Float16Array is now at ECMA Stage 3

- Add {{Float16Array}} Bikeshed custom definition
- Convert the related in-spec issue into a note
- Tweak the note wording

Author: anssiko

index.bs

@@ -61,6 +61,9 @@ urlPrefix: https://webidl.spec.whatwg.org/; spec: WEBIDL
     type: dfn
         text: underlying buffer; url: buffersource-underlying-buffer
         text: buffer byte length; url: buffersource-byte-length
+urlPrefix: https://tc39.es/proposal-float16array/; spec: float16array
+    type: interface
+        text: Float16Array; url: sec-float16array
 </pre>
 <pre class="biblio">
 {
@@ -3154,7 +3157,7 @@ console.log('Output value: ' + result.outputs.output);
         <td>{{Float32Array}}
     <tr>
         <td>{{MLOperandType/float16}}
-        <td><p class="issue">TC39 <a href="https://tc39.es/proposal-float16array/">`Float16Array`</a> is work in progress. Implementations can emulate this type by passing raw bits via {{Uint16Array}}. <a href="https://github.com/webmachinelearning/webnn/issues/373">[Issue webnn#373]</a></p>
+        <td>{{Float16Array}}
     <tr>
         <td>{{MLOperandType/int32}}
         <td>{{Int32Array}}
@@ -3169,6 +3172,8 @@ console.log('Output value: ' + result.outputs.output);
         <td>{{Uint8Array}}
 </table>
 
+<p class="note">{{Float16Array}} is at <a href="https://tc39.es/process-document/">ECMA Stage 3</a> signalling its design is finished. Implementers wanting to enable this type ahead native implementations can emulate the type by passing raw bits via {{Uint16Array}}. <a href="https://github.com/webmachinelearning/webnn/issues/373">[Issue webnn#373]</a></p>
+
 <h2 id="acknowledgements">Acknowledgements</h2>
 
 This specification follows the concepts of the Android Neural Networks API C