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      <title>Presentation: From S3 to GPU in One Copy: Rethinking Data Loading for ML Training</title>
      <link>https://www.infoq.com/presentations/vortex-columnar-file-format-gpu-streaming/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Streaming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/vortex-columnar-file-format-gpu-streaming/en/mediumimage/onur-satici-medium-1787813397611.jpeg"/&gt;&lt;p&gt;Onur Satici explains how Vortex, an open-source columnar file format under the Linux Foundation, revolutionizes high-throughput data loading. He details how cascading lightweight encodings, layout-based segment pruning, and zero-copy memory pipelines eliminate CPU/NVMe bottlenecks to stream S3 data straight to GPUs at speeds up to 60 Gbps without requiring upfront data reprocessing.&lt;/p&gt; &lt;i&gt;By Onur Satici&lt;/i&gt;</description>
      <category>GPU</category>
      <category>Data Lake</category>
      <category>Performance</category>
      <category>Data Pipelines</category>
      <category>Rust</category>
      <category>Architecture</category>
      <category>CUDA</category>
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      <category>Streaming</category>
      <category>QCon London 2026</category>
      <category>Columnar Databases</category>
      <category>S3</category>
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      <pubDate>Fri, 04 Sep 2026 11:00:00 GMT</pubDate>
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      <dc:creator>Onur Satici</dc:creator>
      <dc:date>2026-09-04T11:00:00Z</dc:date>
      <dc:identifier>/presentations/vortex-columnar-file-format-gpu-streaming/en</dc:identifier>
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    <item>
      <title>OpenAI Details GPT-Live’s Architecture for Continuous Stateful Voice Interaction</title>
      <link>https://www.infoq.com/news/2026/09/openai-gpt-live/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Streaming</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/openai-gpt-live/en/headerimage/OpenAI-gpt-live-system-architecture-header-1788176199388.jpeg"/&gt;&lt;p&gt;OpenAI recently published an engineering account of GPT-Live. It described how they designed the system to maintain continuous voice interaction while separating latency-sensitive media processing from broader application work. The live path contains the media pipeline and inference loop, while delegation, tool use, persistence, and other application logic run behind an asynchronous RPC boundary.&lt;/p&gt; &lt;i&gt;By Eran Stiller&lt;/i&gt;</description>
      <category>RPC</category>
      <category>OpenAI</category>
      <category>Streaming</category>
      <category>Voice-enabled UI</category>
      <category>WebRTC</category>
      <category>ChatGPT</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 02 Sep 2026 12:20:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/openai-gpt-live/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Streaming</guid>
      <dc:creator>Eran Stiller</dc:creator>
      <dc:date>2026-09-02T12:20:00Z</dc:date>
      <dc:identifier>/news/2026/09/openai-gpt-live/en</dc:identifier>
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