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I agree that we should remain skeptical, however, one important distinction between this and ghost stories is this is already fully technically possible. All th

I agree that we should remain skeptical, however, one important distinction between this and ghost stories is this is already fully technically possible. All that's needed is the will, the raw processing power, and the battery life to support it. No one could ever create a proof of concept for ghosts.

macawfish 9y ago
This comment is an argument that it's possible, not a claim that it's happening. It'd be much, much easier for apps like FB messenger to transmit sparse samples of low bitrate audio to a server for processing there. 1 hr/day @ 8kbps ~ 110 MB/month. As a matter of fact, with "deep learning" and whatall, it doesn't seem like the audio would even need to be intelligible to human ears for it to still be useful in some marketing algorithms or to generate guesses of interests correlating to the audio. Those interests might be presented as an ad, search suggestion, etc. Why would google use something like this for search recommendations? Because it's training data, that's why! What I'm arguing is that even though conventional "speech recognition" is processor intensive and unlikely happening on a mobile client side, it's just not that far-fetched that small snips of low bitrate conversation data might be used to tune marketing prediction models on the server-side. In training general purpose models, huge amounts of data could be generated by only a little bit of data/user. Where would this sort of thing cross a privacy line? I'm not sure. Personally, it kinda creeps me out regardless. Seriously, listen to these 8kbps opus samples: http://www.opus-codec.org/examples/ http://www.opus-codec.org/examples/ . If they're intelligible to human ears, I can't imagine what some clever learning algorithms could do with that and much much less. Here's a random anecdote about how much data FB messenger can use: https://www.reddit.com/r/androidapps/comments/49yhlh/facebook_messenger_background_data_usage_4gb_in_a/ https://www.reddit.com/r/androidapps/comments/49yhlh/faceboo...
IanCal 9y ago
Replace ghost stories with the creepy house at the end of that old road having an old woman in who eats children if they try and get their ball back, and turns them into puppets making the next victim watch the show, then. And it's totally happening because I heard a crunch one time that must have been bones. The fact that it's possible to eat a child or make a puppet does little to make this kind of thing much more realistic. The much simpler answer is that you are more predictable than you think, and likely more influenced by things Google can watch (clicks, ads) than you think. You also don't spot when it doesn't recommend something so accurate so it could even just be chance (or at least doesn't mean they're good at it)

macawfish 9y ago

This comment is an argument that it's possible, not a claim that it's happening. It'd be much, much easier for apps like FB messenger to transmit sparse samples of low bitrate audio to a server for processing there. 1 hr/day @ 8kbps ~ 110 MB/month. As a matter of fact, with "deep learning" and whatall, it doesn't seem like the audio would even need to be intelligible to human ears for it to still be useful in some marketing algorithms or to generate guesses of interests correlating to the audio. Those interests might be presented as an ad, search suggestion, etc. Why would google use something like this for search recommendations? Because it's training data, that's why! What I'm arguing is that even though conventional "speech recognition" is processor intensive and unlikely happening on a mobile client side, it's just not that far-fetched that small snips of low bitrate conversation data might be used to tune marketing prediction models on the server-side. In training general purpose models, huge amounts of data could be generated by only a little bit of data/user. Where would this sort of thing cross a privacy line? I'm not sure. Personally, it kinda creeps me out regardless. Seriously, listen to these 8kbps opus samples: http://www.opus-codec.org/examples/ http://www.opus-codec.org/examples/ . If they're intelligible to human ears, I can't imagine what some clever learning algorithms could do with that and much much less. Here's a random anecdote about how much data FB messenger can use: https://www.reddit.com/r/androidapps/comments/49yhlh/facebook_messenger_background_data_usage_4gb_in_a/ https://www.reddit.com/r/androidapps/comments/49yhlh/faceboo...

IanCal 9y ago

Replace ghost stories with the creepy house at the end of that old road having an old woman in who eats children if they try and get their ball back, and turns them into puppets making the next victim watch the show, then. And it's totally happening because I heard a crunch one time that must have been bones. The fact that it's possible to eat a child or make a puppet does little to make this kind of thing much more realistic. The much simpler answer is that you are more predictable than you think, and likely more influenced by things Google can watch (clicks, ads) than you think. You also don't spot when it doesn't recommend something so accurate so it could even just be chance (or at least doesn't mean they're good at it)