All of this can be done without connecting edge devices directly to the internet (and potentially allowing inbound connections). The question is not why they have networking, but why the connectivity is such that an attack like this is even possible.

> True. But I think "int" would be the right choice anyway in almost all case.

It's the worst choice. int is 32-bit on most 64-bit architecture/compiler-versions that matter.

I know. This does not make it a bad choice.

Which options are there, really? There is re-write, fixing, and mitigation.

We have a lot of legacy code that probably contains many bugs that could be exploited.

We could either stop using that legacy code, i.e. re-write and move to a newer library / package. Or fix the old code.

I now believe that "fixing" the code is actually in reach for an organization such as Google, which has deep pockets, frontier AI models, and a history of working on open source. Spend a few billions to walk through every package that runs on a common Linux installation, find potential issues and robustify the code.

The code is FOSS, it's been sitting there in the open for its lifetime available for anyone to inspect, discover bugs, and fix (patch or rewrite)

The inspection/discovery part is what has accelerated; the fix, patch or rewrite, has not.

People smugly yelling on the internet to rewrite because they have a new toy isn't constructive - why aren't they out there doing it already?

Some say water is never wet, it makes wet.

How would a single agent work that long, the context window would overflow pretty quickly, no?

It's mostly a scale thing. Transformers scale better when you have a lot of training data. (Not saying CNNs don't scale, but it's way more difficult to tune the hyper parameters).

For smaller training data sizes, transformers don't have a clear advantage over CNNs. CNNs are still the way to go if you have problems that are not too complex, and especially constraints regarding inference costs. Think of a small edge device / sensor that counts apples in your apple picking machine.

What we sometimes see is that a backbone is trained using transformers, then a smaller CNN is destilled from that (DinoV3 for example).

And by buying all of the available compute.

That doesn't appear to be the only thing necessary. Grok is still much worse than other closed source models, despite access to more compute.

Conversely, DeepSeek are relatively compute starved and produce a usable model (definitely not frontier but 10x cheaper).

Uranium, Plutonium were created by fusion processes as well. Fission extracts energy put there by the fusion inside a dying star.

Most of the heavy elements beyond ruthenium or so were created by neutron star mergers rather than red giant or supernova nucleosynthesis[1]. It could be argued that this is technically fission, since neutron stars are, to a first order, giant atomic nuclei.

[1]: https://upload.wikimedia.org/wikipedia/commons/3/31/Nucleosy...

But those fibers disturb the crystal lattice of the ice, so surely there is some tradeoff?

Alloying copper with tin to make bronze produces a material which is stronger and more durable than either component, and this works because the tin disturbs the copper's crystal lattice, which restricts the mobility of dislocations, which in turn reduces the plasticity of the alloy.

I do not know if cellulose fibers have a similar effect in ice, but in general, if you can trade the feature that is causing a problem for one that will not, you are improving things.

Aka it makes it less brittle, which ultimately makes it stronger?

It makes it less ductile, which means it's harder and more resistant to deformation. Bronze is more brittle than copper.

Adding fibres to already brittle materials improves their resilience to tensile forces mostly

So you’re saying it makes it more brittle? Because the opposite of ductile is brittle.

Or are you saying it increase yield strength, because that is a separate property, yes?

It's also other devices. I used to get a notification that my wife's AirPods would be following me. It only got silenced when we formed an Apple family.