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@@ -480,7 +480,7 @@
   
     <li class="md-nav__item">
       <a href="how-to-guides/use-service/" class="md-nav__link">
-        How to deploy a GreatAI service
+        How to perform prediction with GreatAI
       </a>
     </li>
   
@@ -874,12 +874,12 @@
 <h2 id="features">Features<a class="headerlink" href="#features" title="Permanent link">#</a></h2>
 <ul class="task-list">
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Save prediction traces of each prediction including arguments and model versions</li>
-<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Save feedback and merge it into a ground-truth database <em><img alt="➡" class="twemoji" src="https://twemoji.maxcdn.com/v/latest/svg/27a1.svg" title=":arrow_right:" /> quasi-shadow deployment</em></li>
+<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Save feedback and merge it into a ground-truth database</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Version and store models and data on shared infrastructure <em>(MongoDB GridFS, S3-compatible storage, shared local-volume)</em></li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Automatically scaffolded custom REST API (and OpenAPI schema) for easy integration</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Input validation</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Sensible cache-policy</li>
-<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Seamless support for both synchronous and <code>async</code> inference methods</li>
+<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Seamless support for both synchronous and asynchronous inference methods</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Easy integration with remote GreatAI instances</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Built-in parallelisation (with support for multiprocessing, async, and mixed modes) for batch processing</li>
 <li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Well-tested utilities for common NLP tasks (cleaning, language-tagging, sentence-segmentation, etc.)</li>
@@ -921,7 +921,7 @@
 </ol>
 <details class="note">
 <summary>Note</summary>
-<p>In practice, <code>greeter</code> could be an inference function of some AI/ML application. But it could also just wrap a black-box solution of some SaaS. Either ways, it is <a href="https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai" target="_blank">imperative to have continuos oversight</a> of the services you provide and data you process especially in the context of AI/ML applications.</p>
+<p>In practice, <code>greeter</code> could be an inference function of some AI/ML application. But it could also just wrap a black-box solution of some SaaS. Either way, it is <a href="https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai" target="_blank">imperative to have continuous oversight</a> of the services you provide and data you process especially in the context of AI/ML applications.</p>
 </details>
 <div class="highlight"><span class="filename">terminal</span><pre><span></span><code><a id="__codelineno-2-1" name="__codelineno-2-1" href="#__codelineno-2-1"></a>great-ai demo.py
 </code></pre></div>
@@ -944,7 +944,7 @@
 <li><strong>T</strong>rustworthy: deploy models that you and society can confidently trust</li>
 </ul>
 <h2 id="why-greatai">Why GreatAI?<a class="headerlink" href="#why-greatai" title="Permanent link">#</a></h2>
-<p>There are other, existing solutions aiming to facilitate this phase. <a href="https://aws.amazon.com/sagemaker" target="_blank">Amazon SageMaker</a> and <a href="https://www.seldon.io/solutions/open-source-projects/core" target="_blank">Seldon Core</a> provide the most comprehensive suite of features. If you have the opportunity use those, do that because they're great.</p>
+<p>There are other, existing solutions aiming to facilitate this phase. <a href="https://aws.amazon.com/sagemaker" target="_blank">Amazon SageMaker</a> and <a href="https://www.seldon.io/solutions/open-source-projects/core" target="_blank">Seldon Core</a> provide the most comprehensive suite of features. If you have the opportunity to use them, do that because they're great.</p>
 <p>However, research indicates that professionals rarely use them. This may be due to their inherent setup and operating complexity. <mark>GreatAI is designed to be as simple to use as possible.</mark> Its clear, high-level API and sensible default configuration makes it extremely easy to start using. Despite its relative simplicity over Seldon Core, it still implements many of the <a href="https://se-ml.github.io" target="_blank">SE4ML best-practices</a>, and thus, can meaningfully improve your deployment without requiring prohibitively large effort.</p>
 <div style="display: flex; justify-content: space-evenly; flex-wrap: wrap;">
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