Machine learning development requires a lot of computing power. Specifically GPU powered computing. GPUs are super expensive on incumbents like AWS. This creates a big divide between compute rich and compute poor developers and teams. Thus becoming a bottleneck for over 5 Million ML devs.
At Q Blocks, we have figured out a new way to solve this. To bring access to the most powerful GPUs at 1/10th the cost with the reliability and scalability of a cloud.
Try Q Blocks and save significant costs for training and tuning your next ML model
Google Cloud accelerates every organization’s ability to digitally transform its business and industry by delivering enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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Based on our record, Google Cloud Platform seems to be a lot more popular than QBlocks Cloud. While we know about 170 links to Google Cloud Platform, we've tracked only 1 mention of QBlocks Cloud. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There's a middle way: qblocks.cloud - This platform that enables access of unused GPU servers across the globe. It works like a traditional cloud by offering scalability, security and reliability while being upto 80% low cost for AI workloads. Also, offers inbuilt Jupyterlab, AI framework, GPU driver support out of the box. Thus no time wasted in server setup. Source: over 1 year ago
Assuming you have Google Cloud account and installed gcloud CLI. - Source: dev.to / about 1 month ago
In 2008, Google launched AppEngine. This product predates the formal existence of Google Cloud and can be considered Google Cloud's first offering. - Source: dev.to / about 1 month ago
In this article, you'll learn how to set up the NetBird CLI to ensure a secure connection to a Kubernetes cluster on the Google Cloud Platform (GCP), complete with a fail-safe route for uninterrupted access. - Source: dev.to / about 2 months ago
Try to utilize your AWS free tier as much as you can, you can also register a new account if you have exhausted the current one. Alternatively, you can use Google Cloud (GCP) to rent virtual machines from this cloud service provider - you can get $300 credit here or here (NOTE: Please read instructions carefully to get your credits). - Source: dev.to / 4 months ago
A VM is the original “hosting” product of the cloud era. Over the last 20 years, VM providers have come and gone, as have enterprise virtualization solutions such as VMware. Today you can do this somewhere like OVHcloud, Hetzner or DigitalOcean, which took over the “server” market from the early 2000’s. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft's Azure also offer VMs, at a less... - Source: dev.to / 4 months ago
Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Frontegg - Elegant user management, tailor-made for B2B SaaS
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Vultr - VULTR Global Cloud Hosting - Brilliantly Fast SSD VPS Cloud Servers. 100% KVM Virtualization