andrewfromx

tried to take a waymo today in LA: https://i.imgur.com/ufoDjue.png

https://www.youtube.com/watch?v=OzWd7HyIkZ0 30 mins of knowledge!

the best way is to search reddit for specific terms and reply to comments.

this story must have been indexed in the model https://allthatsinteresting.com/aimo-koivunen

Quality Comparison (Rough Rankings)

Tier 1 - Frontier Models:

Claude Code 3.7 - Excellent reasoning, context understanding, complex refactoring

GPT-4o with o3 - Outstanding at complex logic, multi-step planning

Aider + Gemini 2.5 - Very strong code generation and modification

Tier 2 - Good Local Models:

CodeLlama 70B - Decent but requires significant hardware

Llama 3.2 70B - Good general reasoning, okay at code

Tier 3 - Practical Local Models:

CodeLlama 13B - Basic code understanding, simple tasks

Llama 3.2 7B/13B - Limited coding ability, frequent errors

Tier 4 - Fast Local Models:

Llama 3.2 3B - Very basic, often produces buggy code

rust > go (in this case) https://github.com/traefik/traefik or I'll bet you could fix the go code to be way more efficient too. It's not that it HAD to be in rust i guess. But if you are going to re-think it anyways might as well use the language you want.

i think you are missing the elephant in the room: ai

what skills do you having using

https://www.anthropic.com/claude-code

https://aider.chat/

etc? that's the cli to master

i think you just say "i wrote this" because the definition of being the author has changed. You birth it. You watched it get created and tweaked small problems along the way. It wouldn't have been born without you. You wrote the prompts! And all your peers are doing the exact same thing. It can just be assumed everyone is using some AI tool.

kinda cool, we just added this OCR feature to our tv show / movie tracking app. I did it in iOS first and then asked claude for pseudo code to capture all the logic:

https://gist.github.com/andrewarrow/b6a20109ccb96dd7336419c8...

demo video: https://www.youtube.com/shorts/2qwPTsa82x4

beta testing info: https://www.reddit.com/r/showffeur

Now adding it to android will be easy!

oic. maybe add an ascii poll display until it's installed?

how does it look on someone's phone who doesn't have the app installed yet?

Google glass in the bathroom - like a locker room at a gym? Yeah, but then again any picture taken of someone fully clothed AI can just remove the clothing. There was this new "Take it down Act" law just passed. But with AI it's almost moot? Any picture can now be just altered to be explicit.

you know the story of callerID from the 1990s? The whole idea that it was a person's right to see WHO was calling them was deemed crazy. Before this it was consider your right to call people anonymously. Now when we see "Unknown Caller" no one answers. In 2030 this little orb will be so standard if someone wants their privacy back it will be seen the same way. They are the ones wanting to call someone anonymously.

it's a race now for which vibe coding tool will offer copyright clean code?

My point is this:

Having worked at multiple IoT companies with many millions of connections. This is the way.

People tend to overcomplicate things with K8S. I have never once seen a massively distributed IoT system run without a TON of headache and outages with k8s. Sure, it can be done, but it requires spending 4-8x the amount of of development time and has many more outages due to random things.

It's not just the network, its also the amount of config you have to do to get a deterministic system. For IoT, you dont need as much bursting (for most workloads). Its a bunch of devices that are connected 24/7 with fairly deterministic workloads, that are usually using some type of TCP connection that is not HTTP, and trying to shove it into an HTTP paradigm costs more money and more complexity and is not reliable.

https://news.ycombinator.com/item?id=44032250

While Kubernetes theoretically allows for simple iptables-based routing, in practice, very few production environments stop there. Most clusters do use CNIs, kube-proxy, Service abstraction, and often external load balancers or Ingress controllers, which together form a nontrivial networking stack.

The claim that kube-proxy is “not designed for use in proper production systems” is simply incorrect. It is widely used in production and supported by Kubernetes core. While it has limitations—especially with high-connection-load environments—it is still the default in most distros, and even advanced CNIs like Calico and Cilium often interact with or replace kube-proxy functionality rather than ignore it.

If kube-proxy is just a stopgap, why do so many managed Kubernetes platforms like GKE, EKS, and AKS still ship with it?

While it’s true CNIs are plugins and not core to Kubernetes, this outsources complexity rather than eliminates it. Different CNIs (e.g., Calico, Cilium, Flannel, etc.) use different overlay models, BPF implementations, or routing approaches.

Even in a CNI with kernel-fast path routing, pod churn, rolling updates, or horizontal scaling still introduce issues. Service IPs are stable, but pod IPs are ephemeral, which means Long-lived TCP clients pinned to pod IPs.

You can design a lean Kubernetes network path with minimal abstractions, but: You lose things like dynamic service discovery, load balancing, and readiness-based traffic shifting. You must manage more infra manually (e.g., configure iptables or direct routing rules yourself). You’re fighting against the grain of what Kubernetes is designed to do.

| Aspect | Direct EC2 (No K8s) | Kubernetes (K8s Pods) |

|-------------------------|-------------------------------------------------------|-------------------------------------------------------------------------------------|

| Networking Layers | Direct connection to EC2 instance (optional load balancer). | Service VIP → kube-proxy → CNI → pod (plus optional external load balancer). |

| Load Balancing | Optional, handled by ELB/ALB or application. | Built-in via kube-proxy (iptables/IPVS) and Service. |

| IP Addressing | Static or dynamic EC2 instance IP. | Pod IPs are dynamic, abstracted by Service VIP. |

| Connection Persistence | Depends on application and OS TCP stack. | Depends on session affinity, graceful termination, and application reconnection logic. |

| Overhead | Minimal (direct TCP). | Additional latency from kube-proxy, CNI, and load balancer. |

| Resilience | Connection drops if instance fails. | Connection may drop if pod is rescheduled, but Kubernetes can reroute to new pods. |

| Configuration Complexity| Simple (OS-level TCP tuning). | Complex (session affinity, PDBs, graceful termination, CNI tuning). |

when dealing with long lasting TCP connections, why add that extra layer of network complexity with k8s? I work for a big IoT company and we have 1.8M connections spread across 15 ec2 c8g.xlarge boxes. Not even using a NLB just round-robin DNS. Wrote our own broker with https://github.com/lesismal/nbio and use a packer .hcl file to make the AMI that each ec2 box boots. Using https://github.com/lesismal/llib/tree/master/std/crypto/tls to make nbio work with TLS.

you can just copy paste any question you want into AI.

a little more faq and about us? I was so confused when I went to the site.

umm what about the resistance? John Connor can teach us how to fight back!

i ask an LLM why did Alcatraz shut down to learn about this current news of its re-opening and it told me Alcotraz has NOT shut down.

nice, i sent it to a top wikipedia editor i know

you gotta find the one that works for you.