3 ms·
According to my customers and users yes? Granted, we do a lot more than just that though. Dl4j itself has a decent sized user base. Ranging likely from your p
by agibsonccc 8y ago
According to my customers and users yes? Granted, we do a lot more than just that though.
Dl4j itself has a decent sized user base. Ranging likely from your phone maker to your bank and retail store.
We have our own software distro too which is why I'm commenting on this. We don't try
to boil the ocean with a bunch of tech though.
There's a whole new crop of companies focusing on solving bits of the ML problem well rather
than trying to do storage and god knows what else.
My point here about you guys is you're trying to compete in what is largely a commodity market.
People don't need all this stuff.
Simplicity won here. It's not about better tech.
You guys have the same pitch MapR does and largely the same problem: Better tech is only part of the problem with adoption. You need customers,
users, and a clear business
model when going to market.
Cloudera and Horton ran one playbook that at least somewhat worked (it got them public)
and now they can focus on competing with the cloud vendors,
which made the right decision and just made commonly used software easy to use.
- jamesblonde 8y agoWe 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 agoYou 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 agoOk, 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 agoI 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 agoA 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 agoExactly!
- xapata 8y agoWho needs to do that? Not many companies. Deep Learning is overhyped, just as MapReduce was.