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The question is really whether those high salaries are achieving long-term payoffs. For certain things like image and audio processing, they've made some remark
by shaklee3 8y ago
The question is really whether those high salaries are achieving long-term payoffs. For certain things like image and audio processing, they've made some remarkable strides. However, many of those strides have to be remarkable to people outside the HN/AI community. For example, typing dog in Google photos and having it find pictures of your dog is great. However, when it misses a few and people notice that, they wonder why it's so bad. Almost as if Google should correctly identify 100% of them. Someone needs to sink the money into doing the grunt work of getting close to 100%, but the last few percent of improvement cost a lot of money. And to productize that to a user base of hundreds of millions of people is not cheap on the infrastructure, either.
- bitL 8y agoI think one of the hiring strategies is not having those very talented people outside doing damage to them, rather inside even if inefficient/underutilized. They just need to be better than their competition and frankly, looking this week at what Amazon is offering they can continue being in that mode for quite some time. General public more likely notices improvements in apps with immediate feedback like what Snapchat/Messenger is doing. There are already models surpassing human cognition in many tasks, maybe the inferencing costs aren't economical yet?
- glangdale 8y agoI remember people ascribing this hiring strategy to Microsoft (back in the day): hiring up all the researchers to ensure there never was another Microsoft.