I 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.
I think partnering with MOOCs is a great idea. I've been taking the Deep Learning Foundations Nanodegree from Udacity and thought it would be awesome if we got some sort of discount to try this out. Course developers have been trying to get us AWS credits for a while now. What would be the best way to contact the guys?
Hey! Glad you brought this up. We've gotten quite a few requests from students enrolled in Udacity courses and have been helping get them set up & run their class projects on Floyd.
Here's our instructions for the Self Driving Car Engineer nanodegree program: https://github.com/floydhub/CarND-Term1-Starter-Kit. Happy to do the same for your class as well! How can I reach you? Feel free to to mail us directly: founders@floydhub.com.
We've also reached out to folks at Udacity to see if we can offer any official support for the courses.
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.