3 ms·

Sounds like despite their best efforts, NLP + full automation still has a long way to go. Unless they didn't get the resources they need to push it over the edg

by otp124 9y ago

Sounds like despite their best efforts, NLP + full automation still has a long way to go. Unless they didn't get the resources they need to push it over the edge? > That’s because most of the tasks fulfilled by M required people. > One source familiar with the program estimates M never surpassed 30 percent automation. Last spring, M’s leaders admitted the problems they were trying to solve were more difficult than they’d initially realized. > But as it became clear that M would always require a sizable workforce of expensive humans, the idea of expanding the service to a broader audience became less viable.

bronco21016 9y ago
The scope was just way too large. Think about it. You could ask M for anything. How many services do you use or pull data from on a day to day basis? Now how many of them have an API? Until nearly everything has a publicly accessible API I don’t see how something like M could ever happen without extensive human interaction. I’ve been giving this a lot of thought lately. I pull information from a few intranet sites routinely for managing travel for my job. It’s almost exclusively online and because of the scattered sites it can be annoying to manage at times. It’s perfect for automation and an AI assistant but without any kind of programmable interface how would an AI assistant ever work with the sites? I think Alexa and Google Assistant ultimately have the right idea, privacy issues aside. Start with a small enough scope and attract so many users that eventually services are compelled to support the devices. Over time the scope covers almost everything.
- ertand 9y ago
  I agree with this. It's a matter of scope and therefore a product problem. What can be done using NLP today is not a secret and I'm sure Facebook was already aware of the shortcomings. They could have reduced to scope to a more tractable problem, but they chose to cover everything that a consumer might want. I think there are a lot of good use cases that can be automated today.
- zjaffee 9y ago
  As someone who had access to M, initially my friends and I mostly just asked it to do all kinds of obscure things, which at scale would be very difficult (and I imagine most users would enjoy actually using it for as well for the sake of entertainment). We asked that it drew pictures of us, and tons of other queries around memes, ect. Outside of that the only other use case was having it remind me to wish friends a happy birthday when they otherwise didn't list it on facebook.
shubb 9y ago
The secret sauce aspect here is a bit of a worry. I wonder how many other products are secretly hand cranked. When you talk to Alexa, and the algorithm can't tell what you are saying, is there a guy in a call centre somewhere typing up what you are saying? Either to service your request or to provide a dataset of transcribed tricky samples? Alexa is bad enough, the idea that a human really is listening to me in my home is somehow worse.

by otp124 9y ago

bronco21016 9y ago

The scope was just way too large. Think about it. You could ask M for anything. How many services do you use or pull data from on a day to day basis? Now how many of them have an API? Until nearly everything has a publicly accessible API I don’t see how something like M could ever happen without extensive human interaction. I’ve been giving this a lot of thought lately. I pull information from a few intranet sites routinely for managing travel for my job. It’s almost exclusively online and because of the scattered sites it can be annoying to manage at times. It’s perfect for automation and an AI assistant but without any kind of programmable interface how would an AI assistant ever work with the sites? I think Alexa and Google Assistant ultimately have the right idea, privacy issues aside. Start with a small enough scope and attract so many users that eventually services are compelled to support the devices. Over time the scope covers almost everything.

ertand 9y ago
I agree with this. It's a matter of scope and therefore a product problem. What can be done using NLP today is not a secret and I'm sure Facebook was already aware of the shortcomings. They could have reduced to scope to a more tractable problem, but they chose to cover everything that a consumer might want. I think there are a lot of good use cases that can be automated today.
zjaffee 9y ago
As someone who had access to M, initially my friends and I mostly just asked it to do all kinds of obscure things, which at scale would be very difficult (and I imagine most users would enjoy actually using it for as well for the sake of entertainment). We asked that it drew pictures of us, and tons of other queries around memes, ect. Outside of that the only other use case was having it remind me to wish friends a happy birthday when they otherwise didn't list it on facebook.

shubb 9y ago

The secret sauce aspect here is a bit of a worry. I wonder how many other products are secretly hand cranked. When you talk to Alexa, and the algorithm can't tell what you are saying, is there a guy in a call centre somewhere typing up what you are saying? Either to service your request or to provide a dataset of transcribed tricky samples? Alexa is bad enough, the idea that a human really is listening to me in my home is somehow worse.