kadoban

> And, back then, this was the normal or is ice covering the normal?

"Normal" is probably not a very useful framing. We're currently in an interglacial period in an ice age. So, on one scale we'd expect ice there, on one scale we'd not. On another scale we're just waiting for the sun to swallow the Earth and burn it all away. What's "normal" out of that?

If you happen to be asking if the current human-caused warming is an issue, yes it is. The Earth doesn't care, and "normal" doesn't care. We do though, we're fucking up our environment pretty good and it's causing misery and death.

Even if it just ends up being a base to throw and llm at to update, isn't that still useful? Sounds to me like it'll probably skip the whole part where my agent would have to give me 4 different plans, searches the internet, argues that it's impossible, works out subtools to generate, etc.

Can't tell if they plan to release the model weights? Very uninteresting if not. Otherwise seems like potentially some nice post training.

> This has been known for a long long time too (decades+), its not a recent discovery.

We've known what caused the effect for a long time. We did _not_ know how they achieved the nanoparticle mix and size in the glass, last I checked. This story is about someone actually taking the basic idea and making a real object.

You are implying that the law cannot be dehumanizing?

One practical-ish thing you could reasonably do with this (beyond just better understanding how models work so you can make better choices/tradeoffs), is post-train some of the small-to-medium models, fine-tune them on your own data or priorities.

You don't need to change many weights, relatively, to add capabilities or modify behavior. Look up LoRas for instance.

I'm of the opinion that post-training existing models is an area with a lot of benefit and fun in the near future (it's already being done here and there of course).

I doubt you _really_ have to know everything in this course to know how to do that, but I'd want this as background personally for it.

Relatively sure it's not. I'm using pi and I can't find any place it's doing any such thing. My current theory is that it's behavior trained into the model either accidentally or intentionally, probably during post-training in some harness that _does_ give hints of that sort?

Any idea what the ~rule is or how it's meant to work? I assume it'd work better if I can wire up my harness to handle it, but no idea. It didn't seem to know itself, from it's training. I didn't search too much yet though.

DeepSeek v4.1 flash seems to do this thing where it starts saying that we should wrap up the current work and start again "next session" (whatever that means), that the "context budget" is almost up, or some other wording I'm forgetting, as the context gets longer.

I've taken to just manually making it write a handoff file and clearing context completely. I'm pretty much manually compacting instead of my harness doing it. Feels weird, but it does work.

Almost any movie makes heavy use of CGI. Combining them with practical effects, like stop-motion, yields better results than sticking to one technique.

The practical grounds the digital, and the digital enhances the practical.

What has been ruined?

Hm? I see a model download link to hf.

These people building on or tweaking open models is _great_, it should be encouraged. There's a lot of room to spend some effort improving models in various ways that the original creators didn't have time for.

Your favorite agent is really good at organizing media files, if you haven't tried that and it happens to fit your situation. I usually make it write out a list of move/renames as a script so I can double-check, but bet it's fine without most of the time.

You could cloak where it's coming from more easily this way.

Yeah, this would be a much better version of the well-meaning but poorly produced youtube videos I typically use to fix things up around the house. Probably a lot of value there.