i am not sure how expensive it will be to generate shadows from fog ? that was the first thing i noticed when i looked at the article, specifically the 'foggy cube' thingy.

linux on this would be *soo* cool !

I don't think that it would take that much.

It is my understanding that the A18 CPU is pretty well understood already. AFAIK it doesn't have the new architecture that is keeping the Asahi team from supporting the M4 and M5 for example.

But I guess we'll have to wait for devs to get their hands on a Neo device

If Asahi runs well on this I'd be very tempted to get one as a dedicated Linux machine

M4 is basically an upgraded version of the A18.

M1 was A14, albeit upscaled.

slop-steganography is that a name || a verb ?

> When AI writes the software, who verifies it?

oh thats quite simple: the dude / dudette who gets blamed is the one who verifies it.

yet another chromium clone iirc.

It's basically ungoogled-chromium with manifest v2 support. Chromium is just technically superior than Firefox. It's a simple fact. The problem is the telemetry and AI features they added in it, which Helium or ungoogled-chromium doesn't have.

>It's a simple fact

I'd love to hear why you say this.

> It's a simple fact

one mans fact, is another ones fodder :o)

xeno-kovah is responsible for that one. see the most excellent 39c3 video "asahi linux porting linux to apple silicon" for more information.

the money quote (at least for some)

    In fact, the current state of M3 support is about where M1 support was when we released the first Arch
    Linux ARM based beta; keyboard, touchpad, WiFi, NVMe and USB3 are all working, albeit with some local 
    patches to m1n1 and the Asahi kernel (yet to make their way into a pull request) required. So that 
    must mean we will have a release ready soon, right?

and how do you know it is not going to be an inverted j-curve ?

Ha ha. I suppose an inverted j curve technology would offer short term productivity but yield long term slow-downs. I can see aspects of that - perhaps using agents people write code that quickly adds the next feature but overall is not maintainable. Or they quickly write a project plan but in the long term it doesn’t result in good payoffs. I’ve already observed both of these.

I think the hardest part to figure out will be delineating the illusion of productivity from actual productivity.

In the other hand - we do have empirical research (from the economist in this article) even from 2023 showing LLMs ability to offer real productivity in certain tasks : https://www.nber.org/papers/w31161. And the models have become much more better since then.

So it’s probably a question of if we can use them for what they are good for without being lulled by the sirens song of fake productivity.

didn’t cv raman prove just that via his raman-effect for which he got the noble prize ?

Kind of, but not really.

Rayleigh scattering is elastic (only the direction changes), whereas Raman scattering is inelastic (energy, that is color changes in addition to direction) scattering.