I come from reading about CRDTs from Evan Wallace and also having built a product used by >40M users.
It applies to software products too!
In their words…
If you want to build products, use React or even vibecode; you will learn higher-level issues of solutions to problems (i.e. people problems rather than machine problems), not how to push data/state/computation around. The problem is solving a need.
Neither is good nor bad; just be clear about your goals and then it’ll be easy to decide if you want to follow Zynga’s cofounder, Jonathan Blow, or Notch! And before you rush to answer… consider whether any of them are happy.
For people who recommend against learning these skills because “what Carmack did is not possible anymore.”… well, if what you look for is money then yeah! But, if you just want to learn for the love of the game, then that would be a very bad advice!
"it's hard to justify burning a LoRA for most uses" -> Not really, it's literally cheaper on Krea than using ChatGPT Images; NBP and GPT-Images 2.0 are quite expensive, you'd be surprised. LoRAs are one of our most stickiest features (this doesn't mean they are intuitive; this just means that customers who use it, suddenly are retained way more because of how much better their images become). But yeah, anything out there doesn't offer a nice training UIs like Krea where you can just drag-and-drop a moodboard and get a LoRA in a few minutes. It literally takes only a few minutes on Krea; definitely not "N hours for GPUs to churn".
I appreciate the skepticism but we find internally that this model is used more than Nano Banana for many cases like moodboarding (also, 4x cheaper than NBP never hurts). Agentic workflows are compatible with Krea 2 so I’m not sure I follow there. If you are talking about an edit model, that’s coming too.
Also, we are on par with them in t2i benchmarks, check the artificial analysis link I posted in my top comment.
And you cannot re-train nano banana or ChatGPT to understand your brand, which is what our customers complain about constantly.
Plus open-source! It’s hard to do an apple to apple comparison.
There is a lot of discourse about it on Reddit. Check the AMA link I put in the comment above for learning more. The basics is it wasn’t released when we started and we use it for internal models and hope to do further open source releases.
We are releasing the weights and a _juicy_ technical report---at least given current industry standards. In it we describe data curation/captioning, model architecture, post-training, RL pipelines, prompt expansion, style references, and our infrastructure in great detail.
When it comes to theweights themselves, there's actually 2 releases:
* Krea 2 Turbo. This model is both guidance- and timestep- distilled for faster inference.
* Krea 2 RAW. This model is actually meant to be hackable/fine-tunable
One of the things we think the (open) LLM community does well is release models in different sizes and also at different stages of the training pipelines; we are releasing two checkpoints at both the mid-training and post-training stage. This is rare in the image & multimedia community, so we can't help it but to feel proud of this release.
I thought sharpening my craft in software for a decade would help; but, the more I read ancient scriptures, the more sense they started making -- and this is as someone who's been mostly agnostic.
Seeing people working on nostalgic apps, wealth-pursuing prompt management tools, or ideological open-source alternatives. I've worked myself in many types of software of similar kinds, and I've found.. not much at the other side of the pursuit.
Some call it “הֶבֶל”; “तृष्णा”; or, “تَكَاثَرَ”...
I'm the cofounder of Krea (https://www.krea.ai/). We build creative tools and large-scale infrastructure for multimedia teams. Users range from hobbyists to world-renowned creatives: architects behind the World Trade Center or creative teams at Apple.
We treat research, engineering, and creativity as first-class citizens; we want engineers for our research, product, and supercomputing teams.
Just say GenAI-free; organic software (written by organic agents as opposed to silicon-based ones); or, literally anything that actually means what you wrote.
I'm the cofounder of Krea (https://www.krea.ai/), a company building creative tooling and large-scale infrastructure for multimedia teams. Users range from hobbyists to world-renowned creatives: architects behind the World Trade Center or creative teams at Apple.
We treat research, engineering, and creativity as first-class citizens. We're looking for engineers to join our research, product, and infra teams.
As suspected, this project was possible, in part, because of LLM models. I have also been exploring in using LLMs for Gameboy Color testing.
There is something quite ironic about old hardware becoming increasingly useful due to current developments in AI research. I wonder about the repercussions of this.
krea.ai | Senior Backend Engineer | San Francisco, CA | ONSITE | https://www.krea.ai
krea does AI research & builds AI tools for image generation, video generation, node-based workflows, LoRA training, and more. Small, mostly in-person team with a view of Alcatraz from the office window. Our users range from hobbyists all the way to professional designers at Apple or architects at firms behind The World Trade Center or Burj Khalifa.
We're looking for senior backend engineers. You'd work across our SvelteKit app (Postgres, Redis, Docker, ClickHouse), Python ML inference on GPU clusters, and k8s clusters across multiple cloud and GPU providers.
Some recent projects:
- building canary deploys with cookie-sticky traffic splitting
- implementing durable execution for long-running workflows
- designing our public API with OpenAPI docs auto-generated from Zod schemas
- implementing enterprise-grade authentication, authorization, and permissions
- optimizing ML inference for our hosted image generation models
We care way more about first-principles and core engineering skills rather than specific shenanigans around programming languages or particular tooling—knowing a lot about old UNIX principles is a plus though.
You should be comfortable owning things end-to-end. Experience with GPU infra is a plus. Many of us have some kind of creative background, it helps when building tools for creatives but is not a requirement by any means.
To apply, email [email protected] (use the +hn suffix to make sure your email is prioritized!)
I come from reading about CRDTs from Evan Wallace and also having built a product used by >40M users.
It applies to software products too!
In their words…
If you want to build products, use React or even vibecode; you will learn higher-level issues of solutions to problems (i.e. people problems rather than machine problems), not how to push data/state/computation around. The problem is solving a need.
Neither is good nor bad; just be clear about your goals and then it’ll be easy to decide if you want to follow Zynga’s cofounder, Jonathan Blow, or Notch! And before you rush to answer… consider whether any of them are happy.
For people who recommend against learning these skills because “what Carmack did is not possible anymore.”… well, if what you look for is money then yeah! But, if you just want to learn for the love of the game, then that would be a very bad advice!