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Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

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Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#61

Post by narenst »

sarthakjain wrote: post #43

Running DL and sharing results is a huge pain. I feel versioning is a big challenge, also experiments with multiple architectures are a pain since large parts of the same calculations are repeated. Do you also solve this problem? (Feature request if not)

Yes, our Enterprise offering allows for building more complex workflows. Everything (code, parameters, environment and data) is versioned for reproducibility. One of the big value-adds is efficient caching of parts of the pipeline to avoid repetitions and save resources. We have noticed that this usually results in 10x increase in the number of experiments run by teams.

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#62

Post by saip »

bfortuner wrote: post #40

Nice! There is a real need for this in the market right now--especially among students, who struggle to setup working environments. I really benefited from your early Github project aimed to make setting up DL machines easier. Curious how defensible your product will be in the event Heroku/AWS come in with a competitor?

Defending against big players with almost infinite resources is always an interesting problem. Kind of have to hope they don’t come at you head on :) That said, there might be other aspects that come into play. For example, the market is fragmented with big providers each having their own frameworks and infra that they prioritize (Google - Tensorflow/GCP, Facebook - Torch, Microsoft - CNTK/Azure, Amazon - MXNet/AWS, Baidu - PaddlePaddle, etc.) Since there is yet no clear winner, which will likely be the case for the near future, vendor lock-in is not really desirable. We intend to be backend / framework / language agnostic.

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#64

Post by narenst »

ryanchan001 wrote: post #59

The github page for floydhub has a lot of open source projects. What parts of floyd is not open sourced?

Deep Learning is a very open source friendly community - most of the popular frameworks/algorithms are in fact open source. In fact, Floydhub is built on top of a lot of open source projects. We definitely considered open sourcing the core components of Floyd but the Rethinkdb fiasco made us "rethink" that. Instead, we are supporting the open source community by hosting Deep Learning Docker images, popular datasets, and projects. In the future, we are planning to open source more parts of Floyd but not all (similar to Github).

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#65

Post by saip »

cr0sh wrote: post #58

This sounds interesting and useful - I hope you guys make it! A couple of years ago I worked for a local cloud server provider, as a backend developer. Some of the work I did moved the company into deploying VPS instances using OpenStack. Our backend code was mainly PHP-based; so we used OpenCloud for the purpose - extending it where needed (when we started it didn't support all we needed; I extended things in such a…

That’s awesome! ML to some extent, and DL to a large extent are still not considered mainstream enough by many. The big players (Google, Facebook, Baidu) seem to recognize this and invest appropriately, but the others not so much yet. That’s hopefully a sign of a burgeoning market!

Good luck with your Udacity class! If you want to play around, take a look at our guide for Neural Style Transfer: http://docs.floydhub.com/guides/style_transfer/

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#66

Post by saip »

rajsat wrote: post #42

This looks neat! We have been doing a lot of deep learning for NLP at our startup recently. Several “engineering bottlenecks” in the process (1) managing multiple jobs is definitely worth solving. git for deep learning would be neat (2) collaborating is a pain when the team is remote. I guess this ties to (1) too. And oh, about the time I forgot to turn off our GPU instance for a couple of weeks… racked up a nice bil…

We’ve definitely felt the bane of forgetting to turn off some really expensive GPU instances. Efficient scheduling and spinning instances up/down as required is one of the first things we built to cut down on the costs.

Git is an apt analogy. The search space of hyperparameters is usually fairly large for most DL algorithms, so a good amount of experimentation is required to tune them. Things can start to get haywire without end-to-end version control of code, data, parameters, results, environments, etc. Definitely one of the core problems we solve.

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#67

Post by narenst »

ravibala1 wrote: post #60

You guys seem to make setting up Deep Learning infrastructure easy for data scientists which is awesome! What about situations where the end user/business isn't sure exactly how to use Deep Learning (which algorithm, how to partition the data into training and result sets, stability of results etc.) for the problem/data set at hand? Would it be possible to use FloydHub as a marketplace of sorts where I could hire a d…

Yes, we are planning to build a FloydHub marketplace for talented data scientists to find gigs. We believe Floydhub can showcase their work and expertise easily (similar to StackOverflow) and help find a suitable partners to work with. A wide range of industries like Medical, Oil and Finance have been collecting huge amounts of data and now with Deep Learning, they can effectively make use of that. So I definitely see a rise in demand for deep learning practitioners and we want to support them on Floydhub.

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#68

Post by penagwin »

saip wrote: post #22
whodunser wrote: post #13

I have been using your docker container for 6 months or so now, thanks for putting it together :) The jupyter jobs look neat, but I assume they are charged continuous time? Would be cool if somehow that only ended up charged for compute time, but I understand that would be difficult. Are these instances guaranteed to be in a given region, for if I wanted to route more complex debug output / intermediate files to S3?

Thanks - glad you found it useful! The attention and feedback that I got from building dl-docker has been terrific. Definitely one of the reasons we started working on this seriously :)

Little off topic, does DL-docker work in Ubuntu on Windows for the GPU?

Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning

#69

Post by saip »

penagwin wrote: post #68
saip wrote: post #22

Earlier quoted context omitted.

Thanks - glad you found it useful! The attention and feedback that I got from building dl-docker has been terrific. Definitely one of the reasons we started working on this seriously :)

Little off topic, does DL-docker work in Ubuntu on Windows for the GPU?

You mean bash on Windows? The CPU version of dl-docker will work on Windows! But unfortunately, the GPU version does not. You would need GPU passthrough, which is currently not supported. See https://github.com/NVIDIA/nvidia-docker/issues/197
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