10 ms·

Intel AI open-sources library for deep learning-driven NLP

183 points by rcarndrums 8y ago

jl2718 8y ago
Link to repo?
- Jorslu 8y ago
  https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect It's not linked directly in the article but the article does mention the name of the software is "nlp-architect"
christophclarke 8y ago
GitHub repos here: https://github.com/NervanaSystems https://github.com/NervanaSystems
s4chin 8y ago
GitHub link - https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect
syllogism 8y ago
Looking forward to seeing the evaluation numbers! I'm mostly curious about how their NER and parser compare against what I've implemented for https://spaCy.io https://spaCy.io . I've tried the architectures they're using, and I've found they need very wide (and therefore slow) hidden layers to get competitive accuracy. I'm sure they have some evaluations, right? I mean you can't really develop these things without running experiments...
- spdustin 8y ago
  Well, the NLP Architect mentioned (https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect) uses Spacy, so... :)
  - syllogism 8y ago
    Well, that's what makes me curious! They have a class that runs the BIST parser (by Kilperwasser and Goldberg) using spaCy to pre-process for tokenization, sentence boundard detection and POS tags. Now, spaCy by default uses the parser to add sentence boundaries...So you've already got a parse right there. So, is their BIST parser more accurate than spaCy's parser? I'm getting similar (but slightly higher) WSJ accuracies to what Eli and Yoav reported in their paper, so I'd be surprised if they're doing so much better?
- iloveluce 8y ago
  Also it seems like their reported NER is just serving up the spaCy NER. “spacy_ner service which provides Spacy NER annotations.” [0]http://nlp_architect.nervanasys.com/service.html http://nlp_architect.nervanasys.com/service.html
  - deleted 8y ago
    [deleted]
- JPKab 8y ago
  Love Spacy, thanks for working on it. This is a giant corporation getting academics to build software in a lab. I hope it's good, but I've usually seen it doesn't end up being much.
dmichulke 8y ago
That title will make someone a proud winner of bingo.
siscia 8y ago
A while ago there was an article about creating a "wasteland" of unprofittability around your core business so to become the monopolist and extract the highest margin out of the industry. The position of Intel/Nvidia is then quite simple, they will open source any model, dataset, toolkit, library, etc that makes use of their hardware. Training new AI will become simpler and simpler and they will extract high margin from selling the hardware. What about Google instead? They have the data and the engineering knowledge to make complex AI works, however it seems quite unlikely that they will be able to drive the price of AI hardware down. Moreover they are charging quite a lot for the use of their custom TPU. From this analysis it seems like Google is bound to fail in the long term in the AI race. Am I wrong? Why?
- bluGill 8y ago
  Google has a lot of data, which might be enough for them: anyone who can use google data should get better results because of that data. Intel is taking a risk because what they release for free can also run on ARM and AMD. Is either significant? Ask me in 30 years...
  - sharemywin 8y ago
    The problem is for google, they have a lot of data but very few use cases that are big enough for all that data. driving cars, but driverless car services will be slow to take hold and I'm not sure it's winner take all. To me there's not much difference between is it safe and is it the safest. And with a car buying cycles in multiple years and regulations slow to catch up they might not leap ahead enough. And it's not like netflix and amazon service where it's cheap enough you just use both.
    - thfuran 8y ago
      There may not be a lot of difference between "very safe" and "most safe", but if they have enough of an advantage to get to "safe enough" before anyone else, that's a big deal.
      - 8y ago
make3 8y ago
so just another deep learning wrapper, or does it do anything significant not already done by 10 other more established libs?
sanxiyn 8y ago
The more interesting announcement is that Intel Nervana, already postponed multiple times, is again postponed to "late 2019". One theory is that Intel Nervana outperformed Nvidia Pascal, but didn't outperform Nvidia Volta, so it couldn't be released.
regnarg 8y ago
An AI decided to open source something? Hmm... Perhaps it's trying to use humans to further advance itself...

183 points by rcarndrums 8y ago

jl2718 8y ago

Link to repo?

Jorslu 8y ago
https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect It's not linked directly in the article but the article does mention the name of the software is "nlp-architect"

christophclarke 8y ago

GitHub repos here: https://github.com/NervanaSystems https://github.com/NervanaSystems

s4chin 8y ago

GitHub link - https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect

syllogism 8y ago

Looking forward to seeing the evaluation numbers! I'm mostly curious about how their NER and parser compare against what I've implemented for https://spaCy.io https://spaCy.io . I've tried the architectures they're using, and I've found they need very wide (and therefore slow) hidden layers to get competitive accuracy. I'm sure they have some evaluations, right? I mean you can't really develop these things without running experiments...

spdustin 8y ago
Well, the NLP Architect mentioned (https://github.com/NervanaSystems/nlp-architect https://github.com/NervanaSystems/nlp-architect) uses Spacy, so... :)
- syllogism 8y ago
  Well, that's what makes me curious! They have a class that runs the BIST parser (by Kilperwasser and Goldberg) using spaCy to pre-process for tokenization, sentence boundard detection and POS tags. Now, spaCy by default uses the parser to add sentence boundaries...So you've already got a parse right there. So, is their BIST parser more accurate than spaCy's parser? I'm getting similar (but slightly higher) WSJ accuracies to what Eli and Yoav reported in their paper, so I'd be surprised if they're doing so much better?
iloveluce 8y ago
Also it seems like their reported NER is just serving up the spaCy NER. “spacy_ner service which provides Spacy NER annotations.” [0]http://nlp_architect.nervanasys.com/service.html http://nlp_architect.nervanasys.com/service.html
- deleted 8y ago
  [deleted]
JPKab 8y ago
Love Spacy, thanks for working on it. This is a giant corporation getting academics to build software in a lab. I hope it's good, but I've usually seen it doesn't end up being much.

dmichulke 8y ago

That title will make someone a proud winner of bingo.

siscia 8y ago

A while ago there was an article about creating a "wasteland" of unprofittability around your core business so to become the monopolist and extract the highest margin out of the industry. The position of Intel/Nvidia is then quite simple, they will open source any model, dataset, toolkit, library, etc that makes use of their hardware. Training new AI will become simpler and simpler and they will extract high margin from selling the hardware. What about Google instead? They have the data and the engineering knowledge to make complex AI works, however it seems quite unlikely that they will be able to drive the price of AI hardware down. Moreover they are charging quite a lot for the use of their custom TPU. From this analysis it seems like Google is bound to fail in the long term in the AI race. Am I wrong? Why?

bluGill 8y ago
Google has a lot of data, which might be enough for them: anyone who can use google data should get better results because of that data. Intel is taking a risk because what they release for free can also run on ARM and AMD. Is either significant? Ask me in 30 years...
- sharemywin 8y ago
  The problem is for google, they have a lot of data but very few use cases that are big enough for all that data. driving cars, but driverless car services will be slow to take hold and I'm not sure it's winner take all. To me there's not much difference between is it safe and is it the safest. And with a car buying cycles in multiple years and regulations slow to catch up they might not leap ahead enough. And it's not like netflix and amazon service where it's cheap enough you just use both.
  - thfuran 8y ago
    There may not be a lot of difference between "very safe" and "most safe", but if they have enough of an advantage to get to "safe enough" before anyone else, that's a big deal.
    - 8y ago

make3 8y ago

so just another deep learning wrapper, or does it do anything significant not already done by 10 other more established libs?

sanxiyn 8y ago

The more interesting announcement is that Intel Nervana, already postponed multiple times, is again postponed to "late 2019". One theory is that Intel Nervana outperformed Nvidia Pascal, but didn't outperform Nvidia Volta, so it couldn't be released.

regnarg 8y ago

An AI decided to open source something? Hmm... Perhaps it's trying to use humans to further advance itself...