<story><title>Three chips in and Google Tensor is on life support</title><url>https://www.notebookcheck.net/Three-chips-in-and-Google-Tensor-is-on-life-support.768438.0.html</url></story><parent_chain><item><author>silisili</author><text>99% of smartphone consumers don&amp;#x27;t care about &amp;#x27;ML performance&amp;#x27; as a primary concern.  People care how fast apps open, and battery life.  From the perspective, the tensor chips are pigs that nobody is excited about.</text></item><item><author>elromulous</author><text>In general I agree that the tensor hardware has been mostly a disappointment. I mean this more in general performance than in ML.&lt;p&gt;In ML I think the story is a little different. Hardware design&amp;#x2F;production pipelines are measured in years. The LLM &amp;quot;revolution&amp;quot; is relatively recent. For the Pixel8, I imagine some folks at Google had to make the really tough decision of whether to run weaker, smaller models on device, or run the giant LLM models in the cloud, giving &lt;i&gt;much&lt;/i&gt; better results, albeit slower (and with ofc the requirement for an Internet connection).</text></item></parent_chain><comment><author>senkora</author><text>iPhones have all sorts of little niceties that are directly enabled by good ML performance. For example, automatic OCR of text within images, even on websites. I think the facial recognition for grouping photos by person is also done locally by the ML chip.</text></comment>
<story><title>Three chips in and Google Tensor is on life support</title><url>https://www.notebookcheck.net/Three-chips-in-and-Google-Tensor-is-on-life-support.768438.0.html</url></story><parent_chain><item><author>silisili</author><text>99% of smartphone consumers don&amp;#x27;t care about &amp;#x27;ML performance&amp;#x27; as a primary concern.  People care how fast apps open, and battery life.  From the perspective, the tensor chips are pigs that nobody is excited about.</text></item><item><author>elromulous</author><text>In general I agree that the tensor hardware has been mostly a disappointment. I mean this more in general performance than in ML.&lt;p&gt;In ML I think the story is a little different. Hardware design&amp;#x2F;production pipelines are measured in years. The LLM &amp;quot;revolution&amp;quot; is relatively recent. For the Pixel8, I imagine some folks at Google had to make the really tough decision of whether to run weaker, smaller models on device, or run the giant LLM models in the cloud, giving &lt;i&gt;much&lt;/i&gt; better results, albeit slower (and with ofc the requirement for an Internet connection).</text></item></parent_chain><comment><author>matthewmacleod</author><text>That&amp;#x27;s a bit reductive. They also care if their apps work _well_ – if their pictures look nice, if their dictation is responsive, if their assistant understands queries, if OCR is accurate… which is all about &amp;quot;ML performance&amp;quot;.</text></comment>