pavnilschanda@lemmy.world to Technology@lemmy.worldEnglish · 1 year agoLLMs are surprisingly great at compressing images and audio, DeepMind researchers findventurebeat.comexternal-linkmessage-square8fedilinkarrow-up193cross-posted to: aicompanions@lemmy.worldtechnology@lemmy.mltech@kbin.social
arrow-up193external-linkLLMs are surprisingly great at compressing images and audio, DeepMind researchers findventurebeat.compavnilschanda@lemmy.world to Technology@lemmy.worldEnglish · 1 year agomessage-square8fedilinkcross-posted to: aicompanions@lemmy.worldtechnology@lemmy.mltech@kbin.social
minus-squareTibert@compuverse.uklinkfedilinkEnglisharrow-up12·1 year agoWell from the article a dataset is required, but not always the heavier one. Tho it doesn’t solve the speed issue, where the llm will take a lot more time to do the compression. gzip can compress 1GB of text in less than a minute on a CPU, an LLM with 3.2 million parameters requires an hour to compress
minus-squarerubikcuber@programming.devlinkfedilinkEnglisharrow-up1·1 year agoI imagine that the compression is linked to the dataset, so if you update or retrain then you maybe lose access to the compressed data.
Well from the article a dataset is required, but not always the heavier one.
Tho it doesn’t solve the speed issue, where the llm will take a lot more time to do the compression.
I imagine that the compression is linked to the dataset, so if you update or retrain then you maybe lose access to the compressed data.