Great project. There's been multiple approaches/tools in the space(top of my head I can think of e2b, arrakis, claude's new tool). how is this different?
Thanks! I'll review Arrakis and come back. E2B is often considered harder to setup and less AI engineers friendly for direct stack contributions, as Katakate is the only alternative fully implemented in Python (core modules, Typer CLI, FastAPI, Python SDK).
Our native K8s support and exposition of K8s API also makes it friendly to devops.
Finally, our deploy/infra stack is lean and tightly fits in a single Ansible playbook, which makes it easy to understand and contribute to, letting you rapidly gain full understanding and ownership of the stack.
Not the op but to me personally: yes. Facial structure, lips, eyes.. The configuration tilts towards an expression that I interpret differently. A friend of mine is Asian, I've learned to be better at it, but to me he at first looked like having flatter affect than average.. People of color look more naive than average to me, across the board, probably due to their facial features. I perceive them as having less tension in the face I think (which is interesting now that I think about it)
I have a background in East Asian cultural studies. A lot more expressions are done via the eyes there rather than the mouth. For the uninitiated, it's subtle, but once you get used to it, it becomes more obvious.
Anthropologists call that display rules and encoding differences. Cultures don’t just express emotion differently, but they also read it differently. A Japanese smile can be social camouflage, while an American smile signals approachability. I guess that's why western animation over-emphasizes the mouth, while eastern animation tend to over-emphasize the eyes.
Why would Yakutian, Indio or Namib populations not have similar phenomeon an AI (or a stereotypical white westerner who does not excessively study those societies/cultures) would not immediately recognise?
AI trained on Western facial databases inherits those perceptual shortcuts. It "learns" to detect happiness by wide mouths and visible teeth, sadness by drooping lips - so anything outside that grammar registers as neutral or misclassified.
And it gets reinforced by (western) users: a hypothetical 'perfect' face-emotion-identification AI would probably be percieved a less reliable to the white western user than the one that mirrors the biasses.
Yeah most enterprise software barely works and is an absolute maintenance nightmare because they're sprawling distrivuted systems.
Ask yourself: how does an enterprise with 1000 engineers manage to push a feature out 1000x slower than two dudes in a garage? Well, processes, but also architecture.
Distributed systems slow down your development velocity by many orders of magnitude, because they create extremely fragile systems and maintenance becomes extremely high risk.
We're all just so used to the fragility and risk we might think it's normal. But no, it's really not, it's just bad. Don't do that.
Enterprises are frequently antipattern zoos. If you have many teams you can use the modular monolith pattern instead of microservices, that way you have the separation but not the distributed system.
Sorry to hear that! We're working to make search better, but we still have a long way to go. I'm curious where you felt the biggest pain points with search.
If we were good enough to have drugs that could work with that precision we’d eliminate an enormous category of things. The side effects are usually the scary things. We have drugs that can cure the symptoms of depression and anxiety - they just so happen to be insanely addictive, cause respiratory depression, loss of coordination, and you quickly build a tolerance to them.
It's basic economics that more workers with fewer rights lower wages across the board. "They make what Americans do" when there is a continuous flow of competing labor. Sure. What would companies pay if they didn't have these exploitable workers? Would the companies have opened new office closer to where Americans are educated? Certainly, one of those two would happen.
But this is why the government should enforce existing laws and include provisions like must pay x above median average salary for the role to discourage fraud.
But it does negate the claim that H-1Bs are paid the same wage.
If your claim only applies to a subset of visa workers in a subset of companies, then refine the claim to use a word like "some", and it will be a trivial claim that I agree with.
