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>They certainly aren't capable of doing magic tricks like writing an app for you. It's the money-men that need to realize it. Practitioners know that it's sim

>They certainly aren't capable of doing magic tricks like writing an app for you. It's the money-men that need to realize it. Practitioners know that it's simply rebranded statistical methods. The usage is exactly the same. That said, some of the things these guys offer are useful; but branding it as "AI" is another story. By the way, is SoftBank going to implode, or what?

EGreg 7y ago
Softbank implode? Why?
- sgarman 7y ago
  Presumably the OP is referring to the insane amount of money Softbank has invested in the AI space.
- navigatesol 7y ago
  Because they are a massive fund throwing money into every half-baked idea coming out of Silicon Valley? https://www.zdnet.com/article/softbank-group-looking-to-ride-ai-unicorns-into-the-future/ https://www.zdnet.com/article/softbank-group-looking-to-ride... That image was copped form an investor presentation. How can anyone take that seriously?
MiroF 7y ago
I get the backlash against the hype, but to suggest that DL is simply "rebranded statistical methods" is just wrong. Yes, backprop existed before the recent explosion, that doesn't mean they're haven't been major leaps forward.
- 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 ago
    I 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.
- navigatesol 7y ago
  >Yes, backprop existed before the recent explosion, that doesn't mean they're haven't been major leaps forward. I didn't mean to imply that things were not advancing, only that what we claim is "AI" are processes we've been doing in statistics forever. But, yes, of course the tools and techniques improve.

EGreg 7y ago

Softbank implode? Why?

sgarman 7y ago
Presumably the OP is referring to the insane amount of money Softbank has invested in the AI space.
navigatesol 7y ago
Because they are a massive fund throwing money into every half-baked idea coming out of Silicon Valley? https://www.zdnet.com/article/softbank-group-looking-to-ride-ai-unicorns-into-the-future/ https://www.zdnet.com/article/softbank-group-looking-to-ride... That image was copped form an investor presentation. How can anyone take that seriously?

MiroF 7y ago

I get the backlash against the hype, but to suggest that DL is simply "rebranded statistical methods" is just wrong. Yes, backprop existed before the recent explosion, that doesn't mean they're haven't been major leaps forward.

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 ago
  I 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.
navigatesol 7y ago
>Yes, backprop existed before the recent explosion, that doesn't mean they're haven't been major leaps forward. I didn't mean to imply that things were not advancing, only that what we claim is "AI" are processes we've been doing in statistics forever. But, yes, of course the tools and techniques improve.