schreiaj

Good news, in the US you don't need to choose... and by need, I mean you probably get both.

You almost certainly do not want an LLM to do that. Leap71 actually has computational models generating functional rocket engines that way. You could absolutely wrap a tool like that in a shell and handle control with an LLM and not need anywhere near the tokens.

Thats the thing - these models see and predict tokens. For any real engineering you get more bang for your buck using math.

As someone who has been working on this space for a while (not affiliated with govbase) this is really hard. Between eliminating the sycophancy that seems baked into LLMs and dealing with generalized hallucinations - it's freaking hard. I spent this weekend trying to figure out how to get my system to stop telling me the SAVE Act would be fine because it doesn't say what the process for if birth certificate doesn't match current id.

No, I haven't found a good solution yet - I'm going down a rabbit hole of basically crawling the entire federal register for referenced legislation and then adding in an adversarial agent to see if that can spot gaps.

Would be cool to see some logs on server load, it's one thing to claim "scale to thousands of requests per second" it's another to show the logs of a €4 VPS doing it. I don't doubt it, when I did a similar experiment with golang I never noticed any real issues (aside from a misconfiguration at the proxy requiring a min size on the SSE response) but it would still be neat to see the logs/active users.

SQLite via libsql is my go to for lightweight stuff.

Has vector embedding columns out of the box.

Can you add repos after starting the container? What about persisting indexes across restarts?

Still, neat. Glad to have an easy to deploy open source tool like this.

The number of times I've looked at the speed limit my car thinks it is supposed to be and seen 80 on what is effectively a residential road...

Or that the highway near my house that the car seems to think is 35.

Barring also adding some sort of managed database owned by the state I don't see this being remotely viable.

Squarespace.

Different company than Square.

Maybe if the only thing you're reacting to is other vehicles or the road. The number of times I have to slam on my brakes on that particular road because of animals running into the road is way too high. And no, not always deer. I've come around curves and just had someone's dog sitting in the middle of the road on multiple occasions because for some reason people think it's totally safe to just let their dogs roam.

It’s also difficult to determine if someone is speeding from data.

For example the road I live off of according to the speed limit the car thinks goes from 40 to 65 to 25 to 65 to 40 in about a 4 mile span. Spoiler it does not. It is 40 the whole way. But according to the car I am either going 25 under, 15 over, or exactly the right speed.

(And the 65 section in the middle? Blind corner. Idk where it’s getting its data but it is very very wrong)

No, I actually like that approach better than the traditional ECS approach. Though I assume it both adds and removes some complexity. In a traditional ECS approach you can depend on certain systems running in certain orders because you depend on them having run. Then you refactor, forget this dependency, and suddenly you have changed behaviors and you have no idea why until you remember this. If, as I assume, you have per step immutability that removes a whole class of bugs at the cost of a slight increase in complexity.

Your ECS API looks very similar to that of Bevy's, were you inspired at all by that?

From the little I can see of it, it looks like you don't allow writes to data and instead prefer to return a new thing based on a query? Based entirely on the below.

``` @system def control( sensor: Query[WorldPos, WorldVel, Goal], rw: Query[RWAxis, RWForce] ) -> Query[RWForce]: ```

I assume this is due to the distributed nature of your simulation framework?

Either way, neat. Very interested in this though for more terrestrial applications.

Yes and no, for text type stuff? Yes you're right. But I think in the vision space synthetic data will remain useful for a lot of things. I'm currently working on building a pipeline for personal projects to go from CAD models of environment to segmented training data. So far it looks almost as useful as real world data at a fraction of the cost of manual labeling.