They were using machine learning to try and figure out what people were buying. Machine learning has lots of errors until you train it. The “hundreds of workers” were training it by telling it what each thing was. E.g. it was creating training data for it to learn from.
The goal was to train ML enough so that humans were rarely necessary, obviously.
That’s their excuse but it is convenient for them that in order to train the AI the workers need to follow the exact same steps as what an AI would be doing if it was sufficiently trained. We can’t say as outsiders to what extent the actual work is assisted by AI. Seems likely that it is largely a manual process.
I understand the spirit, but that’s how it goes. You have somebody doing the work, as you want the ML to do it, and then feed the data. It’s the same when they get oncology scans that have been diagnosed by well paid doctors, somebody who knows does and the machine tries to replicate.
What very likely happened is that the failure rate platoed much higher than they expected, and all this time the goal was to lower it. Remember, it’s cheaper to have 0 people in India than 1, specially with AWS in mind.
Moreover, even if the accuracy was incredibly high, they would still need people reviewing. You have to review random events to ensure the model keeps performing well and to evaluate the ones with low confidence or suspicious.
Jesus christ these headlines mislead everything.
They were using machine learning to try and figure out what people were buying. Machine learning has lots of errors until you train it. The “hundreds of workers” were training it by telling it what each thing was. E.g. it was creating training data for it to learn from.
The goal was to train ML enough so that humans were rarely necessary, obviously.
That’s their excuse but it is convenient for them that in order to train the AI the workers need to follow the exact same steps as what an AI would be doing if it was sufficiently trained. We can’t say as outsiders to what extent the actual work is assisted by AI. Seems likely that it is largely a manual process.
I understand the spirit, but that’s how it goes. You have somebody doing the work, as you want the ML to do it, and then feed the data. It’s the same when they get oncology scans that have been diagnosed by well paid doctors, somebody who knows does and the machine tries to replicate.
What very likely happened is that the failure rate platoed much higher than they expected, and all this time the goal was to lower it. Remember, it’s cheaper to have 0 people in India than 1, specially with AWS in mind.
Moreover, even if the accuracy was incredibly high, they would still need people reviewing. You have to review random events to ensure the model keeps performing well and to evaluate the ones with low confidence or suspicious.
My goal is to build a fusion reactor.
I will hire Indian call center workers to add fuel to my diesel generator until the fusion is up and running.
This plan makes sense to certain people on the internet.
You could probably get lots of funding with this. I say go for it.