https://ai.google.dev/gemini-api/docs/models/gemini-3.5-flas...

The market does work, but it’s a giant paper clip AI and needs regulation in order to not turn everything into paper clips.

But if it’s just about starting over from 0 being the AI apocalypse or something, I’m sure it’ll be more manageable, and the fix could hopefully be done on a cave wall using a flint spear tip.

It’s not so much a message to you as a message to the model from itself.

You’re allowed to rebind a var defined within a loop, it doesn’t mean that you can’t hang on to the old value if you need to.

With mutability, you actively can’t hang on to the old value, it’ll change under your feet.

Maybe it makes more sense if you think about it like tail recursion: you call a function and do some calculations, and then you call the same function again, but with new args.

This is allowed, and not the same as hammering a variable in place.

Immutability doesn’t have this connotation.

Sometimes, it seems that this just makes parts of their offering seem aged though, while they (presumably) sit around being discontent with the currently available alternatives. Especially now with LLMs which age faster than anything.

If US GDP is ~30 trillion, the program would have to capture ~20% of that to achieve your target.

Do check my math, I’m not sure I’ve got this right.

Other than that, there’s literally nothing I need from Microsoft currently.

MS is little more than a rent seeker to me.

LLMs are incredibly good at social engineering when we let them, whereas I could write the code to emit "you're right" or "that's not quite right" without involving any statistical prediction.

Ie., as a method of persuasion, canned responses are incredibly inefficient (as evidenced by the annoyance with them), whereas we know that the LLM is capable of being far more insidious and subtle in its praise of you. For example, it could be instructed to launch weak counter arguments, "spot" the weaknesses, and then conclude that your position is the correct one.

But let's say that there's a monitoring mechanism that concludes that adjustments are needed. In order to "force" the LLM to drop the previous context, it "seeds" the response with "You're right", or "That's not quite right", as if it were the LLMs own conclusion. Then, when the LLM starts predicting what comes next, it must conclude things that follow from "you're right" or "that's not quite right".

So while they are very inefficient as persuasion and communication, they might be very efficient at breaking with the otherwise overwhelming context that would interfere with the change you're trying to affect.

That's the reason why I like the canned phrases. It's not that I particularly enjoy the communication in itself, it's that they are clear enough signals of what's going on. They give a tiny level observability to the black box, in the form of indicating a path change.

I get that it’s tradeoffs, but erring on the side of the human being correct is probably going to be a safer bet for another generation or two.

It’s a canned phrase in a place where an LLM could be much more creative to much greater efficacy.

The complement appears to be, “actually, that’s not right.”, a correction mechanism.

1: https://news.ycombinator.com/item?id=45137802