snowzach

FWIW, I have been running regular Pop using the Cosmic Store for a while now. It's nice and snappy.

I think this very much depends on the agent. My wife is an agent and busts her ass. When she's a seller agent, if it's small jobs like painting a room, covering up spots, changing a massively outdated light fixture, she does it her self. She's spent days a time landscaping.

Also when it comes to pricing, it helps to know the market. She will list a house for 8% under market value because she knows it will draw interest and end in a bidding war with escalation clauses.

She also knows other agents and other lenders and that's very important when you have a timeline. One offer may look good but you know the agent and know they will give you an artifically high offer and then ask for 10's of thousands in remedies. Or if you're trying to get a deal done on a timeline so you can get another house and a buyer comes in with a lender that's just notoriously bad at doing things on time. You may take an offer for a few thousand less when you know a deal will end on time.

Like most things, you get what you pay for and there's plenty of people out there willing to take your money and do nothing. There are good realtors and bad ones.

I run this one: https://github.com/joohoi/acme-dns It's super simple and has a REST API for updating records.

I pick Kubernetes because I want to manage software and not manage servers. I think it gets a lot of hate because people look at helm charts that are designed to support all possible software configurations and they are quite confusing. If you break it down to the basic pieces of configuration it's not really any more complicated than say a docker-compose file. Just a little more verbose.

Have you actually tried it? I didn't really notice any lag at all. I believe the Stadia controller connects directly to WiFi to skip the hop on whatever you happen to be playing on and reduce latency. Was actually pretty surprised.

An interesting thought I've wondered about as well. I imagine the risks outweigh the benefits. I would think the same thing would happen when planting a forest (granted it taking much longer to produce an effect)

I actually did something similar with a really cheap micro-controller+Arduino with an OLED screen and an Echelon Fit stationary bike. It connects via Bluetooth and displays Peleton compatible stats. https://github.com/snowzach/echbt

1. I built it to integrate with Home Assistant and security systems. I was trying to use Tensorflow on a Raspberry Pi and the dependencies were a nightmare. Tensorflow in general is a nightmare to compile and run IMO. I got to thinking, what if I could make all the deps inside of a docker container. What if I could run it remotely. It was born out of that.

2. As for base64, I'm not sure of a better way to support sending raw image data over JSON (in REST mode) In some ways I think GRPC is a better medium than JSON (it supports either) as GRPC supports sending the RAW bytes. What leads you to believe GRPC isn't the right transport? Plus you can do it in a stream format if you want to do a lot of video.

The only limitations I can think of are that Tensorflow supports a myriad of CPU optimizations so providing a single container image that has all the right options is basically impossible. I created one that has what I think are some of the better options (AVX, SSE4.X) and then an image that basically should run on any 64 bit intel compatible CPU. To get optimized options you need to build the docker container yourself which can take the better part of a day on slower CPUs.

With that said, I also provide ARM32 and ARM64 containers that actually run semi-okay on Raspberry Pis and and other ARM SBCs. I can run the inception model on a Pi4 on a 1080p image in about 5 seconds which is pretty good IMO.

Shameless plug, check out DOODS: https://github.com/snowzach/doods It's a simple REST/gRPC API for doing object detection with Tensorflow or Tensorflow Lite. It will run on a Raspberry Pi. It actually did support the EdgeTPU hardware accelerator to make the Pi pretty quick for certain models. They broke something so I need to fix EdgeTPU support but it's still usable on the Pi withe the mobilenet models or inception if you're not in a hurry.