7 ms·

The way I see it, TensorFlow has already won, even if competing frameworks don't yet see it that way. New ideas and research breakthroughs will spread faster t

by cs702 10y ago

The way I see it, TensorFlow has already won, even if competing frameworks don't yet see it that way. New ideas and research breakthroughs will spread faster to the framework that has the most users and contributors, thereby attracting more users and contributors, in a feedback loop. Some of the other frameworks will continue to be used (for example, FaceBook's AI team is unlikely to back away from its commitment to Torch), but the TensorFlow ecosystem and its network effects appear to have reached 'escape velocity' in a winner-take-all space. New higher-level services and products will be built atop the framework most widely used by the most software developers, almost by definition. Expect a shakeout: https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.bzlyyk3ed https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.bzl... -- EDITS: Added the "new higher-level services and products" sentence.

astazangasta 10y ago
It's been less than a year, eh. A bit early to declare it has "already won"? There's decades of research ahead of us.
- AJ007 10y ago
  How many of those decades will be human driven?
  - astazangasta 10y ago
    Since no one even in concept has figured out how to give an AI motivations or goals other than ones specified by humans: all of them.
    - nurettin 10y ago
      Surely someone would have tried if "mind building" was in anyone's monetary interest.
      - Jtsummers 10y ago
        People have tried. No one's succeeded. Not every endeavor is a success.
        nurettin 10y ago
        Can you supply a list of monetary interest groups for building sentient minds?
  - dmreedy 10y ago
    Barring some Einstein/Shannon-level of momentary insight that catapults understanding of the nature of intelligence forward by orders of magnitude from where it is now, likely all of them. And entirely likely that it will be more than decades.
kartD 10y ago
It's a little early if you ask me, IMO you win once you make the first killer product that changes the market Eg: search, iPhone, self-driving cars etc
- ma2rten 10y ago
  Google wasn't the first search engine.
  - kartD 10y ago
    I said first killer (market defining and expanding product) product, iPhone wasn't the first smartphone either, but they pushed them from cool towards ubiquitous
    - ma2rten 10y ago
      I remember trying out Google in the early days and deciding that it is about the same quality as other search engines. I might be wrong, but I would say that it's continuous improvement that gave them their current position. Later that history was kind of rewritten that it was the genius invention of PageRank.
      - bennyg 10y ago
        Not having ads and bs all over the page helped a TON too.
        CaptSpify 10y ago
        I remember when this was the big debate as to which site was better: http://www.madisonavenuejournal.com/images/crystalball-7.jpg http://www.madisonavenuejournal.com/images/crystalball-7.jpg
        bjelkeman-again 10y ago
        Alfa Vista started as a clean interface too. But their failed monetisation efforts (ads etc) on the search home page I seem to rember triggered me to move to Google.
cscurmudgeon 10y ago
This is silly. There have been so many "wins" in AI. Get away from the hype. Go to an AI conference like IJCAI or AAAI. See what is used there.
- ma2rten 10y ago
  I think GP was specifically referring to GPU accelerated linear algebra a.k.a. deep learning frameworks.
quantumhobbit 10y ago
Are deep learning and other frameworks really that much more subject to vendor lock in than frameworks in other areas of tech? People make it seem like whichever framework wins now will own AI for the future, but transfer that logic to web development and you would expect perl and php to still be on top of the world instead of whatever the js framework of the day is. GPU acceleration seems to be a pretty big barrier to entry for upstarts. But I think that has more to do with the crappy state of tooling than intrinsic difficulty of GPGPU. Cuda showed that GPGPU could be much easier and I think there is still plenty of room for improvement. Compare the difficulty of setting up Apache a decade ago vs Nodejs today for how much simpler servers have become. Anyway Tensorflow is really hyped right now, but there is no way to know if that will last.
- seangrogg 10y ago
  In all fairness, PHP still does dominate the field - it routinely picks up new web developers, is the backing language of some of the largest well-known, simple, and open source CMS (WordPress, Magento), and inertia alone places it at ~80% of websites. Is it new/shiny? Nah. But while other languages/frameworks may get the lion's share of attention for reasons that circulate performance, concurrency, and/or scale and large companies do adopt them from time to time... PHP enjoys ridiculous levels of usage. And this is from someone that dislikes and never uses PHP.
- cs702 10y ago
  Whoa, I did not write (or even intend to mean) that TensorFlow "will own AI for the future," whatever that means. No one is saying that!!! I claim only that TensorFlow has won the "framework for numerical computation using software-specified data-flow graphs" space, at the expense of many other competing frameworks (Caffe, Theano, Torch, CNTK, etc.). In other words, if you want to build a large-scale machine/deep learning model (e.g., with tens or hundreds of millions of parameters) and you need to train this model with, say, tens of billions of samples in a cluster of multi-GPU machines (or TPUs), TensorFlow has become the go-to software infrastructure for doing that.
AIMunchkin 10y ago
I think the TensorFlow the API has indeed won. TensorFlow the Machine Learning Engine not so much. It's not derisively referred to as TensorSlow(tm) without cause.
jgalt212 10y ago
> winner-take-all space What's the reasoning behind the claim for AI frameworks to be a "winner-talk-all space"?
vonnik 10y ago
TensorFlow has kind of won the Python deep-learning community, although frameworks like Keras[0] make it easier to use. While Python programmers make up the majority of deep-learning practitioners, they don't have much penetration in enterprise, which is chiefly JVM and lower-level languages. Deeplearning4j [1] has won deep learning on the JVM. Nothing else comes close. (Disclosure: I'm one of its creators.) DL4J has the most sophisticated Spark integration, plugs into Kafka and works as a Hadoop job. It does all that while running on distributed GPUs, multiple CPUs and heterogenous hardware. It wraps cuDNN, which is faster than Tensorflow. Finally, part of our stack, JavaCPP [2], is used by the TF communities as well as other big company projects to bridge the gap between Java and C++. Dev mindshare in the form of Github stars doesn't equal revenue. Finally, there are a number of strategic problems companies face when adopting a Google project. First, they are leery of depending on Google when they also compete with it. This is particularly true because Google doesn't open source a lot of its best work, like code from DeepMind. So Tensorflow adopters are getting the leftovers in a way, and they're kneecapped in the AI race. Secondly, Tensorflow is not platform neutral. It's optimized for TPUs, which are not publicly available. It's a play to attract people to the Google Cloud. [0] http://keras.io/ http://keras.io/ [1] http://deeplearning4j.org/ http://deeplearning4j.org/ [2] https://github.com/bytedeco/javacpp https://github.com/bytedeco/javacpp
- cs702 10y ago
  Upvoting, because I agree that JVM and .NET shops, like commercial banks and industrial manufacturers, are more likely to use Deeplearning4j (DL4J) and CNTK, respectively, than TensorFlow (or anything else, really). However, those corporate shops are typically many years behind the state-of-the-art in AI, and in many, if not most, cases, they will likely end up paying for higher-level "AI services" provided by a third party than building new kinds of applications in-house with lower-level frameworks. My view is that those new AI services will be created by startups we haven't heard about yet, led by developers outside of Corporate America who by and large are betting on TensorFlow and non-Oracle, non-Microsoft stacks. Google's competitors will of course want to use their own in-house frameworks regardless. -- PS. By the way, I think DL4J is awesome. Great job!
  - 10y ago

by cs702 10y ago

astazangasta 10y ago

It's been less than a year, eh. A bit early to declare it has "already won"? There's decades of research ahead of us.

AJ007 10y ago
How many of those decades will be human driven?
- astazangasta 10y ago
  Since no one even in concept has figured out how to give an AI motivations or goals other than ones specified by humans: all of them.
  - nurettin 10y ago
    Surely someone would have tried if "mind building" was in anyone's monetary interest.
    - Jtsummers 10y ago
      People have tried. No one's succeeded. Not every endeavor is a success.
      - nurettin 10y ago
        Can you supply a list of monetary interest groups for building sentient minds?
- dmreedy 10y ago
  Barring some Einstein/Shannon-level of momentary insight that catapults understanding of the nature of intelligence forward by orders of magnitude from where it is now, likely all of them. And entirely likely that it will be more than decades.

kartD 10y ago

It's a little early if you ask me, IMO you win once you make the first killer product that changes the market Eg: search, iPhone, self-driving cars etc

ma2rten 10y ago
Google wasn't the first search engine.
- kartD 10y ago
  I said first killer (market defining and expanding product) product, iPhone wasn't the first smartphone either, but they pushed them from cool towards ubiquitous
  - ma2rten 10y ago
    I remember trying out Google in the early days and deciding that it is about the same quality as other search engines. I might be wrong, but I would say that it's continuous improvement that gave them their current position. Later that history was kind of rewritten that it was the genius invention of PageRank.
    - bennyg 10y ago
      Not having ads and bs all over the page helped a TON too.
      - CaptSpify 10y ago
        I remember when this was the big debate as to which site was better: http://www.madisonavenuejournal.com/images/crystalball-7.jpg http://www.madisonavenuejournal.com/images/crystalball-7.jpg
      - bjelkeman-again 10y ago
        Alfa Vista started as a clean interface too. But their failed monetisation efforts (ads etc) on the search home page I seem to rember triggered me to move to Google.

cscurmudgeon 10y ago

This is silly. There have been so many "wins" in AI. Get away from the hype. Go to an AI conference like IJCAI or AAAI. See what is used there.

ma2rten 10y ago
I think GP was specifically referring to GPU accelerated linear algebra a.k.a. deep learning frameworks.

quantumhobbit 10y ago

Are deep learning and other frameworks really that much more subject to vendor lock in than frameworks in other areas of tech? People make it seem like whichever framework wins now will own AI for the future, but transfer that logic to web development and you would expect perl and php to still be on top of the world instead of whatever the js framework of the day is. GPU acceleration seems to be a pretty big barrier to entry for upstarts. But I think that has more to do with the crappy state of tooling than intrinsic difficulty of GPGPU. Cuda showed that GPGPU could be much easier and I think there is still plenty of room for improvement. Compare the difficulty of setting up Apache a decade ago vs Nodejs today for how much simpler servers have become. Anyway Tensorflow is really hyped right now, but there is no way to know if that will last.

seangrogg 10y ago
In all fairness, PHP still does dominate the field - it routinely picks up new web developers, is the backing language of some of the largest well-known, simple, and open source CMS (WordPress, Magento), and inertia alone places it at ~80% of websites. Is it new/shiny? Nah. But while other languages/frameworks may get the lion's share of attention for reasons that circulate performance, concurrency, and/or scale and large companies do adopt them from time to time... PHP enjoys ridiculous levels of usage. And this is from someone that dislikes and never uses PHP.
cs702 10y ago
Whoa, I did not write (or even intend to mean) that TensorFlow "will own AI for the future," whatever that means. No one is saying that!!! I claim only that TensorFlow has won the "framework for numerical computation using software-specified data-flow graphs" space, at the expense of many other competing frameworks (Caffe, Theano, Torch, CNTK, etc.). In other words, if you want to build a large-scale machine/deep learning model (e.g., with tens or hundreds of millions of parameters) and you need to train this model with, say, tens of billions of samples in a cluster of multi-GPU machines (or TPUs), TensorFlow has become the go-to software infrastructure for doing that.

AIMunchkin 10y ago

I think the TensorFlow the API has indeed won. TensorFlow the Machine Learning Engine not so much. It's not derisively referred to as TensorSlow(tm) without cause.

jgalt212 10y ago

> winner-take-all space What's the reasoning behind the claim for AI frameworks to be a "winner-talk-all space"?

vonnik 10y ago

TensorFlow has kind of won the Python deep-learning community, although frameworks like Keras[0] make it easier to use. While Python programmers make up the majority of deep-learning practitioners, they don't have much penetration in enterprise, which is chiefly JVM and lower-level languages. Deeplearning4j [1] has won deep learning on the JVM. Nothing else comes close. (Disclosure: I'm one of its creators.) DL4J has the most sophisticated Spark integration, plugs into Kafka and works as a Hadoop job. It does all that while running on distributed GPUs, multiple CPUs and heterogenous hardware. It wraps cuDNN, which is faster than Tensorflow. Finally, part of our stack, JavaCPP [2], is used by the TF communities as well as other big company projects to bridge the gap between Java and C++. Dev mindshare in the form of Github stars doesn't equal revenue. Finally, there are a number of strategic problems companies face when adopting a Google project. First, they are leery of depending on Google when they also compete with it. This is particularly true because Google doesn't open source a lot of its best work, like code from DeepMind. So Tensorflow adopters are getting the leftovers in a way, and they're kneecapped in the AI race. Secondly, Tensorflow is not platform neutral. It's optimized for TPUs, which are not publicly available. It's a play to attract people to the Google Cloud. [0] http://keras.io/ http://keras.io/ [1] http://deeplearning4j.org/ http://deeplearning4j.org/ [2] https://github.com/bytedeco/javacpp https://github.com/bytedeco/javacpp

cs702 10y ago
Upvoting, because I agree that JVM and .NET shops, like commercial banks and industrial manufacturers, are more likely to use Deeplearning4j (DL4J) and CNTK, respectively, than TensorFlow (or anything else, really). However, those corporate shops are typically many years behind the state-of-the-art in AI, and in many, if not most, cases, they will likely end up paying for higher-level "AI services" provided by a third party than building new kinds of applications in-house with lower-level frameworks. My view is that those new AI services will be created by startups we haven't heard about yet, led by developers outside of Corporate America who by and large are betting on TensorFlow and non-Oracle, non-Microsoft stacks. Google's competitors will of course want to use their own in-house frameworks regardless. -- PS. By the way, I think DL4J is awesome. Great job!
- 10y ago