4 ms·

Yes, i felt cheated when i read it was about training 1/10th of ImageNet on a SVM. I guess IBM are desparate not to be left behind in the race for distributed d

Yes, i felt cheated when i read it was about training 1/10th of ImageNet on a SVM. I guess IBM are desparate not to be left behind in the race for distributed deep learning platforms.

pdeburen 9y ago
Yeah they get you really hyped up first and drop the bomb at the end. Still quite impressive speedup, would be better though to show it on a benchmark where SVM's are used in practice
carlmr 9y ago
Looking at the normal stuff coming out of IBM they're not associated with good software in my mind. So the more outrageous their claim, the less I believe them. They need to earn a reputation first.
- hueving 9y ago
  That's like judging all of Google based on the quality of one product. With 10x as many employees as Google and a very loose organization, expecting any kind of reputation is folly. A product from an IBM consultant is about as related to a product from IBM Watson as is a product from Microsoft being related to a product from Apple.
- kayoone 9y ago
  IBM has 400k employees and god knows how many subsidiaries and divisions, do you really think you can paint them all with one brush because of some negative experience you had with one of their products ?
  - carlmr 9y ago
    Not one, we have multiple IBM software products in my company, and they're all consistently the most terrible software you can imagine making. Sure they might have some divisions that do better, but I have yet to see them.
samfriedman 9y ago
To be honest, I'd readily cheer any groups working on traditional machine learning advancements despite all the current hype for neural methods.
- madenine 9y ago
  I'll second that. For all the attention DL/ANNs get... there's still a lot of legwork going on out there using linear models, basic trees, etc. IIRC this years kaggle survey ranked Logistic Regression as the #1 most used model by a long shot.
  - make3 9y ago
    neural networks are stacked logistic regressions. a lot of the deep learning research benefits logistic regression
- make3 9y ago
  you say that as if it's empty hype. but it's not: deep learning works, and works much better by any reasonable metric than SVMs in most problems that require high to very high model capacity.

Yes, i felt cheated when i read it was about training 1/10th of ImageNet on a SVM. I guess IBM are desparate not to be left behind in the race for distributed deep learning platforms.

pdeburen 9y ago

Yeah they get you really hyped up first and drop the bomb at the end. Still quite impressive speedup, would be better though to show it on a benchmark where SVM's are used in practice

carlmr 9y ago

Looking at the normal stuff coming out of IBM they're not associated with good software in my mind. So the more outrageous their claim, the less I believe them. They need to earn a reputation first.

hueving 9y ago
That's like judging all of Google based on the quality of one product. With 10x as many employees as Google and a very loose organization, expecting any kind of reputation is folly. A product from an IBM consultant is about as related to a product from IBM Watson as is a product from Microsoft being related to a product from Apple.
kayoone 9y ago
IBM has 400k employees and god knows how many subsidiaries and divisions, do you really think you can paint them all with one brush because of some negative experience you had with one of their products ?
- carlmr 9y ago
  Not one, we have multiple IBM software products in my company, and they're all consistently the most terrible software you can imagine making. Sure they might have some divisions that do better, but I have yet to see them.

samfriedman 9y ago

To be honest, I'd readily cheer any groups working on traditional machine learning advancements despite all the current hype for neural methods.

madenine 9y ago
I'll second that. For all the attention DL/ANNs get... there's still a lot of legwork going on out there using linear models, basic trees, etc. IIRC this years kaggle survey ranked Logistic Regression as the #1 most used model by a long shot.
- make3 9y ago
  neural networks are stacked logistic regressions. a lot of the deep learning research benefits logistic regression
make3 9y ago
you say that as if it's empty hype. but it's not: deep learning works, and works much better by any reasonable metric than SVMs in most problems that require high to very high model capacity.