Per second pricing and jupyter mode is pretty nice. Like heroku you're trying to resell AWS and stay competitive which is a challenge. Anyway, this is indeed a common problem and this looks like a solid approach.
Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
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Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#42This 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 bill...
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#43Running 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)
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#44I was one of their earliest beta customers. Despite the initial quirks, the experience has been nothing but magical. It allowed me to go from code to training/model generation in one command, without any of the devops nonsense to do deal with.
While digging into deep learning, I honestly felt that the devops stuff was actually more complicated than the math/backprop/neural nets stuff.
It felt like a Heroku moment for me. They have the potential to do to Tensorflow what Heroku did to Rails. Super simple deploy!
Obviously their vision is much broader (with an entire eco-system/'hub', reproducibility, etc.), but to me atleast the first part is super useful and exciting!
One advantage they have is that GPUs are INSANELY expensive on the cloud - they can actually make it cheaper for everyone with clever binpacking and proper termination.
My advice is that in the initial stage, they should partner with all the Moocs to ensure that all deep learning students are using Floyd. It's cheaper, faster and the students can focus on the science. And they provide, 100 free hours!
Disclosure: I've known the guys for quite a while.
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#45Per second pricing and jupyter mode is pretty nice. Like heroku you're trying to resell AWS and stay competitive which is a challenge. Anyway, this is indeed a common problem and this looks like a solid approach.
Fully agree! In the longer run, I believe there might be some great opportunities wrt infrastructure. GPUs instances are super expensive (now combine with long runtimes). Self hosting infra at scale can drastically drive down prices 10x+ (we're already 2x cheaper than AWS). Till we get there, there’s a few lower hanging fruits to pick, like streamlining development processes and making things easier. Glad you like the Jupyter Notebooks!
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#46So I guess we're competitors in a sense, but congrats nonetheless! We hope to launch at least a private beta of NeuralObjects like "Real Soon Now"™. It'll be interesting to see where we decide to go down different paths, or how we take different approaches to things.
Thanks for the comment! There's lots of challenges to be solved in this space, and I'm sure there's room for all of us. Excited to see what you guys are up to. I will look forward to your beta release "real soon" :)
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#47You said you worked at MS, so you're presumably pretty familiar with Azure's offering. I'm no expert (at all) but I played with it briefly and it was all pretty slick and easy to get up and running. How does FloydHub compare to that?
I assume you're talking about AzureML Studio. It's a pretty neat UI-centric tool for building machine learning workflows! It's great if you're starting out with ML, but offers little in terms of customizability. For example, it only supports R and Python, has no GPUs, no CLI, no container support for managing reproducible environments, etc. I think these are kind of deal breakers for doing deep learning :) FWIW, I wo…
I like the ease of use to get up and running with Floydhub. What internal tools you had to solve this at Microsoft? Were they any good? I heard Facebook has their own FBLearner Flow internally for managing their ML workflows and it's pretty neat.
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#48It seems like everyone and their dog wants to solve this problem; why is it going to be you?
YC Magic?
Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#49Re: Launch HN: FloydHub (YC W17) – Heroku for Deep Learning
#50It seems like everyone and their dog wants to solve this problem; why is it going to be you?
Haha, there’s no magic and it’s difficult to say with any certainty that we’re going to make it. When we started out, we were just scratching our own itch. The AI community is amazingly open and fast paced. May be because of that, the tooling around it isn’t as mature as for, say, software development. More companies, IMHO, tend to be focused on building the next big thing _with_ AI, rather than the next big thing _for_ AI. With the increasing popularity of the space and the relative infancy of the state of tooling, we believe now might be a good time to tackle this problem.
That said, it’s hard to say how things are going to turn out. This is my first startup after working in the corporate for 6 years and it’s been amazing so far. Learning a lot, and excited for what’s ahead! :)