jablongo

I guess it makes the behavior more predictable?

Why do you need a plug-in for this? You can just ask the agents to do all this stuff and it works fine in my experience.

I'm going to put the dmg up on a website next week maybe. I just tested LAN for the first time with a few friends and it was very fun, but we found some major imbalances.

I built a real time strategy game using Bevy, sort of like Starcraft 2, once I learned that SC3 would be an FPS. I relied on a team of claude fable/opus/sonnet agents to develop assets in blender, generative models for the art, and to do most of the coding, but I have a feeling that Bevy's design played a role in shaping the game and the ease of adding new features. The whole thing took a week of running the agents in the background / overnight and the result is very fun to play and includes a LAN mode. Not the level of polish and balance of SC2, but its actually comparable, which is mind blowing to me.

This is really funny. A less extreme example is how much domain-specific terminology in Reinforcement Learning and Control Theory/Model Predictive Control refer to the same underlying phenomena, but we must translate between the two. I understand there are many unique concepts as well, but it would be so helpful if the overlap here used the same terminology and notation.

yea for a real comparison between models this would have been better, but I have a feeling he just wanted to play the best possible version of PoP.

This isn't really comparing the models; he's using successive models to improve his rebuild of Prince of Persia. Either way though, it will be interesting to see which games, if any, resist implementation via LLM. I recently started a Starcraft 2 like real time strategy game with Fable managing many Opus agents and it got to a playable 3d game with 3 races, 40+ units, and 40+ buildings in 3 days.

This is understood I think. It's just how to effectively prevent it or reverse it thats not known.

I'm pretty sure this isn't designed to be marketed towards T1Ds and any benefits will be a happy coincidence. I think this is going to be aimed at health nerds who want to monitor their planned ketosis.

Yea I'm all about finding the uses for this after the fact. However, it seems unlikely that people who are struggling to afford (or get insurance to cover) insulin would be able to afford a cgm or cgm/ckm in this scenario. Also not sure how it's possible to ration insulin and keep your bg stable, but I wouldn't put it past the most skilled T1s out there. In the sick w/ flu case, thats true, but then whats the treatment action? I still think euglycemia + DKA is an edge case.

In diabetics, DKA is preceded by hyperglycemia. Meaning, a CGM would tell you earlier that you are at risk for DKA than a CKM, a CKM would only tell you after you got it. Hence grahar64 is absolutely correct that as far as we know now, this provides no benefit to people at risk of DKA that a CGM does not already provide. I'm sure there will be some benefits but its really not clear at this point.

In theory patents are also to protect smaller players (though not dirt poor), from getting their work ripped off by bigger players after demonstrating feasibility. The idea of being an "inventor" professionally only really works with patents. Software patents pushes this model to logical extremes though. I run a small startup that trains models for medical devices and the only way to get any of the large players to care about implementing improvements you make (and not rip you off) seems to be to have some patent protection. They are mostly interested in the patents as assets to prevent their competitors from acquiring. In all honesty I'm not completely convinced on software patents either but we've had to adapt.

But I don't think Fable or even Opus are ever used as the backend in voice mode. It has to respond in real time so I think in voice mode it's always using Sonnet.