d","ofType","_context","xml","outerCache","nodeIndex","start","parent","useCache","diff","firstChild","lastChild","pseudo","args","setFilters","idx","matched","not","matcher","compile","unmatched","has","lang","elemLang","hash","location","root","focus","activeElement","err","safeActiveElement","hasFocus","href","tabIndex","enabled","checked","selected","selectedIndex","empty","nextSibling","header","button","_matchIndexes","lt","gt","nth","radio","checkbox","file","password","image","submit","r...

    are available in Linux x86, Windows x86, and Linux aarch64 packages.

    *   **Linux x86 packages:**
        *   oneDNN optimizations are *enabled by default* on CPUs with
            neural-network-focused hardware features such as AVX512_VNNI,
            AVX512_BF16, AMX, etc.
            ([Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html)
            and newer CPUs.)

d","ofType","_context","xml","outerCache","nodeIndex","start","parent","useCache","diff","firstChild","lastChild","pseudo","args","setFilters","idx","matched","not","matcher","compile","unmatched","has","lang","elemLang","hash","location","root","focus","activeElement","err","safeActiveElement","hasFocus","href","tabIndex","enabled","checked","selected","selectedIndex","empty","nextSibling","header","button","_matchIndexes","lt","gt","nth","radio","checkbox","file","password","image","submit","r...

  </mime-type>
  <mime-type type="application/illustrator+ps">
    <acronym>AI</acronym>
    <_comment>Adobe Illustrator Artwork -- the older postscript based AI files</_comment>
    <!-- we can do more specific versions by focusing on the integer in the regex below -->
    <tika:link>http://justsolve.archiveteam.org/wiki/Adobe_Illustrator_Artwork</tika:link>
    <magic priority="60">

### Cluster Lifecycle Stability and Usability Improvements

executing **your own code**, and particularly, **waiting for the network**. But you will probably still get some nice performance improvements just from the upgrade.

The focus of this release is **compatibility** with Pydantic v1 and v2, to make sure your current apps keep working. Later there will be more focus on refactors, correctness, code improvements, and then **performance** improvements. Some third-party early beta testers that ran benchmarks on the beta releases of FastAPI reported...