
Colab Pro - rahidz
https://colab.research.google.com/signup
======
fibrennan
Just wanted to share a Colab alternative I work on called Gradient[0] (also
includes a free GPU).

Some of the key differences:

\- Faster storage. Colab uses Google Drive which is convenient to use but very
slow. For example, training datasets often contain a large amount of small
files (eg 50k images in the sample TensorFlow and PyTorch datasets). Colab
will start to crawl when it tries to ingest these files which is a really
standard workflow for ML/DL. It's great for toy projects eg training MNIST but
not for training more interesting models that are popular in the
research/professional communities today.

\- Notebooks are fully persistent. With Colab, you need to re-install
everything every time you start your Notebook.

\- Colab instances can be shutdown (preempted) in the middle of a session
leading to potential loss of work. Gradient will guarantee the entire session.

\- Gradient offers the ability to add more storage and higher-end dedicated
GPUs from the same environment. If you want to train a more sophisticated
model that requires say a day or two of training and maybe a 1TB dataset,
that's all possible. You could even use the 1-click deploy option to make your
model available as an API endpoint. The free GPU tier is just an entrypoint
into a full production-ready ML pipeline. With Colab, you would need to take
your model somewhere else to accomplish these more advanced tasks.

\- A large repository of ML templates that include all the major frameworks eg
the obvious TensorFlow and PyTorch but also MXNet, Chainer, CNTK, etc.
Gradient also includes a public datasets repository with a growing list of
common datasets freely available to use in your projects.

Those are the main pieces but happy to elaborate on any of this or other
questions!

[0] [https://gradient.paperspace.com](https://gradient.paperspace.com)

~~~
m0zg
After spending 5 minutes on the site, I could not figure out what an offering
comparable to Colab Pro would cost me (i.e. single instance of a notebook
hooked up to P100), and bailed. In contrast, Google puts pricing front and
center, which makes me feel better about their value prop in spite of the fine
print around limits and preemptibility.

~~~
fibrennan
Thanks for the feedback. Instance pricing is currently listed here
([https://gradient.paperspace.com/instances](https://gradient.paperspace.com/instances))
but we're working to make it simpler.

~~~
m0zg
Thanks for not being defensive. I do believe there's not enough competition in
this space, so I wish you guys the best of luck.

Let's look at the page you linked. On the top of the page it says "free GPU"
and for some reason lists three GPU options of varying capacity, all three
"free". But slightly below it's very much "non-free GPU" territory. Which is
it? Is it free, or are you going to hit me with a bill later? And if it's
free, what's the catch? The "free" stuff on the top of the page invites me to
create an instance. Hmm, ok, let's see maybe I'll see the actual pricing
there? Nope, it wants me to create an account, which I'm not going to do just
to see how much something costs.

~~~
snuxoll
6-hour time limit on free instances, there’s a banner at the top of the page
linking to an announcement with this detail.

Might be wise to make this more visible on the pricing page.

------
freediver
Good idea, but it's the first premium product that I've seen where the pitch
is 'you _may_ get certain features if you subscribe'. In another words there
is no guarantee and a premium subscriber may still end up with same GPU as a
free user. You may end up with a high-end V100 (not available to free) might
be a better pitch.

~~~
Confiks
A fair use policy, which you seem to be referring to [1], is pretty standard
fare for many 'invididual user' products to exclude heavy-use groups.

However, they could at least define expected and minimum capacity. They might
omit it because the business in this – aside from capturing users in their
ecosystem – is arbitraging wholesale GPU price against consumer monthly needs,
along with scaling the free tier.

[1] "Why aren't resources guaranteed in Colab Pro?" on
[https://colab.research.google.com/signup](https://colab.research.google.com/signup)

~~~
londons_explore
I would be happy with an explanation of "none of our service is guaranteed,
but if we don't manage to give you your chosen GPU more than 80 percent of the
time, you are free to cancel, and we will refund your final months
subscription payment".

~~~
asdfasgasdgasdg
Since the subscription is monthly with no commitment, I think the viewpoint is
probably something like "if it's not meeting your needs then unsubscribe." A
refund of $10 is not going to be economically meaningful to folks who want to
subscribe to this service. "Chosen GPU more than 80% of the time" sounds nice
but it opens you up to adverse selection. They aren't looking for customers
who want to pay ten bucks a month to rent 80% of a high performance GPU.
That's not nearly enough money for that kind of commitment.

~~~
dr_kiszonka
It would be economically meaningful to ML students.

~~~
dannyw
The free version of Colab is pretty great for ML students.

------
iddan
Colab is the best notebook I've ever used. It is a real game-changer and I can
totally understand why people who use daily would pay for it.

~~~
bitxbit
We should really thank Mathematica for the notebook format.

~~~
anidh
Did mathematica invent the notebook format? Just curious..

~~~
jamesbrock
Yes, my understanding is that Theodore Gray invented the "computational
notebook" for Mathematica in the 90s. Here is the best writeup of the history
of the notebook that I've ever read.
[https://www.theatlantic.com/science/archive/2018/04/the-
scie...](https://www.theatlantic.com/science/archive/2018/04/the-scientific-
paper-is-obsolete/556676/)

~~~
mistrial9
quick look at Wikipedia shows Mathematica: "Initial release June 23, 1988;"

Mathematica took at least a year or more to write.. so that goes back perhaps
to 1986.. 90s is way off...

------
mark_l_watson
I am tempted to sign up. Colab is very usable on Safari for iOS/iPad.

I invested 18 months ago in a GPU setup for home. Really convenient but I
somewhat regret the purchase. I used to spin up GCP GPU instanced when needed
and that was not convenient. Colab is very convenient.

$10/month for better GPUs and longer sessions seems like a good deal.

------
hobofan
I hate to be the boy who cries "Google will cancel this service", but this
offering just seems strange.

With a very low price point coupled with not that huge of a user base, this
will end up making how much for Google? $1MM/month? $10MM/month? Either would
be negligible for them.

~~~
zelly
Like others said, subscription products are very profitable. The target
demographic for this has disposable income and would see this as an
investment. A lot of people will sign up and never use it.

Don't forget that the alternative was just free. For all we know this is the
way they're breaking even on Colab to prevent shutting it down.

~~~
Tenoke
Why would people signup and never use it? I'd expect most of those people to
just use the free Colab.

~~~
zelly
People who need it for one project, use it heavily for a month or two, then
forget to turn off billing.

------
ludwigschubert
Can anyone see a reason why they wouldn’t just allow you to provision (and pay
for) a persistent Google Cloud VM instead? (I currently do that manually and
need port forwarding to a machine that runs Jupyter.)

It’s hard for me to understand why Colab would build such a vague pro tier
instead of the simplest possible solution: let me pay for my compute.

There’s so much more potential, too; they could offer whole clusters on
demand, with really simple Python integrations say using dask, or ray.

~~~
TaylorAlexander
Perhaps this is more profitable. I’ve heard that Colab has become very popular
for people doing certain kinds of deep learning, but that the wait for GPU
instances has been frustrating. It seems a paid tier to get priority is
directly targeting those users.

~~~
dzhiurgis
I've recently used Colab to run some pretty cool StyleGAN notebooks. Finally I
can replicate so many cool projects without bending my head how to setup gcp,
virtualbox or install tensorflow into geforce macbook.

Doubt I'll pickup deep learning as a profession by this, but it's a step
forward.

------
m0zg
Not sure who this is geared towards. People mostly use Colab to share GPU-
dependent work from what I can tell. How would that work on a paid
subscription? Do others need to pay to run the notebooks you shared? Can they
use their "free" account?

As far as utility for research, as a researcher, I _already have_ several
local GPUs at my disposal, and I only use notebooks to kick the tires on
things and visualize. The moment something starts to look like it's useful, I
move it to a real *.py file where it's more maintainable and diffable.

Edit: actually I now think I know who this is geared towards. It's geared
towards people who aren't going to really use it, and don't mind to pay
$120/yr (+tax) for something they don't use. Which, IMO, is pretty smart.

------
minimaxir
A preemptible P100 + VM on Google Compute Engine is about ~$0.45/hr, so to
exceed that value with Colaboratory Pro (ignoring conveience factors) you'd
need to train for more than 22 hours in a month. Which, for deep learning, is
not too unreasonable.

Reading between the lines of both the signup page and up-to-date FAQ, it seems
like the free TPU in Colab notebooks will be depreciated, which isn't too
surprising.

~~~
sillysaurusx
Has anyone here actually tried to use preemptible GPUs on GCE? You're lucky if
you can get the VM to stay up for more than 10 minutes.

Litany of failure here:
[https://twitter.com/theshawwn/status/1174480402779648000](https://twitter.com/theshawwn/status/1174480402779648000)

Perhaps I just got unlucky and the situation is improved now. But it was a
waste of a day for me.

~~~
boulos
Disclosure: I work on Google Cloud.

Sorry about that. We (I) had screwed up and allowed users to smash themselves
into the wall of "Huh, you keep getting preempted, but there's technically a
slot right here". We've re-enabled some backpressure to keep you from getting
hit over and over again, and instead see a stockout error when you should
probably try another (less full) zone.

~~~
sillysaurusx
Hey, neat! Thanks for your work. I was hoping that this was the case, and I
haven't tried since September. But I'll give it another shot now.

~~~
boulos
Feel free to send me an email (contact info in profile), if you want to go
back and forth.

------
dankle
> For now, Colab Pro is only available in the US.

~~~
mkl
Yes, they should have led with that instead of finished with it.

------
bhl
I wonder who made the decision to spin this out into a commercial product;
maybe it has to do with Google's push into the cloud further? I always thought
Colab was just an experimental tool; it's still under the research.google
domain.

------
jonbaer
I wish they would connect Colab under
[https://script.google.com](https://script.google.com) so you can run a
notebook at interval times, something akin to what
[https://github.com/TensorTom/colabctl](https://github.com/TensorTom/colabctl)
does.

------
ccarpenterg
I've been using Colab for over a year now. I train deep learning models on NLP
and medical imaging datasets.

It's a great tool and it lets you focus on the code and the models, instead of
the hardware and OS. But $9.99/month is a little expensive for my taste.

You can't customize it and if they change something you have to install
software by hand sometimes. It should be $1.99/month, that's the kind of price
I'd pay for this basic cloud computing service.

edit: I use Colab to play with ML models. I really don't think it's possible,
for instance, to train a model on Imagenet using Colab. So Colab is similar to
the microwave, if you want to cook a serious recipe you should use a real
kitchen.

~~~
lewis1028282
I mean when modern GPUs are $1000 I'm curious how you think $9.99 is too much.

~~~
m0zg
Not to disagree, but P100 is not a "modern" GPU. It's based on Pascal, so it's
a couple of generations behind. Throughput-wise it's roughly equivalent to
1080ti. Which is still something like $600, so your point stands.

~~~
lupire
Plus the supporting hardware to run and cool it.

------
wildermuthn
A lot of comments are missing the value here: cheap and easy TPU access for
hobbyist use of deep learning models that need TPUs for fine-tuning and/or
inference (GPT-2, I’m looking at you).

------
bitxbit
This is so much better than buying your own hardwares.

------
agluszak
I wonder how long it takes until Google shuts down the free service. It's so
easy to abuse it. And what Google gets in return?

~~~
panchicore3
For example learning about the type of abuse and how to sort out issues while
free, so product future version can be sold as tested?

------
gizmodo59
Some content in their github repo:
[https://github.com/googlecolab](https://github.com/googlecolab)

------
fulafel
This seems to be a hosted Jupyter service, right mybinder, is that right?

~~~
LegitShady
Google Colab is a hosted jupyter notebooks service and is free. It includes
the use of a Tesla k80. Runtimes reset after 12 hours

This is the pro/paid offering with fewer limitations and better resources.

------
lupire
\--

~~~
jrockway
Probably because it's easier to buy something that costs $10/month instead of
"maybe it will be $0, maybe it will be $300,000, we'll see at the end of the
month!"

When you're using your own money to pay for cloud resources, that unbounded
worst case is pretty scary.

~~~
eru
Google Cloud offers tools to limit your worst case expenses upfront.

~~~
jrockway
But you have to admit that if you're just some scientist who wants to GPU-
accelerate their Python notebook, "click here to pay $9.99" is a lot better UX
than "just log into the Google Cloud Console and change 83 settings!"

~~~
eru
Yes, definitely.

------
zapf
There's so much data in this universe, people don't know what to do with it.
When people don't know what to do, an industry grows to let them "feel" they
are doing something useful.

