It also have mine automatically grabs a spot at my gym when spots are released because I always forget.

I'm just playing with it, it's been fun! It's all on a VM in the cloud and I assume it could get pwned at any time but the blast radius would be small.

So to help with that I built this OpenClaw skill, it pulls from 22 government data sources and synthesizes them according to my own interests. It has allowed me to understand better how my local government actually works, and now gives me a weekly update on upcoming town halls, trash pickups, and other events I might want to attend.

I'm relatively new to the world of civics, discussions and contributions are more than welcome.

Comments URL: https://news.ycombinator.com/item?id=47591321

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I do a lot of green field research adjacent work, or work directly with messy code from our researchers. It's been excellent at building small tools from scratch, and for essentially brute forcing undocumented code. I can give it a prompt like "Here is this code we got from research, the docs are 3 months out of date and don't work, keep trying things until you manage to get $THING running".

Even for more production and engineering related tasks I'm finding it speeds up velocity. But my engineering is still closer to greenfield than a lot of people here.

I do however feel less connected to the code, even when reviewing thoroughly, I feel like I internalize things at a high level, rather than knowing every implementation detail off the dome.

The other downside is I get bigger and more frequent code review requests from colleagues. No on is just handing me straight up slop (yet...)

I think there is some behind the scenes prompting from claude code (or open code, whichever is being used here) for plan vs build mode, you can even see the agent reference that in its thought trace. Basically I think the system is saying "if in plan mode, continue planning and asking questions, when in build mode, start implementing the plan" and it looks to me(?) like the user switched from plan to build mode and then sent "no".

From our perspective it's very funny, from the agents perspective maybe it's confusing. To me this seems more like a harness problem than a model problem.

From our perspective it's very funny, from the agents perspective maybe very confusing.

| As robotics moves toward end-to-end AI systems, stuff needs to stay on GPU memory, not shuttled back and forth across processes through a networking stack.

NVIDIA actually is addressing this with NITROS: https://nvidia-isaac-ros.github.io/concepts/nitros/index.htm...

And ROS native buffers: https://discourse.openrobotics.org/t/update-on-ros-native-bu...

I still think you can enjoy it without caring much about religion.

>> Are they worried that by splitting devs into groups of AI experience they might be measuring some confounder that causes people to choose AI / not AI in their careers?

The developer sample size was small (16 people in the original study) and the task sample size is larger (~250 tasks). I think the worry is variance in developer productivity would totally wash out any signal.

[1] https://github.com/NVIDIA-ISAAC-ROS/greenwave_monitor

1. Share a cohesive and inspiring vision for the project.

2. Understand your skills, strengths/weaknesses etc and try to give you work that challenges you / help you grow / are interesting.

I think these are rare and can be hard to do (I'm now trying to do it myself!), but when it happens it's very motivating.

In our case the jumps where because we also have PTP disciplining the same system clock, when you have both PTP and NTP fighting over the same clock, you will see jumping with the default settings.

For us it was easier to just do a one time NTP sync at the beginning/boot, and then sync the robots local network with only PTP afterwards.

We actually disable NTP entirely (run it once per day or at boot) to avoid clocks jumping while recording data.