Vast.ai VS iko.ai

There are already ways to get around this. For example, renting compute from people who aren't in datacenters. Which is already a thing: https://vast.ai. - Source: Hacker News / 3 months ago

By "SETI" I assume you mean the SETI@Home distributed computing project. There's a two-way market where you can rent out your GPU here: https://vast.ai/. - Source: Hacker News / 4 months ago

- https://vast.ai/ (linked by gchadwick above). - Source: Hacker News / 5 months ago

Have you considered running on a cloud machine instead? You can rent machines on https://vast.ai/ for under $1 an hour that should work for small/medium models (I've mostly been playing with stable diffusion so I don't know what you'd need for an LLM off hand). Good GPUs and Apple hardware is pricey. Get a bit of automation setup with some cloud storage (e.g backblaze B2) and you can have a machine ready to run... - Source: Hacker News / 5 months ago

I have heard vast.ai is cheap but I haven't tried it out. https://websiteinvesting.com/reviews/vast-ai-review/. Source: 5 months ago

We built a fascinating platform, https://iko.ai, that allows you to train, track, package, deploy, and monitor machine learning models with real-time collaborative notebooks on your own Kubernetes clusters. Source: over 1 year ago

Hi, Edwin. I'm in the process of integrating Stripe to https://iko.ai. I recently discovered Portal (https://stripe.com/docs/billing/subscriptions/integrating-customer-portal) and I thank you for that. Less code for me. I'm a bit ashamed to say, but I'm having trouble with checking if the customer has a valid subscription. I'm currently only storing the customer_id in the database and retrieving the information... - Source: Hacker News / almost 2 years ago

That was one the reasons we do "bring your own compute" with https://iko.ai so people who already have a billing account on AWS, GCP, Azure, DigitalOcean, can just get the config for their Kubernetes clusters and link them to iko.ai and their machine learning workloads will run on whichever cluster they select. If you get a good deal from one cloud provider, you can get started quickly. It's useful even for... - Source: Hacker News / almost 2 years ago

We built an internal platform to streamline this that allows us to train, package, deploy, and monitor models (very shameless plug for our product https://iko.ai that we started because I was tired of watching colleagues look from the window to see if their train was here because they had to come to the office to train their model on the "powerful machine" and they spent 6 hours in commute every day and at some... Source: almost 2 years ago

We built https://iko.ai which offers real-time collaborative notebooks to train, track, package, deploy, and monitor machine learning models. Source: about 2 years ago