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We don't. We are the only on-premise vendor with proper support for GPUs and python. We are a full data science stack, backed by Hadoop. We even have Kubernetes

We don't. We are the only on-premise vendor with proper support for GPUs and python. We are a full data science stack, backed by Hadoop. We even have Kubernetes for model serving. And python in the cluster (with conda environments). And we have customers and funding. Nothing like MapR. And none of the legacy mapreduce crap.

agibsonccc 8y ago
You bundle way more than they do and on top of that have your own file system just like mapr does. Your pitch is still about differentiated tech, not a large install base, a differentiated business model and something related to people like a good partner ecosystem. Your pitch here requires tons of services. People don't know how to use all of this stuff especially on prem. It takes more than just code to build a business. I say this as someone who's been doing this since 2013. It's not easy.
- jamesblonde 8y ago
  Ok, now you're changing your angle. Differentiated tech is what we are all about - that is ok by me (for now). If you want to train DNNs on a hundred GPUs today on-premise on TensorFlow, come to us, we can do it. They can't.
  - agibsonccc 8y ago
    I don't think I changed my angle here? I'm still addressing the same point. Tech doesn't matter. Simplicity does. Even in our own product line, we only do a small subset of this. We don't even require a cluster to run. We also work with tech that people use. You are currently competing with horovod and kubeflow. eg: "competing with free" You need more than that to survive. Generally, that comes down to services.
    - ironchef 8y ago
      A slightly different wording is it comes to using the tech... which is either through services or through adoption / operationalization (which... with complexity... is very difficult)
      - agibsonccc 8y ago
        Exactly!
  - xapata 8y ago
    Who needs to do that? Not many companies. Deep Learning is overhyped, just as MapReduce was.

agibsonccc 8y ago

You bundle way more than they do and on top of that have your own file system just like mapr does. Your pitch is still about differentiated tech, not a large install base, a differentiated business model and something related to people like a good partner ecosystem. Your pitch here requires tons of services. People don't know how to use all of this stuff especially on prem. It takes more than just code to build a business. I say this as someone who's been doing this since 2013. It's not easy.

jamesblonde 8y ago
Ok, now you're changing your angle. Differentiated tech is what we are all about - that is ok by me (for now). If you want to train DNNs on a hundred GPUs today on-premise on TensorFlow, come to us, we can do it. They can't.
- agibsonccc 8y ago
  I don't think I changed my angle here? I'm still addressing the same point. Tech doesn't matter. Simplicity does. Even in our own product line, we only do a small subset of this. We don't even require a cluster to run. We also work with tech that people use. You are currently competing with horovod and kubeflow. eg: "competing with free" You need more than that to survive. Generally, that comes down to services.
  - ironchef 8y ago
    A slightly different wording is it comes to using the tech... which is either through services or through adoption / operationalization (which... with complexity... is very difficult)
    - agibsonccc 8y ago
      Exactly!
- xapata 8y ago
  Who needs to do that? Not many companies. Deep Learning is overhyped, just as MapReduce was.