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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.
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.
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…
I found Gradient and Paperspace pricing to be incredibly opaque, and even a bit deceptive. First of all, Colab works on a "resources are free, just not guaranteed" model. When I was about to sign up for Developer, with "Free + Low-Mid Instance Types", I expected that I would have reasonable, shared access to low-mid instances as part of my subscription. (otherwise.. what am I paying for? Don't charge me... to charge…
The Colab model of "resources are free, just not guaranteed" model” that you mentioned is literally identical to Gradient: The free tier includes spare capacity at no cost just like Colab. You can upgrade to access high-end instances eg the NVIDIA V100. These additional instances do not have a max runtime as well. I can’t see how this would be a con given this additional option is simply not available in Colab.
Gradient does not have a $5 deposit for storage, the free plan does not cost anything. There is no credit card required. In fact, Gradient doesn’t charge for storage at all.
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…
The "Contact Sales" button on the landing page makes things even more confusing. On the one hand you're using abusive practices like the one above to grab attention, something I usually associate with cheap, low-quality consumer products. On the other hand, your main call-to-action is "Contact Sales", something associated with white-glove enterprise-type products.
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.
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 clust…
As such, I don't think there would be a market for quick and dirty scratchpads backed by rock solid but expensive dedicated compute.
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.
This is a very cheap price.
Earlier quoted context omitted.
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.
Why would people signup and never use it? I'd expect most of those people to just use the free Colab.
Earlier quoted context omitted.
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] "Wh…
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".