3 ms·
It's not that DL is simply "rebranded statistical methods", it's that the companies with names ending in "dot AI" are simply using "rebranded statistical metho
by tachyonbeam 7y ago
It's not that DL is simply "rebranded statistical methods", it's that the companies with names ending in "dot AI" are simply using "rebranded statistical methods". Lots of money is being poured into anything that calls itself "AI" right now, and a lot of people are starting to roll their eyes when they hear that term.
I work with DL researchers on a daily basis, and I feel like there have been a lot of cool developments, but much of it is not ready for prime time. I would really like to see a list of successful DL deployments in the wild, with some info about accuracy if possible.
- MiroF 7y agoI work in NLP and the industry has pretty much completely shifted to DL based approaches (ie. translation vendors pretty much only use neural engines now, language modeling and classification is very often neural as well now). There's definitely a lot that's not quite ready for prime time (reinforcement learning comes to mind as something that is particularly promising but not working really yet). > It's not that DL is simply "rebranded statistical methods", it's that the companies with names ending in "dot AI" are simply using "rebranded statistical methods". Lots of money is being poured into anything that calls itself "AI" right now, and a lot of people are starting to roll their eyes when they hear that term. This is definitely true - but I took it as a bit different from your original comment.