist in better understand complex soil dynamics than was ever possible before.</p>
 <ol>
 <li><strong>Data integration</strong>: They combine information from multiple sources, including:</li>
 </ol>
 <ul>
 <li>Satellite imagery (e.g., spectral data from MODIS and other NASA sources).</li>
-<li>Ground-based sensors.</li>
-<li>Drone data.</li>
-<li>Geological, hydrological, and climate datasets.</li>
+<li>Ground-based sensors, including human-gathered or human-adjusted survey observations.</li>
+<li>Data from field and/or fertigation equipment supplemented with targeted data from robots.</li>
+<li>Existing geological, hydrological, and climate datasets, both present and past.</li>
 </ul>
 <ol start="2">
 <li>

book/print.html

@@ -161,15 +161,15 @@ <h1 id="soil-quality-foundation-models-transforming-earths-living-skin"><a class
 <h2 id="specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models"><a class="header" href="#specialized-foundation-models-the-case-of-soil-quality-laboratory-foundation-models">Specialized Foundation Models, The Case of Soil Quality Laboratory Foundation Models</a></h2>
 <p>Specialized foundation models for soil quality are artificial intelligence systems trained on vast [yet specific to soil quality] diverse geospatial and environmental datasets to analyze, predict, and monitor soil health with high accuracy. Unlike <a href="https://en.wikipedia.org/wiki/Foundation_model">general-purpose foundation models</a>, these <strong>specialized</strong> versions are based on higher quality training data and also more highly fine-tuned for the unique complexities of agricultural and environmental science, allowing for more precise and actionable insights.</p>
 <h3 id="how-specialized-foundation-models-work-for-soil-quality"><a class="header" href="#how-specialized-foundation-models-work-for-soil-quality">How specialized foundation models work for soil quality</a></h3>
-<p>These models leverage large-scale data and transfer learning to understand complex soil dynamics.</p>
+<p>These models leverage vastly-large-scale training data by providing rapid access to query or assess patterns found by intelligent system to assist in better understand complex soil dynamics than was ever possible before.</p>
 <ol>
 <li><strong>Data integration</strong>: They combine information from multiple sources, including:</li>
 </ol>
 <ul>
 <li>Satellite imagery (e.g., spectral data from MODIS and other NASA sources).</li>
-<li>Ground-based sensors.</li>
-<li>Drone data.</li>
-<li>Geological, hydrological, and climate datasets.</li>
+<li>Ground-based sensors, including human-gathered or human-adjusted survey observations.</li>
+<li>Data from field and/or fertigation equipment supplemented with targeted data from robots.</li>
+<li>Existing geological, hydrological, and climate datasets, both present and past.</li>
 </ul>
 <ol start="2">
 <li>

book/searchindex.js

@@ -8,13 +8,13 @@ Specialized foundation models for soil quality are artificial intelligence syste
 
 ### How specialized foundation models work for soil quality
 
-These models leverage large-scale data and transfer learning to understand complex soil dynamics. 
+These models leverage vastly-large-scale training data by providing rapid access to query or assess patterns found by intelligent system to assist in better understand complex soil dynamics than was ever possible before. 
 
 1. **Data integration**: They combine information from multiple sources, including:
 * Satellite imagery (e.g., spectral data from MODIS and other NASA sources).
-* Ground-based sensors.
-* Drone data.
-* Geological, hydrological, and climate datasets. 
+* Ground-based sensors, including human-gathered or human-adjusted survey observations.
+* Data from field and/or fertigation equipment supplemented with targeted data from robots.
+* Existing geological, hydrological, and climate datasets, both present and past. 
 
 2. **Specialized training**: The models are pre-trained on this multi-modal data to learn universal representations of complex environmental patterns. For example, they can associate spectral patterns from satellite images with different soil properties.