{"id":20536,"date":"2022-12-02T14:47:18","date_gmt":"2022-12-02T14:47:18","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/02\/google-frees-nifty-ml-image-compression-model-the-register\/"},"modified":"2022-12-02T14:47:18","modified_gmt":"2022-12-02T14:47:18","slug":"google-frees-nifty-ml-image-compression-model-the-register","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/02\/google-frees-nifty-ml-image-compression-model-the-register\/","title":{"rendered":"Google frees nifty ML image-compression model \u2022 The Register"},"content":{"rendered":"

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A new application of machine learning looks both clever and handy, as opposed to the more normal properties of being somewhere between privacy-, copyright-, or life-endangering. But before you get too excited, you can’t have it.<\/p>\n

The true cost of ML applications varies. Many are free to use, which means they endanger the paid income of someone somewhere. Speech recognition puts poor people in call centers<\/a> out of work. “AI” image generators<\/a> deprive creative artists of their income, and “AI” text generators<\/a> threaten writers \u2013 in those few jobs which survived the web destroying print journalism, anyway.<\/p>\n

Applying ML to image compression and decompression seems like a relatively safe use. Adding more smarts to image compression has felt like it was an inspired idea waiting for its moment ever since Michael Barnsley<\/a> invented fractal image compression<\/a> in 1987.<\/p>\n

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