<story><title>The man who killed Google Search?</title><url>https://www.wheresyoured.at/the-men-who-killed-google/</url></story><parent_chain><item><author>fuzztester</author><text>Same here with YouTube, assuming they use ML, which is likely.&lt;p&gt;They routinely give me brain-dead suggestions such as to watch a video I just watched today or yesterday, among other absurdities.</text></item><item><author>JohnFen</author><text>&amp;gt; where he argued against the other search leads that Google should use less machine-learning&lt;p&gt;This better echoes my personal experience with the decline of Google search than TFA: it seems to be connected to the increasing use of ML in that the more of it Google put in, the worse the results I got were.</text></item><item><author>gregw134</author><text>Ex-Google search engineer here (2019-2023). I know a lot of the veteran engineers were upset when Ben Gomes got shunted off. Probably the bigger change, from what I&amp;#x27;ve heard, was losing Amit Singhal who led Search until 2016. Amit fought against creeping complexity. There is a semi-famous internal document he wrote where he argued against the other search leads that Google should use less machine-learning, or at least contain it as much as possible, so that ranking stays debuggable and understandable by human search engineers. My impression is that since he left complexity exploded, with every team launching as many deep learning projects as they can (just like every other large tech company has).&lt;p&gt;The problem though, is the older systems had obvious problems, while the newer systems have hidden bugs and conceptual issues which often don&amp;#x27;t show up in the metrics, and which compound over time as more complexity is layered on. For example: I found an off by 1 error deep in a formula from an old launch that has been reordering top results for 15% of queries since 2015. I handed it off when I left but have no idea whether anyone actually fixed it or not.&lt;p&gt;I wrote up all of the search bugs I was aware of in an internal document called &amp;quot;second page navboost&amp;quot;, so if anyone working on search at Google reads this and needs a launch go check it out.</text></item></parent_chain><comment><author>998244353</author><text>For what it&amp;#x27;s worth, I do not remember a time when YouTube&amp;#x27;s suggestions or search results were good. Absurdities like that happened 10 and 15 years ago as well.&lt;p&gt;These days my biggest gripe is that they put unrelated ragebait or clickbait videos in search results that I very clearly did not search for - often about American politics.</text></comment>
<story><title>The man who killed Google Search?</title><url>https://www.wheresyoured.at/the-men-who-killed-google/</url></story><parent_chain><item><author>fuzztester</author><text>Same here with YouTube, assuming they use ML, which is likely.&lt;p&gt;They routinely give me brain-dead suggestions such as to watch a video I just watched today or yesterday, among other absurdities.</text></item><item><author>JohnFen</author><text>&amp;gt; where he argued against the other search leads that Google should use less machine-learning&lt;p&gt;This better echoes my personal experience with the decline of Google search than TFA: it seems to be connected to the increasing use of ML in that the more of it Google put in, the worse the results I got were.</text></item><item><author>gregw134</author><text>Ex-Google search engineer here (2019-2023). I know a lot of the veteran engineers were upset when Ben Gomes got shunted off. Probably the bigger change, from what I&amp;#x27;ve heard, was losing Amit Singhal who led Search until 2016. Amit fought against creeping complexity. There is a semi-famous internal document he wrote where he argued against the other search leads that Google should use less machine-learning, or at least contain it as much as possible, so that ranking stays debuggable and understandable by human search engineers. My impression is that since he left complexity exploded, with every team launching as many deep learning projects as they can (just like every other large tech company has).&lt;p&gt;The problem though, is the older systems had obvious problems, while the newer systems have hidden bugs and conceptual issues which often don&amp;#x27;t show up in the metrics, and which compound over time as more complexity is layered on. For example: I found an off by 1 error deep in a formula from an old launch that has been reordering top results for 15% of queries since 2015. I handed it off when I left but have no idea whether anyone actually fixed it or not.&lt;p&gt;I wrote up all of the search bugs I was aware of in an internal document called &amp;quot;second page navboost&amp;quot;, so if anyone working on search at Google reads this and needs a launch go check it out.</text></item></parent_chain><comment><author>gverrilla</author><text>YT Shorts recommendations are a joke.
I&amp;#x27;m an atheist and very rarely watch anything related to religion, and even so Shorts put me in 3 or 4 live prayers&amp;#x2F;scams (not sure) the last few months.</text></comment>