The only gold I see in that gold rush is from acqui-hire.
Deep Learning Business Models
21–30 of 36 posts
Re: Deep Learning Business Models
#22Earlier quoted context omitted.
After watching 'Recent Developments in Deep Learning' by Geoff Hinton [1] a while ago I did come away believing that there does seem to be quite a bit of untapped potential in deep neural nets. Do you feel that talk is overly optimistic/misleading? Or just that you don't think there's that much money to be made with it? [1] https://www.youtube.com/watch?v=vShMxxqtDDs
I've also seen that talk. In many cases I think the advantages which may be had from deep learning are likely to be marginal - a few percent improvement over the next best algorithm. Multi-layer neural nets already existed for a couple of decades, and deep learning is really just a refinement on that, making the training process faster and more robust to overfitting.
Do you know of any other system that gets ~14% error rate on the IMAGENET dataset? The next best system as recent as 2012 was doing ~26% error. That is a pretty big gap, especially considering IMAGENET is a million image data set. (btw did not see the talk)
Re: Deep Learning Business Models
#23If you believe a few assumptions:
1. Machine learning will come to play a more important role in the future (not less)
2. Machine learning is a wide field with many areas of complexity and a wide variety of applications, many not yet discovered
3. Deep learning is an exciting area in machine learning research showing promising (state of the art?) results in several domains
Then I think a few conclusions follow:
1. New tools will address this market, both free and commercial.
2. Services will be a major part of this ecosystem (see history of databases, ERP, CRM) and those consultants both use and sell tools (applications)
3. Deep learning is interesting, quite possibly worth using, and changing rapidly. But it doesn't negate what came before it (or after).
So the answer here is all of the above models will be important, with the application of machine learning to everything really being the larger umbrella opportunity, and deep learning currently being an interesting avenue of research?
Re: Deep Learning Business Models
#24I didn't know there was a deep learning gold rush. Maybe this explains the crazy number of stars on my libdeep library on Github, while there being no comments or issues raised. Deep learning is not any sort of magic bullet. It may be marginally better than other machine learning methods in specific contexts, but I'm not convinced that there are going to be any deep learning tycoons or deep learning entrepreneurs (we…
About libdeep: Would be very useful if you had the man page inserted into the README. This way I can make a decision as to if I need this library without having to download/install.
Re: Deep Learning Business Models
#25If you believe a few assumptions: 1. Machine learning will come to play a more important role in the future (not less) 2. Machine learning is a wide field with many areas of complexity and a wide variety of applications, many not yet discovered 3. Deep learning is an exciting area in machine learning research showing promising (state of the art?) results in several domains Then I think a few conclusions follow: 1. Ne…
Does your company have customers?
Re: Deep Learning Business Models
#26I didn't know there was a deep learning gold rush. Maybe this explains the crazy number of stars on my libdeep library on Github, while there being no comments or issues raised. Deep learning is not any sort of magic bullet. It may be marginally better than other machine learning methods in specific contexts, but I'm not convinced that there are going to be any deep learning tycoons or deep learning entrepreneurs (we…
The fact that features can be learned means we could see the emergence of machine learning methods that could be used by anyone with a technical background, not just ML experts.
That would be a big deal IMHO.
Re: Deep Learning Business Models
#27If you believe a few assumptions: 1. Machine learning will come to play a more important role in the future (not less) 2. Machine learning is a wide field with many areas of complexity and a wide variety of applications, many not yet discovered 3. Deep learning is an exciting area in machine learning research showing promising (state of the art?) results in several domains Then I think a few conclusions follow: 1. Ne…
Does your company have customers?
Yes
Re: Deep Learning Business Models
#28"Deep learning requires a ton of tuning and tweaking, and getting good results is as much art as science." Funny when you think about it : Deep learning is supposed to avoid that ^^'
I think you're confusing deep learning with strong AI.
Re: Deep Learning Business Models
#29kaggle++
Re: Deep Learning Business Models
#30Earlier quoted context omitted.
I've also seen that talk. In many cases I think the advantages which may be had from deep learning are likely to be marginal - a few percent improvement over the next best algorithm. Multi-layer neural nets already existed for a couple of decades, and deep learning is really just a refinement on that, making the training process faster and more robust to overfitting.
Do you know of any other system that gets ~14% error rate on the IMAGENET dataset? The next best system as recent as 2012 was doing ~26% error. That is a pretty big gap, especially considering IMAGENET is a million image data set. (btw did not see the talk)
> especially considering IMAGENET is a million image data set
... and that human error rate is also > 0. Sometimes machine learning bests the humans.