Distill VS iko.ai

Distill was a new take at publishing research/ideas in deep learning in a visual way: https://distill.pub/ I love their articles and while it was hard to sustain, the quality of the ones in their are pretty good. They provide some tips and templates on how to develop such visual storytelling articles. - Source: Hacker News / 7 months ago

Explainable AI is far from early stages. Read into anthropic ai’s work in mechanistic interpretability like toy models of superposition along with the rest of the transformer-circuits papers. Read chris olah’s distill papers. Read neel nanda’s recent work on reverse engineering how language models grok modular addition. Read kevin meng’s work on locating and editing facts inside of gpt. Read openai’s paper on... Source: 11 months ago

I also wasn't aware of either The Pudding or distill.pub. So thanks for just mentioning those. Source: about 1 year ago

Anything from Setosa [0] is really good. It contains interactive, animated illustrations of several Machine Learning ideas. I _loved_ reading papers from Distill Pub [1] as they contained interactive diagrams. My most favorite one so far is the thread on Differentiable Self-organizing Systems [2]. I liked the lizard example very much as it is interactive, and lizards grow lost organs back. I think this is funny.... - Source: Hacker News / over 1 year ago

If you include deep learning in CS then https://distill.pub/ has a lot to offer in this category. - Source: Hacker News / over 1 year 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